a65adcc2e5
Sources: extracted from two upstream archives (skill-repo, skills-main),
merged with the following policy:
- 15 broken symlinks (pointing to /Users/jameslee/.cc-switch/skills or
../../.agents/skills on a foreign machine) discarded
- 3 real name collisions with identical content (ai-pair, ifind-http-api,
zhipu-websearch) kept as one copy
- Functional overlaps deduped keeping the strongest variant:
- docx family: kept docx (official, full toolchain) + docx-cn
(GB/T 9704 Chinese official-document constants),
dropped docx_writer (no scripts, name collided with docx)
- humanizer family: kept humanizer-zh (6 zh reference docs),
dropped humanizer (en, redundant for CN workflow)
- Skills that only ran in a foreign environment removed:
ablemind-ops, app-publish, hlb-design-system, openclaw-adj-skill,
claude-driver
- alphapai excluded from this public repo because its SKILL.md hard-coded
live credentials
Result: 25 skills, 572 files, ~7.5 MB.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
309 lines
12 KiB
Python
309 lines
12 KiB
Python
"""
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PPT 渲染引擎
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"""
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from pathlib import Path
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from typing import Dict
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from datetime import datetime
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import hashlib
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import json
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import pandas as pd
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from pptx import Presentation
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from ppt_station.models.job import Job
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from ppt_station.config import settings
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from ppt_station.connectors import ConnectorFactory
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from ppt_station.transformers import DataFrameTransformer
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from ppt_station.renderers import TextRenderer, TableRenderer
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from ppt_station.utils import get_slide_layouts
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from ppt_station.chart_builder import create_combo_chart
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class PptEngine:
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"""PPT 渲染引擎"""
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def __init__(self):
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self.text_renderer = TextRenderer()
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self.table_renderer = TableRenderer()
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def render(self, job: Job) -> Path:
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"""
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渲染 PPT
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Args:
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job: 任务配置
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Returns:
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生成的 PPT 文件路径
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"""
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# 1. 加载数据（共用）
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raw_dfs = {}
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for name, datasource in job.datasources.items():
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print(f"正在加载数据源: {name}")
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raw_dfs[name] = ConnectorFactory.load_data(name, datasource)
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# 2. 数据转换（共用）
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dfs = DataFrameTransformer.apply_transforms(raw_dfs, job.transforms or {})
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# 3. 按模式分发
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if job.mode == "composer":
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prs = self._render_composer(job, dfs)
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else:
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prs = self._render_template(job, dfs)
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# 4. 添加元数据
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if job.output.add_metadata:
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self._add_metadata(prs, job)
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# 5. 保存文件
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output_path = Path(job.output.path)
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if not output_path.is_absolute():
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output_path = settings.output_dir / output_path
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output_path.parent.mkdir(parents=True, exist_ok=True)
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if output_path.exists() and not job.output.overwrite:
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raise FileExistsError(f"输出文件已存在: {output_path}")
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prs.save(str(output_path))
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print(f"PPT 已保存: {output_path}")
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return output_path
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# ------------------------------------------------------------------
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# Template 模式（原有逻辑，零修改搬入）
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# ------------------------------------------------------------------
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def _render_template(self, job: Job, dfs: Dict[str, pd.DataFrame]) -> Presentation:
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"""Template 模式渲染：基于模板 + slides 配置"""
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# 加载模板
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template_path = Path(job.template.path)
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if not template_path.is_absolute():
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template_path = settings.templates_dir / template_path
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if not template_path.exists():
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raise FileNotFoundError(f"模板文件不存在: {template_path}")
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prs = Presentation(template_path)
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# 准备渲染上下文
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context = {"params": job.params or {}}
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# 获取幻灯片版式
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slide_layouts = get_slide_layouts(prs)
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# 渲染每一页
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for i, slide_spec in enumerate(job.slides):
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print(f"正在渲染幻灯片: {slide_spec.id}")
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# 如果需要指定版式，则创建新幻灯片
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if slide_spec.layout:
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if slide_spec.layout not in slide_layouts:
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raise ValueError(f"未找到版式: {slide_spec.layout}")
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slide = prs.slides.add_slide(slide_layouts[slide_spec.layout])
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elif i < len(prs.slides):
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# 使用现有幻灯片
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slide = prs.slides[i]
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else:
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# 使用默认版式
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slide = prs.slides.add_slide(prs.slide_layouts[0])
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# 渲染文本
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if slide_spec.texts:
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self.text_renderer.render(slide, slide_spec.texts, context)
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# 渲染表格
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if slide_spec.tables:
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for table_spec in slide_spec.tables:
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if table_spec.source not in dfs:
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print(f"警告: 数据源 '{table_spec.source}' 不存在")
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continue
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self.table_renderer.render(slide, table_spec, dfs[table_spec.source])
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# 渲染图表 - 使用新的 chart_builder
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if slide_spec.charts:
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for chart_spec in slide_spec.charts:
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if chart_spec.source not in dfs:
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print(f"警告: 数据源 '{chart_spec.source}' 不存在")
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continue
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df = dfs[chart_spec.source]
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try:
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create_combo_chart(
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slide=slide,
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data=df,
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shape_name=chart_spec.shape_name if hasattr(chart_spec, 'shape_name') else None,
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)
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except Exception as e:
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print(f"警告: 图表渲染失败: {e}")
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return prs
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# ------------------------------------------------------------------
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# Composer 模式（新增）
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# ------------------------------------------------------------------
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def _render_composer(self, job: Job, dfs: Dict[str, pd.DataFrame]) -> Presentation:
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"""Composer 模式渲染：基于 PageComposer + pages 配置"""
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from ppt_station.composer import PageComposer
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from ppt_station.composer.themes import resolve_theme
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theme = resolve_theme(job.theme or "jp_finance", aspect_ratio=job.aspect_ratio)
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composer = PageComposer(theme=theme)
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default_lc = job.default_layout_config
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for page_spec in job.pages:
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data = self._resolve_data_refs(page_spec.data, dfs, default_layout_config=default_lc)
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composer.add_page(page_spec.layout, data)
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return composer.prs
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def _resolve_data_refs(self, data: dict, dfs: Dict[str, pd.DataFrame],
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default_layout_config=None) -> dict:
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"""解析 data 中的 datasource/source 引用，替换为实际 DataFrame
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语义规则:
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- datasource (新 canonical key): 始终视为数据源引用
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- source: 值匹配已知数据源时视为引用并 pop；否则保留为脚注文本
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- footnote: 始终保留，用于页脚渲染
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执行顺序（修复嵌套 layout_config 类型错误）:
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1. 顶层 datasource 解析
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2. 嵌套 datasource 解析（不转 config 对象）
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3. 注入 defaults（全部仍为 dict，安全合并）
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4. 统一转对象（顶层 + 嵌套）
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"""
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resolved = dict(data)
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# Step 1: 顶层 datasource 解析
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ds_key = None
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if "datasource" in resolved:
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ds_key = "datasource"
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elif "source" in resolved and resolved["source"] in dfs:
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ds_key = "source"
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if ds_key:
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resolved["df"] = dfs[resolved.pop(ds_key)]
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# Step 2: 嵌套 datasource 解析（不转 config 对象）
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for key in ("left", "right", "top", "bottom"):
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if key in resolved and isinstance(resolved[key], dict):
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sub = dict(resolved[key])
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sub_ds_key = None
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if "datasource" in sub:
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sub_ds_key = "datasource"
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elif "source" in sub and sub["source"] in dfs:
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sub_ds_key = "source"
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if sub_ds_key:
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sub["df"] = dfs[sub.pop(sub_ds_key)]
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resolved[key] = sub
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# Step 3: 注入 defaults（全部仍为 dict，安全合并）
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if default_layout_config:
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self._inject_default_layout_config(resolved, default_layout_config)
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# Step 4: 统一转对象（顶层 + 嵌套）
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self._resolve_config_objects(resolved)
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for key in ("left", "right", "top", "bottom"):
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if key in resolved and isinstance(resolved[key], dict):
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self._resolve_config_objects(resolved[key])
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return resolved
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def _inject_default_layout_config(self, data: dict, defaults: dict) -> None:
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"""将 Job 级 default_layout_config 合并到页面数据中（页面级优先覆盖）"""
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def _merge_lc(target):
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if "layout_config" not in target and "df" not in target:
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return # 非图表数据，跳过
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if "layout_config" in target:
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merged = dict(defaults)
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merged.update(target["layout_config"]) # 页面级覆盖
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target["layout_config"] = merged
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elif "df" in target:
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target["layout_config"] = dict(defaults)
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_merge_lc(data)
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for key in ("left", "right", "top", "bottom"):
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if key in data and isinstance(data[key], dict):
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_merge_lc(data[key])
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def _resolve_config_objects(self, data: dict) -> None:
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"""将 dict 形式的 style_config / layout_config 转为对象"""
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from ppt_station.chart_builder.styles import StyleConfig
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from ppt_station.chart_builder.layout import (
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ChartLayoutConfig, LegendConfig, ValueAxisConfig, CategoryAxisConfig,
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)
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if "style_config" in data and isinstance(data["style_config"], dict):
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data["style_config"] = StyleConfig(**data["style_config"])
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if "layout_config" in data and isinstance(data["layout_config"], dict):
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data["layout_config"] = self._build_layout_config(data["layout_config"])
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def _build_layout_config(self, cfg: dict):
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"""将嵌套 dict 转为 ChartLayoutConfig，处理子对象实例化"""
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from ppt_station.chart_builder.layout import (
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ChartLayoutConfig, LegendConfig, ValueAxisConfig, CategoryAxisConfig,
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)
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kwargs = dict(cfg)
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if "legend_config" in kwargs and isinstance(kwargs["legend_config"], dict):
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kwargs["legend_config"] = LegendConfig(**kwargs["legend_config"])
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if "category_axis_config" in kwargs and isinstance(kwargs["category_axis_config"], dict):
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kwargs["category_axis_config"] = CategoryAxisConfig(**kwargs["category_axis_config"])
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if "value_axis_config" in kwargs and isinstance(kwargs["value_axis_config"], dict):
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kwargs["value_axis_config"] = ValueAxisConfig(**kwargs["value_axis_config"])
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if "secondary_value_axis_config" in kwargs and isinstance(kwargs["secondary_value_axis_config"], dict):
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kwargs["secondary_value_axis_config"] = ValueAxisConfig(**kwargs["secondary_value_axis_config"])
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# date_axis_config 用预设名解析
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if "date_axis_config" in kwargs and isinstance(kwargs["date_axis_config"], str):
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from ppt_station.chart_builder.date_axis import (
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DAILY_TICKS, WEEKLY_TICKS, BIWEEKLY_TICKS,
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MONTHLY_TICKS, QUARTERLY_TICKS, YEARLY_TICKS,
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)
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presets = {
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"daily": DAILY_TICKS, "weekly": WEEKLY_TICKS,
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"biweekly": BIWEEKLY_TICKS, "monthly": MONTHLY_TICKS,
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"quarterly": QUARTERLY_TICKS, "yearly": YEARLY_TICKS,
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}
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preset_name = kwargs["date_axis_config"].lower()
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if preset_name in presets:
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kwargs["date_axis_config"] = presets[preset_name]
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else:
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raise ValueError(f"未知日期轴预设: {preset_name}。可用: {list(presets.keys())}")
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return ChartLayoutConfig(**kwargs)
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# ------------------------------------------------------------------
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# 共用工具
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# ------------------------------------------------------------------
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def _add_metadata(self, prs: Presentation, job: Job) -> None:
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"""添加生成信息到 PPT 元数据"""
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core_props = prs.core_properties
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core_props.modified = datetime.now()
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metadata_lines = [
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"生成信息:",
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f"生成时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
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]
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if job.mode == "template" and job.template:
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metadata_lines.append(f"模板: {job.template.path}")
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elif job.mode == "composer":
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metadata_lines.append(f"模式: composer, 主题: {job.theme or 'jp_finance'}")
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if job.params:
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metadata_lines.append(f"参数: {json.dumps(job.params, ensure_ascii=False)}")
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config_str = json.dumps(job.model_dump(), ensure_ascii=False, sort_keys=True, default=str)
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config_hash = hashlib.sha256(config_str.encode()).hexdigest()[:16]
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metadata_lines.append(f"配置哈希: {config_hash}")
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core_props.comments = "\n".join(metadata_lines)
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