Add skills-lock.json to manage skill dependencies for drawio-skill and prd
This commit is contained in:
Guangfei.Zhao
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# pyright: reportMissingImports=false
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from __future__ import annotations
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from pathlib import Path
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import re
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from openpyxl import load_workbook
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ROOT = Path(__file__).resolve().parent
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SOURCE_FILE = ROOT.parent / "202606 Conti Retail APP Component data source.xlsx"
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OUTPUT_FILE = ROOT / f"{SOURCE_FILE.stem}.md"
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FIELDS = [
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("编号", 2),
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("模块", 3),
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("功能", 4),
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("负责人", 5),
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("前置任务", 6),
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("数据集", 7),
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("来源", 8),
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("安全", 9),
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("备注", 10),
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]
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def normalize_cell(value: object) -> str:
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if value is None:
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return ""
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if isinstance(value, float) and value.is_integer():
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value = int(value)
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text = str(value).replace("\r\n", "\n").replace("\r", "\n")
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lines = [re.sub(r"\s+", " ", line).strip() for line in text.split("\n")]
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return "\n".join(line for line in lines if line)
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def add_field(parts: list[str], name: str, value: str) -> None:
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if not value:
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return
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parts.append(f"**{name}**")
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parts.append("")
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lines = [line.strip() for line in value.splitlines() if line.strip()]
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if len(lines) > 1:
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parts.extend(f"- {line}" for line in lines)
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else:
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parts.extend(lines)
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parts.append("")
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def extract_workbook_to_md() -> None:
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workbook = load_workbook(SOURCE_FILE, data_only=True)
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parts: list[str] = [f"# {SOURCE_FILE.stem}", ""]
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for worksheet in workbook.worksheets:
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rows: list[dict[str, str]] = []
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for row_index in range(2, worksheet.max_row + 1):
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row = {
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field: normalize_cell(worksheet.cell(row=row_index, column=column).value)
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for field, column in FIELDS
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}
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if not any(row.values()):
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continue
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if not any(row[key] for key in ("编号", "模块", "功能")):
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continue
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rows.append(row)
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if not rows:
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continue
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parts.append(f"## {worksheet.title}")
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parts.append("")
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for row in rows:
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number = row["编号"]
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module = row["模块"]
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title = " ".join(part for part in (number, module) if part).strip()
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level = min(6, 3 + number.count(".")) if number else 3
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parts.append(f"{'#' * level} {title or 'Untitled'}")
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parts.append("")
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add_field(parts, "功能", row["功能"])
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add_field(parts, "负责人", row["负责人"])
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add_field(parts, "前置任务", row["前置任务"])
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add_field(parts, "数据集", row["数据集"])
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add_field(parts, "来源", row["来源"])
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add_field(parts, "安全", row["安全"])
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add_field(parts, "备注", row["备注"])
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OUTPUT_FILE.write_text("\n".join(parts).strip() + "\n", encoding="utf-8")
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print("Wrote workbook markdown output")
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if __name__ == "__main__":
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extract_workbook_to_md()
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@@ -1,128 +0,0 @@
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# pyright: reportMissingImports=false
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from __future__ import annotations
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from pathlib import Path
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import re
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import fitz
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import numpy as np
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from pptx import Presentation
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from pptx.enum.shapes import MSO_SHAPE_TYPE
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from rapidocr_onnxruntime import RapidOCR
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ROOT = Path(__file__).resolve().parent
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SOURCE_DIR = ROOT.parent
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PDF_PATH = SOURCE_DIR / "User Journeys.pdf"
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PPTX_PATH = SOURCE_DIR / "零售商系统方案研讨会PPT.retro.pptx"
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PDF_OUTPUT = ROOT / "User Journeys.md"
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PPTX_OUTPUT = ROOT / "零售商系统方案研讨会PPT.retro.md"
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OCR = RapidOCR()
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def normalize_text(text: str) -> str:
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text = text.replace("\r\n", "\n").replace("\r", "\n")
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lines = [re.sub(r"\s+", " ", line).strip() for line in text.split("\n")]
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return "\n".join(line for line in lines if line)
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def extract_page_ocr_text(page: fitz.Page) -> str:
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pix = page.get_pixmap(matrix=fitz.Matrix(4, 4), alpha=False)
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image = np.frombuffer(pix.samples, dtype=np.uint8).reshape(pix.height, pix.width, pix.n)
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result, _ = OCR(image)
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if not result:
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return ""
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return normalize_text("\n".join(str(item[1]) for item in result))
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def extract_pdf_to_md(pdf_path: Path, output_path: Path) -> None:
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doc = fitz.open(pdf_path)
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parts: list[str] = [f"# {pdf_path.stem}", ""]
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try:
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for index in range(doc.page_count):
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page = doc.load_page(index)
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text = normalize_text(str(page.get_text("text") or ""))
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if not text:
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text = extract_page_ocr_text(page)
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parts.append(f"## Page {index + 1}")
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parts.append("")
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parts.append(text or "[No extractable text]")
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parts.append("")
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finally:
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doc.close()
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output_path.write_text("\n".join(parts).strip() + "\n", encoding="utf-8")
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def iter_shape_text(shape) -> list[str]:
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chunks: list[str] = []
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if hasattr(shape, "has_text_frame") and shape.has_text_frame:
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text = normalize_text(shape.text_frame.text)
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if text:
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chunks.append(text)
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if hasattr(shape, "has_table") and shape.has_table:
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for row in shape.table.rows:
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cells = [normalize_text(cell.text) for cell in row.cells]
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cells = [cell for cell in cells if cell]
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if cells:
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chunks.append(" | ".join(cells))
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if shape.shape_type == MSO_SHAPE_TYPE.GROUP:
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for subshape in shape.shapes:
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chunks.extend(iter_shape_text(subshape))
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return chunks
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def extract_pptx_to_md(pptx_path: Path, output_path: Path) -> None:
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prs = Presentation(str(pptx_path))
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parts: list[str] = [f"# {pptx_path.stem}", ""]
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for index, slide in enumerate(prs.slides, start=1):
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title = ""
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parts.append(f"## Slide {index}")
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parts.append("")
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if slide.shapes.title and slide.shapes.title.text:
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title = normalize_text(slide.shapes.title.text)
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if title:
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parts.append(f"### {title}")
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parts.append("")
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seen: set[str] = set()
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collected = []
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for shape in slide.shapes:
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for chunk in iter_shape_text(shape):
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if title and chunk == title:
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continue
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if chunk and chunk not in seen:
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seen.add(chunk)
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collected.append(chunk)
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if collected:
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parts.extend(f"- {chunk}" for chunk in collected)
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else:
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parts.append("[No extractable text]")
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parts.append("")
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output_path.write_text("\n".join(parts).strip() + "\n", encoding="utf-8")
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def main() -> None:
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extract_pdf_to_md(PDF_PATH, PDF_OUTPUT)
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extract_pptx_to_md(PPTX_PATH, PPTX_OUTPUT)
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print("Wrote PDF markdown output")
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print("Wrote PPTX markdown output")
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if __name__ == "__main__":
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main()
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