feat: sync full workspace including web modules, docs, and configurations to Gitea
Optimized the root .gitignore to exclude virtual environments, node modules, and temp folders to ensure clean and lightweight version tracking. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
王冕
586
scripts/sync_repair_ledger_dedupe.py
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586
scripts/sync_repair_ledger_dedupe.py
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@@ -0,0 +1,586 @@
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""One-off: merge repair Excel sources into 羚牛公司车辆运维成本台账.xlsx and dedupe."""
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from __future__ import annotations
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import os
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import re
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from dataclasses import dataclass
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from datetime import datetime
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from pathlib import Path
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from typing import Iterable, Iterator, List, Optional, Tuple
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import pandas as pd
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from openpyxl import load_workbook
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LEDGER = Path("/Users/sylvawong/Desktop/羚牛公司车辆运维成本台账.xlsx")
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ROOTS = [
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/2026年2月常州维修明细"),
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/2026年2月金华维修费"),
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/2026年3-4月金华(中顺维修费）"),
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/2026年3月常州维修费"),
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/2026年3月开封维修费"),
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/2026年4月河南开封维修费"),
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/上海昱巷2026年1月维修费"),
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/上海昱巷2026年2月维修费"),
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Path("/Users/sylvawong/Desktop/26年维修费/沈帅/上海昱巷2026年3月维修费"),
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]
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@dataclass(frozen=True)
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class Row:
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y: int
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m: int
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d: int
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plate: str
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fee: float
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remark: str
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source: str = ""
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def key(self) -> Tuple:
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fee = round(float(self.fee), 2)
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rmk = re.sub(r"\s+", "", self.remark or "")
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return (self.y, self.m, self.d, self.plate, fee, rmk)
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def iter_xlsx_files(roots: Iterable[Path]) -> Iterator[Path]:
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for root in roots:
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if not root.is_dir():
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continue
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for dirpath, _, filenames in os.walk(root):
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for fn in filenames:
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if fn.startswith("~$"):
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continue
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low = fn.lower()
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if low.endswith(".xlsx") or low.endswith(".xls"):
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yield Path(dirpath) / fn
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def parse_cn_date_yy(s: object) -> Optional[Tuple[int, int, int]]:
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if s is None or (isinstance(s, float) and pd.isna(s)):
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return None
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t = re.sub(r"\s+", "", str(s).strip())
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m = re.match(r"^(\d{2})年(\d{1,2})月(\d{1,2})日", t)
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if not m:
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return None
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y, mo, d = int(m.group(1)), int(m.group(2)), int(m.group(3))
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if y < 100:
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y += 2000
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return y, mo, d
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def parse_cn_date_yyyy(s: object) -> Optional[Tuple[int, int, int]]:
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if s is None or (isinstance(s, float) and pd.isna(s)):
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return None
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t = str(s).strip()
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m = re.match(r"^(\d{4})\s*年\s*(\d{1,2})\s*月\s*(\d{1,2})\s*日", t)
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if not m:
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return None
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return int(m.group(1)), int(m.group(2)), int(m.group(3))
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def parse_any_date_cell(s: object) -> Optional[Tuple[int, int, int]]:
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if s is None or (isinstance(s, float) and pd.isna(s)):
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return None
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if isinstance(s, datetime):
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return s.year, s.month, s.day
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t = pd.to_datetime(s, errors="coerce")
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if pd.notna(t):
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tt = t.to_pydatetime()
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return tt.year, tt.month, tt.day
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x = parse_cn_date_yyyy(s)
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if x:
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return x
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return parse_cn_date_yy(s)
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def month_from_parent_dir(path: Path) -> Optional[Tuple[int, int]]:
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"""Parse (year, month) from folder name like '2026年4月河南开封维修费'."""
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m = re.search(r"(\d{4})年(\d{1,2})月", path.parent.name)
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if m:
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return int(m.group(1)), int(m.group(2))
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return None
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def parse_standard_feedback_df(df: pd.DataFrame) -> Optional[Tuple[int, int, int, str, float, str]]:
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if df.shape[0] < 3:
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return None
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ymd = parse_cn_date_yy(df.iloc[1, 0])
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if ymd is None or ymd[0] is None:
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ymd = parse_cn_date_yyyy(df.iloc[1, 0])
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if ymd is None:
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return None
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y, mo, d = ymd
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plate = None
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info_fallback = ""
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for i in range(min(30, df.shape[0])):
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v = df.iloc[i, 0]
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if pd.isna(v):
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continue
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s = str(v)
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if "车牌号：" in s or "车牌号:" in s:
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m = re.search(r"车牌号[：:]\s*([^\s]+)", s)
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if m:
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plate = m.group(1).strip()
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if "车辆维修信息：" in s or "车辆维修信息:" in s:
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info_fallback = re.split(r"车辆维修信息[：:]", s, maxsplit=1)[-1].strip()
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header_idx = None
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for i in range(df.shape[0]):
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c0 = df.iloc[i, 0]
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c1 = df.iloc[i, 1] if df.shape[1] > 1 else None
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if pd.isna(c0):
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continue
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if str(c0).strip() == "序号" and pd.notna(c1) and "维修项目" in str(c1):
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header_idx = i
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break
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projects: List[str] = []
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total_fee: Optional[float] = None
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if header_idx is not None:
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for j in range(header_idx + 1, df.shape[0]):
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c0 = df.iloc[j, 0]
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s0 = "" if pd.isna(c0) else str(c0)
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if "费用总计" in s0 or "费用共计" in s0:
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m = re.search(r"(?:费用总计|费用共计)[：:]\s*([\d.]+)", s0)
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if m:
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total_fee = float(m.group(1))
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break
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try:
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float(c0)
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int(float(c0))
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except (TypeError, ValueError):
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continue
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proj = df.iloc[j, 1] if df.shape[1] > 1 else None
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if pd.notna(proj):
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p = str(proj).strip()
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if p:
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projects.append(p)
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remark = "；".join(projects) if projects else info_fallback
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if plate is None or total_fee is None:
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return None
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return y, mo, d, plate, float(total_fee), remark
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def parse_yuyu_feedback_df(df: pd.DataFrame) -> Optional[Tuple[int, int, int, str, float, str]]:
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"""上海昱巷「故障车辆维修信息反馈单」."""
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if df.shape[0] < 3:
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return None
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ymd = parse_cn_date_yyyy(df.iloc[1, 0])
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if ymd is None:
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ymd = parse_any_date_cell(df.iloc[1, 0])
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if ymd is None or ymd[1] == 0 or ymd[2] == 0:
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return None
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y, mo, d = ymd
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plate = None
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symptom = ""
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for i in range(min(25, df.shape[0])):
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v = df.iloc[i, 0]
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if pd.isna(v):
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continue
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s = str(v)
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if "车牌号：" in s or "车牌号:" in s:
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m = re.search(r"车牌号[：:]\s*([^\s]+)", s)
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if m:
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p = m.group(1).strip()
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if p:
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plate = p
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if "故障现象：" in s or "故障现象:" in s:
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symptom = re.split(r"故障现象[：:]", s, maxsplit=1)[-1].strip()
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header_idx = None
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for i in range(df.shape[0]):
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c0 = df.iloc[i, 0]
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c1 = df.iloc[i, 1] if df.shape[1] > 1 else None
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if pd.isna(c0):
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continue
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if str(c0).strip() == "序号" and pd.notna(c1) and "维修项目" in str(c1):
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header_idx = i
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break
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projects: List[str] = []
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total_fee: Optional[float] = None
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if header_idx is not None:
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for j in range(header_idx + 1, df.shape[0]):
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c0 = df.iloc[j, 0]
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c1 = df.iloc[j, 1] if df.shape[1] > 1 else None
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s0 = "" if pd.isna(c0) else str(c0)
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s1 = "" if pd.isna(c1) else str(c1)
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if "费用共计" in s0 or "费用共计" in s1:
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cell = s1 if "费用共计" in s1 else s0
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m = re.search(r"费用共计[：:]\s*([\d.]+)", cell)
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if m:
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total_fee = float(m.group(1))
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break
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try:
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float(c0)
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int(float(c0))
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except (TypeError, ValueError):
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continue
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if pd.notna(c1):
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p = str(c1).strip()
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if p:
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projects.append(p)
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remark = "；".join(projects) if projects else symptom
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if plate is None or total_fee is None:
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return None
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return y, mo, d, plate, float(total_fee), remark
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def parse_mingrui_chaidui(path: Path, df: pd.DataFrame) -> List[Row]:
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out: List[Row] = []
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if df.shape[0] < 3:
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return out
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hdr_row = 1 if str(df.iloc[1, 0]).strip() == "序号" else None
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if hdr_row is None:
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return out
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sub = pd.read_excel(path, sheet_name=0, header=hdr_row)
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cols = {str(c).strip(): c for c in sub.columns}
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need = ["车牌号", "时间", "维修项目", "价格"]
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if not all(k in cols for k in need):
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return out
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for _, r in sub.iterrows():
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plate = r.get("车牌号")
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if pd.isna(plate) or str(plate).strip() == "":
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continue
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proj = r.get("维修项目")
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if pd.notna(proj) and "合计" in str(proj):
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continue
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ymd = parse_cn_date_yy(r.get("时间"))
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if ymd is None:
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continue
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y, mo, d = ymd
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fee = r.get("价格")
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try:
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fee_f = float(fee) if pd.notna(fee) else 0.0
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except (TypeError, ValueError):
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fee_f = 0.0
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remark = "" if pd.isna(proj) else str(proj).strip()
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out.append(Row(y, mo, d, str(plate).strip(), fee_f, remark, path.name))
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return out
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def parse_jinhua_chaidui(path: Path, df: pd.DataFrame) -> List[Row]:
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out: List[Row] = []
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if df.shape[0] < 3:
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return out
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hdr = None
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for i in range(min(5, df.shape[0])):
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if str(df.iloc[i, 0]).strip() == "车牌号":
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hdr = i
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break
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if hdr is None:
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return out
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sub = pd.read_excel(path, sheet_name=0, header=hdr)
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time_col = "时间" if "时间" in sub.columns else None
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proj_col = None
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for c in sub.columns:
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cs = str(c).strip()
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if cs in ("项目", "维修项目"):
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proj_col = c
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break
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price_col = None
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for c in sub.columns:
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if str(c).strip().startswith("价格"):
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price_col = c
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break
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if time_col is None or proj_col is None or price_col is None:
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return out
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for _, r in sub.iterrows():
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plate = r.get("车牌号")
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if pd.isna(plate) or str(plate).strip() == "":
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continue
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ymd = parse_cn_date_yy(r.get(time_col))
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if ymd is None:
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continue
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y, mo, d = ymd
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proj = r.get(proj_col)
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if pd.notna(proj) and "合计" in str(proj):
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continue
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try:
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fee_f = float(r.get(price_col)) if pd.notna(r.get(price_col)) else 0.0
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except (TypeError, ValueError):
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fee_f = 0.0
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remark = "" if pd.isna(proj) else str(proj).strip()
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out.append(Row(y, mo, d, str(plate).strip(), fee_f, remark, path.name))
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return out
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def parse_kaifeng_chaidui(path: Path, df: pd.DataFrame) -> List[Row]:
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out: List[Row] = []
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mm = month_from_parent_dir(path)
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if mm is None:
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return out
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y0, m0 = mm
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hdr = None
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for i in range(min(6, df.shape[0])):
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c0 = str(df.iloc[i, 0]).strip() if pd.notna(df.iloc[i, 0]) else ""
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if c0 == "序号":
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hdr = i
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break
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if hdr is None:
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return out
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sub = pd.read_excel(path, sheet_name=0, header=hdr)
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for _, r in sub.iterrows():
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try:
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idx = r.iloc[0]
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if pd.isna(idx):
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continue
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float(idx)
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except (TypeError, ValueError):
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continue
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plate = r.get("车牌") if "车牌" in sub.columns else r.get(sub.columns[1])
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if plate is None or (isinstance(plate, float) and pd.isna(plate)):
|
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continue
|
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fee_col = None
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for c in sub.columns:
|
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if str(c).strip() == "价格":
|
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fee_col = c
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||||
break
|
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if fee_col is None:
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||||
continue
|
||||
try:
|
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fee_f = float(r.get(fee_col)) if pd.notna(r.get(fee_col)) else 0.0
|
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except (TypeError, ValueError):
|
||||
continue
|
||||
if "合计" in str(plate):
|
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continue
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out.append(Row(y0, m0, 1, str(plate).strip(), fee_f, "开封拆堆", path.name))
|
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return out
|
||||
|
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|
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def find_col(df: pd.DataFrame, names: Tuple[str, ...]) -> Optional[str]:
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for c in df.columns:
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cs = str(c).strip()
|
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if cs in names:
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return c # type: ignore[return-value]
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return None
|
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|
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def parse_system_table_df(df: pd.DataFrame, source: str) -> List[Row]:
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out: List[Row] = []
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if df.shape[0] < 1:
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return out
|
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plate_c = find_col(df, ("车牌号", "车牌号码"))
|
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if plate_c is None:
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return out
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date_c = find_col(df, ("故障上报时间",))
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sol_c = find_col(df, ("解决方案",))
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part_c = find_col(df, ("配件价格", "配件", "配件费用", "配件费"))
|
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labor_c = find_col(df, ("工时", "人工", "工时费"))
|
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|
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for _, r in df.iterrows():
|
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plate = r.get(plate_c)
|
||||
if plate is None or (isinstance(plate, float) and pd.isna(plate)):
|
||||
continue
|
||||
plate_s = str(plate).strip()
|
||||
if plate_s == "" or plate_s == "NaN":
|
||||
continue
|
||||
sol = r.get(sol_c) if sol_c else None
|
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if sol is not None and "合计" in str(sol):
|
||||
continue
|
||||
|
||||
ymd = parse_any_date_cell(r.get(date_c)) if date_c else None
|
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if ymd is None:
|
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continue
|
||||
|
||||
fee = 0.0
|
||||
if part_c:
|
||||
fee += float(r.get(part_c) or 0) if pd.notna(r.get(part_c)) else 0.0
|
||||
if labor_c:
|
||||
v = r.get(labor_c)
|
||||
if pd.notna(v):
|
||||
try:
|
||||
fee += float(v)
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||||
except (TypeError, ValueError):
|
||||
pass
|
||||
|
||||
# skip summary rows where part column shows 合计
|
||||
if part_c:
|
||||
pv = r.get(part_c)
|
||||
if pd.notna(pv) and "合计" in str(pv):
|
||||
continue
|
||||
|
||||
remark = "" if sol is None or pd.isna(sol) else str(sol).strip()
|
||||
y, mo, d = ymd
|
||||
out.append(Row(y, mo, d, plate_s, float(fee), remark, source))
|
||||
return out
|
||||
|
||||
|
||||
def parse_system_workbook(path: Path) -> List[Row]:
|
||||
out: List[Row] = []
|
||||
xl = pd.ExcelFile(path)
|
||||
for sn in xl.sheet_names:
|
||||
try:
|
||||
df = pd.read_excel(path, sheet_name=sn, header=0)
|
||||
except Exception:
|
||||
continue
|
||||
if df.shape[0] == 0:
|
||||
continue
|
||||
c0 = str(df.columns[0]).strip() if df.columns[0] is not None else ""
|
||||
if c0 not in ("车牌号", "车辆编号"):
|
||||
continue
|
||||
out.extend(parse_system_table_df(df, f"{path.name}:{sn}"))
|
||||
return out
|
||||
|
||||
|
||||
def classify_and_parse(path: Path) -> List[Row]:
|
||||
rows: List[Row] = []
|
||||
try:
|
||||
df0 = pd.read_excel(path, sheet_name=0, header=None)
|
||||
except Exception:
|
||||
return rows
|
||||
if df0.shape[0] == 0:
|
||||
return rows
|
||||
c00 = str(df0.iloc[0, 0]) if pd.notna(df0.iloc[0, 0]) else ""
|
||||
|
||||
# 河南开封拆堆（无日期列）
|
||||
if "开封拆堆" in c00 or ("拆堆明细" in c00 and "开封" in c00):
|
||||
rows.extend(parse_kaifeng_chaidui(path, df0))
|
||||
return rows
|
||||
|
||||
# 铭瑞类拆堆
|
||||
if "铭瑞" in c00 or (df0.shape[0] > 2 and str(df0.iloc[1, 0]).strip() == "序号" and "维修项目" in str(df0.iloc[1, 4])):
|
||||
mr = parse_mingrui_chaidui(path, df0)
|
||||
if mr:
|
||||
return mr
|
||||
|
||||
# 金华拆堆
|
||||
if "金华维修明细" in c00:
|
||||
jh = parse_jinhua_chaidui(path, df0)
|
||||
if jh:
|
||||
return jh
|
||||
|
||||
# 昱巷：故障车辆维修信息反馈单（多 sheet）
|
||||
if "故障车辆维修信息反馈单" in c00:
|
||||
xl = pd.ExcelFile(path)
|
||||
for sn in xl.sheet_names:
|
||||
df = pd.read_excel(path, sheet_name=sn, header=None)
|
||||
rec = parse_yuyu_feedback_df(df)
|
||||
if rec:
|
||||
y, mo, d, plate, fee, remark = rec
|
||||
rows.append(Row(y, mo, d, plate, fee, remark, f"{path.name}:{sn}"))
|
||||
return rows
|
||||
|
||||
# 常州/开封 车辆维修信息反馈单
|
||||
if "车辆维修信息反馈单" in c00:
|
||||
xl = pd.ExcelFile(path)
|
||||
for sn in xl.sheet_names:
|
||||
df = pd.read_excel(path, sheet_name=sn, header=None)
|
||||
rec = parse_standard_feedback_df(df)
|
||||
if rec:
|
||||
y, mo, d, plate, fee, remark = rec
|
||||
rows.append(Row(y, mo, d, plate, fee, remark, f"{path.name}:{sn}"))
|
||||
return rows
|
||||
|
||||
# 系统故障 / 系统维修 / 昱巷系统明细
|
||||
c0h = str(df0.iloc[0, 0]).strip() if pd.notna(df0.iloc[0, 0]) else ""
|
||||
if c0h == "车牌号" or c0h == "车辆编号":
|
||||
rows.extend(parse_system_workbook(path))
|
||||
return rows
|
||||
|
||||
# 兜底：按系统表再试（部分文件首行是合并格）
|
||||
alt = parse_system_workbook(path)
|
||||
if alt:
|
||||
return alt
|
||||
|
||||
return rows
|
||||
|
||||
|
||||
def read_existing_ledger(path: Path) -> Tuple[int, List[Row]]:
|
||||
wb = load_workbook(path)
|
||||
ws = wb.active
|
||||
header_row = None
|
||||
for i, row in enumerate(ws.iter_rows(min_row=1, max_row=40, values_only=True), start=1):
|
||||
if row and any(c == "年份" for c in row if c is not None):
|
||||
header_row = i
|
||||
break
|
||||
if header_row is None:
|
||||
raise SystemExit("ledger: 年份 header not found")
|
||||
col_map: dict = {}
|
||||
for cell in ws[header_row]:
|
||||
if cell.value:
|
||||
col_map[str(cell.value).strip()] = cell.column
|
||||
out: List[Row] = []
|
||||
for r in range(header_row + 1, ws.max_row + 1):
|
||||
plate = ws.cell(row=r, column=col_map["车牌号"]).value
|
||||
if plate is None or str(plate).strip() == "":
|
||||
continue
|
||||
y = ws.cell(row=r, column=col_map["年份"]).value
|
||||
mo = ws.cell(row=r, column=col_map["月份"]).value
|
||||
d = ws.cell(row=r, column=col_map["日期"]).value
|
||||
fee = ws.cell(row=r, column=col_map["修理费"]).value
|
||||
remark = ws.cell(row=r, column=col_map["备注"]).value
|
||||
try:
|
||||
yy, mm, dd = int(y), int(mo), int(d)
|
||||
ff = float(fee) if fee is not None else 0.0
|
||||
except (TypeError, ValueError):
|
||||
continue
|
||||
rmk = "" if remark is None else str(remark)
|
||||
out.append(Row(yy, mm, dd, str(plate).strip(), ff, rmk, "ledger:existing"))
|
||||
return header_row, out
|
||||
|
||||
|
||||
def write_ledger(path: Path, header_row: int, rows: List[Row]) -> None:
|
||||
wb = load_workbook(path)
|
||||
ws = wb.active
|
||||
col_map: dict = {}
|
||||
for cell in ws[header_row]:
|
||||
if cell.value:
|
||||
col_map[str(cell.value).strip()] = cell.column
|
||||
|
||||
if ws.max_row > header_row:
|
||||
ws.delete_rows(header_row + 1, ws.max_row - header_row)
|
||||
|
||||
r = header_row + 1
|
||||
for row in rows:
|
||||
ws.cell(row=r, column=col_map["年份"], value=row.y)
|
||||
ws.cell(row=r, column=col_map["月份"], value=row.m)
|
||||
ws.cell(row=r, column=col_map["日期"], value=row.d)
|
||||
ws.cell(row=r, column=col_map["车牌号"], value=row.plate)
|
||||
ws.cell(row=r, column=col_map["修理费"], value=row.fee)
|
||||
for k in ("保养费", "年审费", "轮胎费", "其他"):
|
||||
if k in col_map:
|
||||
ws.cell(row=r, column=col_map[k], value=None)
|
||||
ws.cell(row=r, column=col_map["小计"], value=row.fee)
|
||||
if "费用是否为公司承担" in col_map:
|
||||
ws.cell(row=r, column=col_map["费用是否为公司承担"], value=None)
|
||||
ws.cell(row=r, column=col_map["备注"], value=row.remark or None)
|
||||
r += 1
|
||||
wb.save(path)
|
||||
|
||||
|
||||
def main() -> None:
|
||||
files = sorted({p.resolve() for p in iter_xlsx_files(ROOTS)})
|
||||
imported: List[Row] = []
|
||||
for p in files:
|
||||
imported.extend(classify_and_parse(p))
|
||||
|
||||
header_row, existing = read_existing_ledger(LEDGER)
|
||||
merged = existing + imported
|
||||
before = len(merged)
|
||||
|
||||
seen = set()
|
||||
deduped: List[Row] = []
|
||||
for row in merged:
|
||||
k = row.key()
|
||||
if k in seen:
|
||||
continue
|
||||
seen.add(k)
|
||||
deduped.append(row)
|
||||
|
||||
deduped.sort(key=lambda x: (x.y, x.m, x.d, x.plate, x.remark))
|
||||
|
||||
write_ledger(LEDGER, header_row, deduped)
|
||||
print("files scanned:", len(files))
|
||||
print("rows imported from files:", len(imported))
|
||||
print("existing ledger rows:", len(existing))
|
||||
print("merged before dedupe:", before)
|
||||
print("after dedupe:", len(deduped))
|
||||
print("removed duplicates:", before - len(deduped))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Reference in New Issue
Block a user