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feat: sync full workspace including web modules, docs, and configurations to Gitea

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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>
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王冕
2026-06-09 18:12:25 +08:00
parent 351688006e
commit a27e3b8e43
1510 changed files with 162044 additions and 1517 deletions
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scripts/compare_h2_records.py Normal file
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#!/usr/bin/env python3
"""比对「加氢记录」与「氢费台账-加氢订单」，输出标黄/标红 Excel。"""
from __future__ import annotations
import re
from collections import defaultdict
from pathlib import Path
import pandas as pd
from openpyxl import load_workbook
from openpyxl.styles import Font, PatternFill
FILE_RECORD = Path(
"/Users/sylvawong/Library/Containers/com.tencent.xinWeChat/Data/Documents/"
"xwechat_files/wxid_l80gh7d3x7u012_385c/msg/file/2026-05/"
"加氢记录-（2026.1月-4月）.xlsx"
)
FILE_LEDGER = Path(
"/Users/sylvawong/Library/Containers/com.tencent.xinWeChat/Data/Documents/"
"xwechat_files/wxid_l80gh7d3x7u012_385c/msg/file/2026-05/"
"氢费台账总表2026.5.21(1).xlsx"
)
OUT_DIR = Path("/Users/sylvawong/Desktop/CURSOR/ONE-OS")
OUT_FILE = OUT_DIR / "加氢记录与台账比对结果.xlsx"
COMPARE_FIELDS = [
("加氢站", "加氢站名称", "加氢站"),
("成本单价", "成本单价(元/kg)", "成本单价"),
("成本金额", "成本费用(元)", "成本金额"),
("加氢单价", "加氢单价(元/kg)", "加氢单价"),
("加氢金额", "加氢金额（元）", "加氢金额"),
("客户名", "客户名称", "客户名"),
("氢费计算方式", "结算类别", "氢费计算方式"),
]
YELLOW = PatternFill(start_color="FFFF00", end_color="FFFF00", fill_type="solid")
RED = PatternFill(start_color="FF9999", end_color="FF9999", fill_type="solid")
RED_FONT = Font(color="9C0006", bold=True)
def read_record_sheet(path: Path) -> pd.DataFrame:
raw = pd.read_excel(path, sheet_name=0, header=None)
# 第 0 行为汇总行，第 1 行为表头
raw.columns = [
str(c).strip() if pd.notna(c) else f"_col{i}" for i, c in enumerate(raw.iloc[1])
]
df = raw.iloc[2:].copy().reset_index(drop=True)
rename = {
"序号": "序号",
"日期": "日期",
"车牌": "车牌",
"加气量（kg)": "加气量（kg)",
"加气量（kg）": "加气量（kg)",
"加氢站": "加氢站",
"成本单价": "成本单价",
"成本金额": "成本金额",
"加氢单价": "加氢单价",
"加氢金额": "加氢金额",
"客户名": "客户名",
"氢费计算方式": "氢费计算方式",
}
for old, new in rename.items():
if old in df.columns:
df = df.rename(columns={old: new})
return df
def parse_date(val) -> str:
if pd.isna(val):
return ""
if isinstance(val, pd.Timestamp):
return val.strftime("%Y-%m-%d")
if isinstance(val, (int, float)) and val > 40000:
try:
return (pd.Timestamp("1899-12-30") + pd.Timedelta(days=int(val))).strftime("%Y-%m-%d")
except Exception:
pass
s = str(val).strip()
for fmt in ("%Y-%m-%d", "%Y/%m/%d", "%Y-%m-%d %H:%M:%S"):
try:
return pd.to_datetime(s).strftime("%Y-%m-%d")
except Exception:
continue
try:
return pd.to_datetime(val).strftime("%Y-%m-%d")
except Exception:
return s[:10] if len(s) >= 10 else s
def norm_plate(val) -> str:
if pd.isna(val):
return ""
return re.sub(r"[\s\-·]", "", str(val).strip().upper())
def norm_kg(val, tol_decimals=3) -> str:
if pd.isna(val) or str(val).strip() in ("", "-", "nan"):
return ""
try:
return f"{round(float(val), tol_decimals):.{tol_decimals}f}"
except Exception:
return str(val).strip()
def norm_str(val) -> str:
if pd.isna(val):
return ""
return str(val).strip()
def norm_num(val, tol=0.02) -> float | None:
if pd.isna(val) or str(val).strip() in ("", "-", "nan"):
return None
try:
return float(val)
except Exception:
return None
def values_equal(a, b, numeric: bool) -> bool:
if numeric:
na, nb = norm_num(a), norm_num(b)
if na is None and nb is None:
return True
if na is None or nb is None:
return False
return abs(na - nb) <= 0.02
return norm_str(a) == norm_str(b)
def make_key(row, date_col, plate_col, kg_col) -> str:
return f"{parse_date(row[date_col])}|{norm_plate(row[plate_col])}|{norm_kg(row[kg_col])}"
def build_index(df, date_col, plate_col, kg_col):
"""同一 key 可能多行，用列表保存行号。"""
idx: dict[str, list[int]] = defaultdict(list)
for i, row in df.iterrows():
k = make_key(row, date_col, plate_col, kg_col)
parts = k.split("|")
if parts[0] and parts[1] and parts[2]:
idx[k].append(i)
return idx
def pair_rows(keys_a: list[int], keys_b: list[int]):
"""按顺序一对一配对，多余行不配。"""
n = min(len(keys_a), len(keys_b))
return list(zip(keys_a[:n], keys_b[:n]))
def compare_pair(row_a: pd.Series, row_b: pd.Series) -> tuple[list[str], list[str]]:
"""返回 (差异字段名列表, 备注片段列表)。"""
diffs = []
notes = []
for col_a, col_b, label in COMPARE_FIELDS:
numeric = label in ("成本单价", "成本金额", "加氢单价", "加氢金额")
va = row_a.get(col_a)
vb = row_b.get(col_b)
if not values_equal(va, vb, numeric):
diffs.append(label)
notes.append(f"{label}:记录[{norm_str(va)}]≠台账[{norm_str(vb)}]")
return diffs, notes
def add_ledger_cols(df: pd.DataFrame, row_b: pd.Series | None) -> dict:
if row_b is None:
return {f"台账_{label}": "" for _, _, label in COMPARE_FIELDS}
out = {}
for col_a, col_b, label in COMPARE_FIELDS:
out[f"台账_{label}"] = row_b.get(col_b, "")
return out
def run():
df_rec = read_record_sheet(FILE_RECORD)
df_led = pd.read_excel(FILE_LEDGER, sheet_name="加氢订单")
# 台账限定 2026-01 ~ 2026-04，与加氢记录范围一致
df_led["_date_parsed"] = df_led["加氢时间"].apply(parse_date)
df_led_14 = df_led[
(df_led["_date_parsed"] >= "2026-01-01") & (df_led["_date_parsed"] < "2026-05-01")
].copy()
idx_rec = build_index(df_rec, "日期", "车牌", "加气量（kg)")
idx_led = build_index(df_led_14, "加氢时间", "车牌号", "加氢量(kg)")
all_keys = set(idx_rec) | set(idx_led)
pairs: list[tuple[int | None, int | None, str]] = []
for k in sorted(all_keys):
ra = idx_rec.get(k, [])
rb = idx_led.get(k, [])
paired = pair_rows(ra, rb)
for ia, ib in paired:
pairs.append((ia, ib, k))
for ia in ra[len(paired) :]:
pairs.append((ia, None, k))
for ib in rb[len(paired) :]:
pairs.append((None, ib, k))
# --- 加氢记录侧输出 ---
rows_rec_out = []
rec_diff_cells: dict[int, set[str]] = defaultdict(set) # excel row -> col names
rec_red_rows: set[int] = set()
for ia, ib, k in pairs:
if ia is None:
continue
row_a = df_rec.loc[ia]
row_b = df_led_14.loc[ib] if ib is not None else None
extra = add_ledger_cols(df_rec, row_b)
remark_parts = []
if ib is None:
if k in idx_led:
remark_parts.append("同键重复：加氢记录行数多于台账，本条未配对")
else:
remark_parts.append("台账缺失：加氢订单(1-4月)中无匹配记录")
rec_red_rows.add(len(rows_rec_out) + 2) # +2: header + 1-based
else:
diffs, notes = compare_pair(row_a, row_b)
if diffs:
remark_parts.append("字段差异：" + "；".join(notes))
for label in diffs:
rec_diff_cells[len(rows_rec_out) + 2].add(label)
rec_diff_cells[len(rows_rec_out) + 2].add(f"台账_{label}")
out_row = row_a.to_dict()
out_row.update(extra)
out_row["比对备注"] = "；".join(remark_parts) if remark_parts else "一致"
rows_rec_out.append(out_row)
df_rec_out = pd.DataFrame(rows_rec_out)
# --- 加氢订单侧输出（含仅台账有、加氢记录无）---
rows_led_out = []
led_diff_cells: dict[int, set[str]] = defaultdict(set)
led_red_rows: set[int] = set()
for ia, ib, k in pairs:
if ib is None:
continue
row_b = df_led_14.loc[ib]
row_a = df_rec.loc[ia] if ia is not None else None
out_row = row_b.drop(labels=["_date_parsed"], errors="ignore").to_dict()
remark_parts = []
if ia is None:
if k in idx_rec:
remark_parts.append("同键重复：台账行数多于加氢记录，本条未配对")
else:
remark_parts.append("加氢记录缺失：加氢记录表中无匹配记录")
led_red_rows.add(len(rows_led_out) + 2)
else:
diffs, notes = compare_pair(row_a, row_b)
if diffs:
remark_parts.append("字段差异：" + "；".join(notes))
col_map = {label: col_b for _, col_b, label in COMPARE_FIELDS}
for label in diffs:
led_diff_cells[len(rows_led_out) + 2].add(col_map[label])
out_row["比对备注"] = "；".join(remark_parts) if remark_parts else "一致"
rows_led_out.append(out_row)
df_led_out = pd.DataFrame(rows_led_out)
# 汇总
matched = sum(1 for ia, ib, _ in pairs if ia is not None and ib is not None)
only_rec = sum(1 for ia, ib, _ in pairs if ia is not None and ib is None)
only_led = sum(1 for ia, ib, _ in pairs if ia is None and ib is not None)
only_rec_true = sum(
1 for ia, ib, k in pairs if ia is not None and ib is None and k not in idx_led
)
only_rec_dup = only_rec - only_rec_true
only_led_true = sum(
1 for ia, ib, k in pairs if ia is None and ib is not None and k not in idx_rec
)
only_led_dup = only_led - only_led_true
diff_count = sum(
1
for ia, ib, _ in pairs
if ia is not None and ib is not None and compare_pair(df_rec.loc[ia], df_led_14.loc[ib])[0]
)
summary = pd.DataFrame(
[
["加氢记录行数", len(df_rec)],
["台账加氢订单(1-4月)行数", len(df_led_14)],
["匹配键(日期+车牌+加氢量)对数", matched],
["仅加氢记录有-合计", only_rec],
[" 其中台账真缺失", only_rec_true],
[" 其中同键重复多出", only_rec_dup],
["仅台账有-合计", only_led],
[" 其中加氢记录真缺失", only_led_true],
[" 其中同键重复多出", only_led_dup],
["匹配但字段有差异", diff_count],
],
columns=["项目", "数量"],
)
OUT_DIR.mkdir(parents=True, exist_ok=True)
with pd.ExcelWriter(OUT_FILE, engine="openpyxl") as writer:
summary.to_excel(writer, sheet_name="比对汇总", index=False)
df_rec_out.to_excel(writer, sheet_name="加氢记录-比对", index=False)
df_led_out.to_excel(writer, sheet_name="加氢订单-比对", index=False)
apply_styles_rec(df_rec_out, rec_diff_cells, rec_red_rows)
apply_styles_led(df_led_out, led_diff_cells, led_red_rows)
print(f"已输出: {OUT_FILE}")
print(summary.to_string(index=False))
def col_letter_map(columns: list) -> dict[str, int]:
return {str(c): i + 1 for i, c in enumerate(columns)}
def apply_styles_rec(df: pd.DataFrame, diff_cells: dict, red_rows: set):
wb = load_workbook(OUT_FILE)
ws = wb["加氢记录-比对"]
cmap = col_letter_map(list(df.columns))
label_to_col = {label: label for _, _, label in COMPARE_FIELDS}
label_to_col.update({label: f"台账_{label}" for _, _, label in COMPARE_FIELDS})
for row_idx, labels in diff_cells.items():
for label in labels:
col = label_to_col.get(label, label)
if col in cmap:
ws.cell(row=row_idx, column=cmap[col]).fill = YELLOW
for row_idx in red_rows:
for c in range(1, ws.max_column + 1):
ws.cell(row=row_idx, column=c).fill = RED
if "比对备注" in cmap:
ws.cell(row=row_idx, column=cmap["比对备注"]).font = RED_FONT
wb.save(OUT_FILE)
def apply_styles_led(df: pd.DataFrame, diff_cells: dict, red_rows: set):
wb = load_workbook(OUT_FILE)
ws = wb["加氢订单-比对"]
cmap = col_letter_map(list(df.columns))
for row_idx, labels in diff_cells.items():
for col_name in labels:
if col_name in cmap:
ws.cell(row=row_idx, column=cmap[col_name]).fill = YELLOW
for row_idx in red_rows:
for c in range(1, ws.max_column + 1):
ws.cell(row=row_idx, column=c).fill = RED
if "比对备注" in cmap:
ws.cell(row=row_idx, column=cmap["比对备注"]).font = RED_FONT
wb.save(OUT_FILE)
if __name__ == "__main__":
run()