Replace pandas with a small openpyxl/csv reader for imports.

pandas + numpy were ~60MB of the shipped venv for three call sites (alarm
Excel import, managed-NE import, import template). netx_api/tabular.py
reads/writes xlsx and csv and parses spreadsheet timestamps.

Checked against the pandas version on the same inputs: timestamp parsing
identical for 24 formats, managed-NE csv/xlsx import, stored rows and both
templates identical. Differences, all fixes:
- alarm codes in mixed text/number columns are "1001", not "1001.0"
- error row numbers are the real sheet rows (blank rows no longer shift them)
- GBK-encoded CSVs (Chinese Excel "Save as CSV") import instead of failing
- "2024年1月2日 03:04:05" style timestamps parse

Also: conftest compares parsed DB URLs (newer SQLAlchemy renders "C:" as
"C%3A").

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

netx_api/ne_service_common.py

@@ -2,10 +2,10 @@
 from __future__ import annotations
 
 from datetime import datetime
+import math
 import re
 from typing import Any
 
-import pandas as pd
 from fastapi import HTTPException
 from sqlalchemy.orm import Session
 
@@ -199,7 +199,7 @@ def _parse_import_bool(value: Any) -> bool:
 
 
 def _import_cell_str(value: Any) -> str:
-    if value is None or (isinstance(value, float) and pd.isna(value)):
+    if value is None or (isinstance(value, float) and math.isnan(value)):
         return ""
     text = str(value).strip()
     return "" if text.lower() == "nan" else text