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>
Add column filters and clearer API error mapping for NE management, tighten port validation, and slim the workbench into reusable modules with cleaner styles.
Co-authored-by: Cursor <cursoragent@cursor.com>
Some hops only accept stelnet in system-view; make it a saved yes/no setting (default off) instead of auto-retry, and always ALTER the new column on API boot when Alembic skips legacy DDL.
Co-authored-by: Cursor <cursoragent@cursor.com>
Keep the public facade stable while moving device CRUD and sample/compare
logic into focused modules, and use naive UTC via timeutil plus FastAPI lifespan.
Co-authored-by: Cursor <cursoragent@cursor.com>
Keep thin facades for existing imports, tighten CSV import required columns, and restore Chinese WebCRT connection labels in status responses.
Co-authored-by: Cursor <cursoragent@cursor.com>
