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>
Set up netx as a standalone git-managed project with isolated Python dependencies, alarm ingestion/query APIs, oclaw bridge integration, and ops-focused UI enhancements including history and raw field access.
Co-authored-by: Cursor <cursoragent@cursor.com>
