NetAlertX database architecture patterns. Use this when designing features that write to the Devices table, implementing audit/history logging, or choosing between trigger-based vs Python-hook approaches.
64
75%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Passed
No findings from the security scan
Fix and improve this skill with Tessl
tessl review fix ./.github/skills/database-patterns/SKILL.mdBefore implementing any feature that reads or writes the Devices table, audit ALL write paths. The table is modified from many locations — missing one path is a correctness bug.
Known production write paths (as of 2026-07-04):
| File | Function | Fields written |
|---|---|---|
server/models/device_instance.py | setDeviceData() | All user-editable fields |
server/models/device_instance.py | updateField() | Any single field (workflows) |
server/models/device_instance.py | updateDeviceColumn() | Any single column |
server/models/device_instance.py | deleteDevices() etc. | DELETE operations |
server/scan/device_handling.py | update_devices_data_from_scan() | Scan-derived fields |
server/scan/device_handling.py | update_vendors_from_mac() | devVendor, devVendorSource |
server/scan/device_handling.py | Name resolution block | devName, devFQDN, *Source |
server/scan/device_handling.py | update_ipv4_ipv6() | devPrimaryIPv4, devPrimaryIPv6 |
server/scan/device_handling.py | update_icons_and_types() | devIcon, devType |
server/scan/device_handling.py | update_presence_from_CurrentScan() | devPresentLastScan |
server/scan/device_handling.py | update_devLastConnection_from_CurrentScan() | devLastConnection |
server/scan/device_handling.py | update_devPresentLastScan_based_on_*() | devPresentLastScan |
server/db/authoritative_handler.py | enforce_source_on_user_update() | *Source columns |
server/db/authoritative_handler.py | lock_field() / unlock_field() | *Source columns |
server/models/notification_instance.py | clearPendingEmailFlag() | devLastNotification |
front/plugins/db_cleanup/script.py | cleanup_database() | DELETE operations |
Key insight: Most scan functions use sql.executemany() — there is no per-row Python state available. Python hooks before/after executemany require a pre-fetch+diff pattern that is expensive and error-prone.
*Source Fields — Attribution SystemThe FIELD_SOURCE_MAP in server/db/authoritative_handler.py defines 10 fields that carry write attribution via paired *Source columns:
FIELD_SOURCE_MAP = {
"devMac": "devMacSource",
"devName": "devNameSource",
"devFQDN": "devFQDNSource",
"devLastIP": "devLastIPSource",
"devVendor": "devVendorSource",
"devSSID": "devSSIDSource",
"devParentMAC": "devParentMACSource",
"devParentPort": "devParentPortSource",
"devParentRelType": "devParentRelTypeSource",
"devVlan": "devVlanSource",
}*Source values: 'USER', 'LOCKED', 'NEWDEV', or a plugin prefix (e.g., 'ARPSCAN', 'NSLOOKUP').
These fields are updated in the same transaction as the primary field. A SQLite AFTER UPDATE trigger can read NEW.devNameSource to obtain correct attribution without any extra context-passing.
Attribution rules for features that need changedBy:
| Field category | Attribution |
|---|---|
In FIELD_SOURCE_MAP | COALESCE(NULLIF(NEW.<field>Source, ''), 'system') |
User-only fields (devGroup, devComments, devFavorite, devOwner, devLocation, etc.) | 'user:api' — only setDeviceData() writes these |
Auto-computed fields (devIcon, devType, devPrimaryIPv4, devPrimaryIPv6) | 'system' |
*Source fields themselves | 'system' |
When a feature needs to intercept every write to the Devices table (audit logging, computed columns, cascading logic), prefer a SQLite AFTER UPDATE / AFTER INSERT trigger over Python-layer hooks.
Why:
executemany() bulk updatesNEW.*Source fields (see above)When Python hooks are still appropriate:
CREATE TRIGGER trg_example
AFTER UPDATE ON Devices
FOR EACH ROW
-- Guard: short-circuit entire body when feature is disabled (zero cost)
WHEN (SELECT CAST(setValue AS INTEGER) FROM Settings WHERE setKey = 'FEATURE_ENABLED') > 0
BEGIN
-- Per-field conditional insert
INSERT INTO SomeTable (devGUID, column, oldVal, newVal, changedBy, ts)
SELECT NEW.devGUID, 'devName', OLD.devName, NEW.devName,
COALESCE(NULLIF(NEW.devNameSource, ''), 'system'),
datetime('now', 'utc')
WHERE OLD.devName IS NOT NEW.devName
AND instr(',' || (SELECT setValue FROM Settings WHERE setKey = 'TRACKED_FIELDS') || ',', ',devName,') > 0;
-- Repeat for each tracked field...
END;Performance: The Settings table is tiny (~100 rows) and stays in SQLite's page cache. Per-row Settings reads inside triggers are effectively in-memory lookups. The WHEN guard makes the disabled state zero-cost.
When implementing change history, always use event-sourced (per-field rows) not snapshots (full row copies).
| Event-sourced | Snapshot | |
|---|---|---|
| Storage | Small — only changed fields | Large — all 40+ columns every mutation |
| Filter by field | O(log n) via index | O(n) — must diff every adjacent pair |
| Filter by source | O(log n) via index | Not possible without diffing |
changedBy attribution | Embedded at write time | Not available without extra context |
| Retention calculation | Simple timestamp DELETE | Same, but much higher storage |
At 1000 devices, 5-min scan interval, 14-day retention: snapshot storage ≈ 280 MB/day. Event-sourced storage for the same workload is typically <1 MB/day (most scans produce no tracked field changes).
DevicesHistory Table — Reference SchemaCREATE TABLE IF NOT EXISTS DevicesHistory (
id INTEGER PRIMARY KEY AUTOINCREMENT,
devGUID TEXT NOT NULL,
timestamp DATETIME DEFAULT CURRENT_TIMESTAMP,
changedBy TEXT NOT NULL,
changedColumn TEXT NOT NULL,
oldValue TEXT,
newValue TEXT,
FOREIGN KEY (devGUID) REFERENCES Devices(devGUID) ON DELETE CASCADE
);
CREATE INDEX IF NOT EXISTS idx_devhist_guid_column ON DevicesHistory(devGUID, changedColumn);
CREATE INDEX IF NOT EXISTS idx_devhist_timestamp ON DevicesHistory(timestamp);20ddf48
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.