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fix: match scanned devices to canvas nodes by ip-token and mac (#258)

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Node.ip stores several comma-separated addresses once a user adds an
IPv6 (e.g. "fe80::1, 192.168.1.5"). All placement/inventory matching did
exact string equality on that field, so a device scanned as the plain
IPv4 looked absent from the canvas: canvas_count stayed 0, the "In N
canvas" badge and hide-on-canvas button vanished, and bulk-approve
re-placed a duplicate node.

Match per-address instead, and add MAC (a stable identifier immune to IP
edits) as a cumulative match key alongside ieee/ip:
- _canvas_correlation indexes ip per token + by_mac
- bulk_approve skip detection tokenizes ip + tracks mac
- find_duplicate_node narrows with Node.ip.contains then confirms per
  token in Python (guards the 10.0.0.4 / 10.0.0.40 substring false match)

ha-relevant: maybe
This commit is contained in:
Pouzor
2026-07-09 14:41:53 +02:00
parent 2bebe8f42d
commit 2d3b646e45
3 changed files with 192 additions and 36 deletions
Download Patch File Download Diff File Expand all files Collapse all files
backend/app/api/routes/scan.py
+60 -20
View File
@@ -27,6 +27,17 @@ _ZIGBEE_TYPES = {"zigbee_coordinator", "zigbee_router", "zigbee_enddevice"}
_ZWAVE_TYPES = {"zwave_coordinator", "zwave_router", "zwave_enddevice"}
def _ip_tokens(ip: str | None) -> list[str]:
"""Split a Node/device ``ip`` field into individual addresses.
The canvas stores multiple addresses in one comma-separated string (e.g.
``"fe80::1, 192.168.1.5"`` once a user adds an IPv6 address). Matching a
scanned device against that field must compare per-address, not against the
whole string, or the device looks absent from the canvas (issue #258).
"""
return [t.strip() for t in ip.split(",") if t.strip()] if ip else []
def _is_wireless(node_type: str | None) -> bool:
"""Zigbee + Z-Wave mesh devices share online status / no ICMP check."""
return node_type in _ZIGBEE_TYPES or node_type in _ZWAVE_TYPES
@@ -215,12 +226,18 @@ def _agg(values: list[datetime], *, newest: bool) -> datetime | None:
async def _canvas_correlation(
db: AsyncSession, devices: list[PendingDevice]
) -> dict[str, dict[str, Any]]:
"""Correlate each device to existing canvas nodes by ``ieee_address`` or ``ip``.
"""Correlate each device to existing canvas nodes by ``ieee_address``, ``mac``
or ``ip``.
Returns, per device id: the number of distinct canvases (designs) it appears
on, plus aggregated timestamps from every matching node — created_at (oldest),
last_scan / updated_at / last_seen (newest). One node query, grouped in Python
(node counts are small for a homelab), so no N+1 per device.
IP matching is per-address: a node's ``ip`` may hold several comma-separated
addresses (e.g. an IPv6 added before the IPv4), so we index each token, not
the raw string. MAC is a stable identifier immune to such IP edits, so it is
matched too — cumulatively with ieee/ip (issue #258).
"""
if not devices:
return {}
@@ -228,6 +245,7 @@ async def _canvas_correlation(
await db.execute(
select(
Node.ip,
Node.mac,
Node.ieee_address,
Node.design_id,
Node.created_at,
@@ -237,12 +255,15 @@ async def _canvas_correlation(
).where(Node.design_id.isnot(None))
)
).all()
# Index matching nodes by ip and by ieee so a device can look up both.
# Index matching nodes by ip token, mac and ieee so a device can look up any.
by_ip: dict[str, list[Any]] = {}
by_mac: dict[str, list[Any]] = {}
by_ieee: dict[str, list[Any]] = {}
for row in rows:
if row.ip:
by_ip.setdefault(row.ip, []).append(row)
for tok in _ip_tokens(row.ip):
by_ip.setdefault(tok, []).append(row)
if row.mac:
by_mac.setdefault(row.mac, []).append(row)
if row.ieee_address:
by_ieee.setdefault(row.ieee_address, []).append(row)
@@ -251,9 +272,11 @@ async def _canvas_correlation(
matched = []
if d.ieee_address:
matched += by_ieee.get(d.ieee_address, [])
if d.ip:
matched += by_ip.get(d.ip, [])
# De-duplicate nodes matched by both ip and ieee.
if d.mac:
matched += by_mac.get(d.mac, [])
for tok in _ip_tokens(d.ip):
matched += by_ip.get(tok, [])
# De-duplicate nodes matched by more than one identifier.
matched = list({id(m): m for m in matched}.values())
designs = {m.design_id for m in matched}
info[d.id] = {
@@ -335,17 +358,24 @@ async def bulk_approve_devices(
devices = result.scalars().all()
# What already sits on the target canvas, so we skip devices already placed
# here (by ip or ieee_address) instead of creating duplicate nodes. We map to
# the existing node id so the skip report can point the user at it. A value
# may be a Node still pending flush (in-batch duplicate) — resolved to its id
# after the flush below.
# here (by ip, mac or ieee_address) instead of creating duplicate nodes. We
# map to the existing node id so the skip report can point the user at it. A
# value may be a Node still pending flush (in-batch duplicate) — resolved to
# its id after the flush below. IPs are indexed per comma-separated token so
# a node whose ip is "fe80::1, 192.168.1.5" still matches a device scanned as
# 192.168.1.5 (issue #258).
existing = (
await db.execute(
select(Node.id, Node.ip, Node.ieee_address).where(Node.design_id == default_design_id)
select(Node.id, Node.ip, Node.mac, Node.ieee_address).where(
Node.design_id == default_design_id
)
)
).all()
placed_ips: dict[str, Any] = {ip: nid for nid, ip, _ in existing if ip}
placed_ieee: dict[str, Any] = {ieee: nid for nid, _, ieee in existing if ieee}
placed_ips: dict[str, Any] = {
tok: nid for nid, ip, _, _ in existing for tok in _ip_tokens(ip)
}
placed_mac: dict[str, Any] = {mac: nid for nid, _, mac, _ in existing if mac}
placed_ieee: dict[str, Any] = {ieee: nid for nid, _, _, ieee in existing if ieee}
created_nodes: list[Node] = []
approved_devices: list[PendingDevice] = []
@@ -353,11 +383,12 @@ async def bulk_approve_devices(
for device in devices:
# Record which identifier collided so the caller can explain each skip
# (and, for existing on-canvas nodes, link to the node already there).
if device.ip is not None and device.ip in placed_ips:
ip_hit = next((t for t in _ip_tokens(device.ip) if t in placed_ips), None)
if ip_hit is not None:
skipped_devices.append({
"device_id": device.id,
"label": device.hostname or device.friendly_name or device.ip or "device",
"match": "ip", "value": device.ip, "_ref": placed_ips[device.ip],
"match": "ip", "value": ip_hit, "_ref": placed_ips[ip_hit],
})
continue
if device.ieee_address is not None and device.ieee_address in placed_ieee:
@@ -367,6 +398,13 @@ async def bulk_approve_devices(
"match": "ieee", "value": device.ieee_address, "_ref": placed_ieee[device.ieee_address],
})
continue
if device.mac is not None and device.mac in placed_mac:
skipped_devices.append({
"device_id": device.id,
"label": device.hostname or device.friendly_name or device.mac or "device",
"match": "mac", "value": device.mac, "_ref": placed_mac[device.mac],
})
continue
device.status = "approved"
node_type = device.suggested_type or "generic"
is_wireless = _is_wireless(node_type)
@@ -394,11 +432,13 @@ async def bulk_approve_devices(
db.add(node)
created_nodes.append(node)
approved_devices.append(device)
# Track within this batch so a duplicate selection (same ip/ieee) is not
# placed twice on the same canvas. Store the Node so a later in-batch
# Track within this batch so a duplicate selection (same ip/mac/ieee) is
# not placed twice on the same canvas. Store the Node so a later in-batch
# skip can resolve to its id after flush.
if device.ip:
placed_ips[device.ip] = node
for tok in _ip_tokens(device.ip):
placed_ips[tok] = node
if device.mac:
placed_mac[device.mac] = node
if device.ieee_address:
placed_ieee[device.ieee_address] = node
await db.flush() # populates node.id from Python-side default before reading