- GW1: write commands (C2) carry only the server_id; ServerConfigResolver resolves the connection (command override, live pooled connection, connectors, opc-servers) with a 60 s cache and a 10 s negative cache. - GW2: write_status keeps the worst outcome (ok < error < session_bad, pending/NULL replaced), same rule as the Laborious, built with SQLAlchemy Core (no SQL formatting). - GW3: update_write_status never raises; outcome (updated, kept, row_not_found, invalid, error) logged and counted (opc_write_status_update_total); runs off the event loop. - GW4: the reason of a failed write is logged; opc_write_status_by_model shows the last outcome; a bad timestamp is a failed write, not an exception. - GW5: the NATS first connect gives up after 5 s (nats-py's defaults block the main loop for about 4 minutes while NATS is down); reconnection after it is unbounded; idle_sweep restarts a connection closed for good; stop() is safe on a closed connection. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
6.8 KiB
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project
OPC UA data ingestion service. Pulls tags from OPC UA servers, streams to Kafka (optional) and persists to MongoDB. Horizontally scaled via Redis-coordinated slot leasing — multiple pods share tag load without central orchestration.
Depends on internal shared lib sientia-dataops-library (imported as sientia_do, pinned in requirements.txt via git+ssh) for logging, notifications, metrics controller, and Mongo/Redis repositories. Base classes/utilities from sientia_do won't be visible in this repo — check that lib's source if behavior there is unclear.
Commands
python3.11 -m venv venv && source ./venv/bin/activate
pip install -r requirements.txt -r requirements-dev.txt
./run_local.sh # loads .env, runs python -m ingestor.app
./run_coverage.sh # pytest --cov=ingestor --cov-report=html, opens report
pytest # all tests
pytest tests/unit # unit only
pytest tests/functional # functional only (spins up real-ish clients, see conftest.py)
pytest tests/unit/test_ingestor.py::TestClass::test_name # single test
pytest --cov=ingestor --cov-report=html # coverage report -> htmlcov/
ruff check . # lint
ruff format . # format
mypy ingestor # type check
bandit -r ingestor # security scan
External deps (Redis, MongoDB, Kafka) must be reachable — via kubectl port-forward, local docker-compose, or cloud services. Config lives in .env (copy from .env.example).
Architecture
Manager-based pipeline, one manager per concern, composed by IngestorManager:
app.py (asyncio loop, signals, Prometheus server)
-> Ingestor (ingestor.py) — lifecycle: prepare_ingestor() -> loop() -> shutdown()
-> IngestorManager (managers/ingestor_manager.py) — central coordinator
-> ResourceManager (managers/resource_manager.py) — Redis slot leases, heartbeats, active-ingestor registry
-> ServerReader (managers/server_reader.py), one per OPC server — SubscriptionEngine over the shared OpcConnectionPool
(READ_ENGINE=legacy: OpcManager (managers/opc_manager.py), the rc3 reader kept as plan B until the end of SIENTIAPDE-1974)
-> OpcConnectionPool (connection/pool.py) + CertProvider (connection/certs.py) — pooled connections, cert from MinIO
-> DataManager (managers/data_manager.py) — MongoDB persistence + optional Kafka publish
Slot model: OPC tag configs live in Redis under keys like slot:opc_tags:<n>, each holding one or more OPC servers and their tags (see README "OPC Server Configuration" for the JSON shape). A "slot" is the unit of lease/assignment; each ingestor pod leases some number of slots via ResourceManager and only subscribes to the tags in slots it holds.
Main loop (Ingestor.loop() in ingestor.py) each cycle:
declare_active()+ heartbeat (keeps this pod visible to peers via Redis TTL keys —LEASE_TTL/HEARTBEAT_TTL)- Reads current active-ingestor count, lease count, slot count
manage_no_slots()— grabs one slot if this pod is idle and slots existmanage_leases()— rebalances: acquires slots if other pods are lacking, drops extras (keeps at most 1 slot per pod when supply is sufficient) — this is the load-balancing algorithmupdate_slot_config()+check_opc_servers_integrity()— refresh OPC configs, detect stalled connectionsupdate_ingestor_manager()— diffs current vs previous managed tags, subscribes new, resubscribes changed, unsubscribes removed
Any change to slot/lease counts should be traced through manage_leases/manage_no_slots — that's where the rebalancing math lives, not in ResourceManager itself (which just does Redis primitives).
ServerReader (SIENTIAPDE-1974, default READ_ENGINE=v2; the legacy OpcManager stays as plan B with READ_ENGINE=legacy — slot v1 only, certificate files from the Gitea clone — until it is unused and the tests pass the same without it) reads one OPC server through a SubscriptionEngine: the connection comes from the shared OpcConnectionPool (also used by NATS writes and gRPC), which fetches the platform certificate from MinIO via CertProvider and uses SecurityPolicyBasic256Sha256 — no certificate files in the repo/image. Slots are parsed by io/slots.py (parse_slot), which accepts slot v2 (names[]) and converts the legacy v1 (topics). datachange_notification fans each value out to every names entry via DataSink. Subscribed connections are pinned in the pool so the idle sweep never drops them. Tracks non_receive_count to detect silently-dead subscriptions (check_cycles / check_opc_listenning); a lost server is shut down (pool connection evicted) and re-initialized on the next loop.
Writes (SIENTIAPDE-1975): NatsWriteConsumer → WriteEngine → pool, then DataSink.update_write_status. Commands (C2) carry only server_id; ServerConfigResolver (connection/servers.py) resolves the connection (command override → live pooled connection → connectors → opc-servers). write_status keeps the worst outcome (ok < error < session_bad; same rule as the Laborious' laborious/utils/write_status.py — keep both in sync). The NATS first connect is bounded (it runs on the main loop); reconnection after it is unbounded.
Metrics (ingestor/metrics.py): all Prometheus metrics defined here, always labeled by pod_id. Emitted via SientiaMonitoring.emit_metric(...) (from sientia_do), not the prometheus client directly — new metrics should follow that pattern for consistency with logging/notifications.
Error handling convention: broad except Exception + traceback.print_exc() + notification-handler alert is intentional throughout (see ruff.lint.ignore for BLE001 in pyproject.toml) — this is an always-on service where a single tag/server failure must not kill the pod; failures are surfaced via notifications/metrics instead of raised.
Config
Env vars documented in README ("Configuration" section) and .env.example. Notable ones affecting behavior: LEASE_TTL/HEARTBEAT_TTL (failover speed vs stability), POLL_INTERVAL (loop cadence), EXPORT_TO_KAFKA.
Testing notes
tests/unit/managers/mirrorsingestor/managers/1:1.tests/functional/exercises more end-to-end paths againstconftest.pyfixtures.- Coverage config (
pyproject.toml/.coveragerc) excludesingestor/app.py(thin entrypoint, signal wiring) — don't chase coverage there. ruffcomplexity cap ismax-complexity = 15(mccabe) — factor out branches in manager methods before that.