Files
leocrm/app/core/outbox.py
T
Agent Zero 727d86614e Security fixes: P0-P2 complete (22 fixes)
P0 (7): Auth-bypass removed, migrations fixed, plugin-upload disabled, RLS FORCE+WITH CHECK, plugin double-registration fixed, persistent volume, domain removed
P1 (11): User/tenant model, Redis centralized, worker separated, transactional outbox, XSS fixed, DMS chunked streaming, permissions unified, password reset, metrics secured, config/docs fixed, cross-tenant FK
P2 (4): Contact model normalized, cross-imports reduced 94%, commands+state machines for contacts/dms/mail/calendar, SPA path-traversal

8 new migrations, 99 unit tests, 13 commands, 8 contracts, 72 files changed
2026-07-25 21:03:46 +02:00

211 lines
6.1 KiB
Python

"""Transactional outbox for reliable domain event delivery.
Instead of publishing events directly to an in-process bus (which is lost
on crash/restart), domain events are written to the ``event_outbox`` table
**within the same database transaction** as the business operation. A
background worker then polls the outbox and publishes events to the
in-process event bus.
Usage in services::
from app.core.outbox import enqueue_outbox_event
await enqueue_outbox_event(db, tenant_id, "contact.created", {
"contact_id": str(contact.id),
"tenant_id": str(tenant_id),
})
# ... later, the transaction commits and the event is durable.
"""
from __future__ import annotations
import logging
import uuid
from datetime import datetime, timedelta, timezone
from typing import Any
import redis.asyncio as aioredis
from sqlalchemy import text
from sqlalchemy.ext.asyncio import AsyncSession
logger = logging.getLogger(__name__)
# ── SQL statements (raw text for FOR UPDATE SKIP LOCKED) ────────────────────
_INSERT_SQL = text(
"""
INSERT INTO event_outbox (tenant_id, event_name, payload)
VALUES (:tenant_id, :event_name, CAST(:payload AS JSONB))
"""
)
_CLAIM_SQL = text(
"""
UPDATE event_outbox
SET status = 'processing',
updated_at = now()
WHERE id IN (
SELECT id FROM event_outbox
WHERE status = 'pending'
AND (next_retry_at IS NULL OR next_retry_at <= now())
ORDER BY created_at
LIMIT :batch_size
FOR UPDATE SKIP LOCKED
)
RETURNING id, tenant_id, event_name, payload, attempts, max_attempts
"""
)
_MARK_PUBLISHED_SQL = text(
"""
UPDATE event_outbox
SET status = 'published',
published_at = now(),
updated_at = now()
WHERE id = :id
"""
)
_FAIL_SQL = text(
"""
UPDATE event_outbox
SET status = 'failed',
updated_at = now()
WHERE id = :id
"""
)
_RETRY_SQL = text(
"""
UPDATE event_outbox
SET status = 'pending',
attempts = :attempts,
next_retry_at = :next_retry_at,
updated_at = now()
WHERE id = :id
"""
)
def _json_payload(payload: dict[str, Any]) -> str:
"""Serialise payload to a JSON string suitable for JSONB cast."""
import json
return json.dumps(payload, default=str)
async def enqueue_outbox_event(
db: AsyncSession,
tenant_id: uuid.UUID,
event_name: str,
payload: dict[str, Any],
) -> None:
"""Insert an event into the outbox table within the current transaction.
The event is only persisted when the surrounding transaction commits.
This guarantees at-least-once delivery — no event is lost even if the
process crashes after the business operation but before the event is
published.
Args:
db: Active async SQLAlchemy session (part of the business transaction).
tenant_id: Tenant scope for the event.
event_name: Logical event name (e.g. ``"contact.created"``).
payload: Event payload dict (will be stored as JSONB).
"""
await db.execute(
_INSERT_SQL,
{
"tenant_id": str(tenant_id),
"event_name": event_name,
"payload": _json_payload(payload),
},
)
async def process_outbox_batch(
db: AsyncSession,
redis: aioredis.Redis | None = None,
batch_size: int = 50,
) -> int:
"""Process one batch of pending outbox events.
1. Claim up to *batch_size* pending events using ``FOR UPDATE SKIP LOCKED``
so multiple workers don't interfere.
2. Publish each event to the in-process event bus (for local handlers).
3. On success: mark as ``published``.
4. On failure: increment attempts, schedule retry with exponential
backoff, or mark as ``failed`` if max attempts exceeded.
Args:
db: Async SQLAlchemy session for this batch.
redis: Optional Redis client (unused for now, reserved for future
cross-process pub/sub).
batch_size: Maximum events to process in one batch.
Returns:
Number of events successfully published.
"""
from app.core.event_bus import get_event_bus
event_bus = get_event_bus()
published_count = 0
# Claim a batch of pending events
rows = (
await db.execute(_CLAIM_SQL, {"batch_size": batch_size})
).fetchall()
if not rows:
return 0
for row in rows:
event_id = row[0]
event_name = row[2]
payload = row[3]
attempts = row[4]
max_attempts = row[5]
# payload comes back as a dict from JSONB
if isinstance(payload, str):
import json
payload_dict = json.loads(payload)
else:
payload_dict = payload
try:
results = await event_bus.publish_with_results(event_name, payload_dict)
# If any handler raised, treat as failure
handler_errors = [r for r in results if r is not None]
if handler_errors:
raise handler_errors[0]
await db.execute(_MARK_PUBLISHED_SQL, {"id": str(event_id)})
published_count += 1
except Exception as exc:
logger.error(
"Failed to publish outbox event %s (%s): %s",
event_id, event_name, exc,
exc_info=True,
)
new_attempts = attempts + 1
if new_attempts >= max_attempts:
await db.execute(_FAIL_SQL, {"id": str(event_id)})
logger.warning(
"Outbox event %s marked as failed after %d attempts",
event_id, new_attempts,
)
else:
backoff = timedelta(seconds=(2 ** new_attempts) * 10)
next_retry = datetime.now(timezone.utc) + backoff
await db.execute(
_RETRY_SQL,
{
"id": str(event_id),
"attempts": new_attempts,
"next_retry_at": next_retry,
},
)
await db.commit()
return published_count