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fencekit

CI PyPI Python tests License: MIT

Redis-backed idempotency and fenced distributed locks for background jobs.

Celery with acks_late redelivers work after a worker crash. Redis gives you SET NX and Lua. fencekit wraps those into tested pieces:

Piece Problem it solves
IdempotencyGuard Double-start / redelivery of the same logical job
DistributedLock + fencing token Two workers on the same resource at once
FenceGate / fenced_update Stale lock holder overwriting newer state after TTL expiry

Extracted from ChessMate (Celery + Redis + Postgres). See DESIGN.md for guarantees, non-guarantees, and crash semantics.

Install

pip install fencekit
pip install "fencekit[django]"   # optional Django QuerySet helper
pip install "fencekit[celery]"   # optional Celery task decorator
pip install "fencekit[otel]"     # optional OpenTelemetry hook factory

Requires Redis 6+ (tested with Redis 7) and Python 3.10+.

Quick example

from datetime import timedelta
from redis import Redis

from fencekit import (
    BeginOutcome,
    DistributedLock,
    FenceGate,
    IdempotencyGuard,
    IdempotencyResultMissing,
    fenced_update,
    idempotency_key,
)

r = Redis.from_url("redis://localhost:6379/0", decode_responses=True)
guard = IdempotencyGuard(r)
lock = DistributedLock(r)
fence = FenceGate(r)

def analyze_batch(job) -> dict | None:
    key = idempotency_key(
        {"game_ids": ["abc", "def"], "engine": "sf16"},
        namespace="analysis",
    )
    resource = f"analysis:{job.pk}"
    outcome = guard.try_begin_or_reclaim(
        key, lock=lock, lock_resource=resource, ttl=timedelta(hours=24)
    )
    if outcome == BeginOutcome.ALREADY_DONE:
        try:
            return guard.get_result(key)
        except IdempotencyResultMissing:
            return None
    if outcome == BeginOutcome.IN_PROGRESS:
        return None  # active worker holds the lock

    handle = lock.acquire(resource, ttl=timedelta(minutes=5), owner_id=guard.owner_id)
    try:
        fence.set_if_fresh(handle.token, f"analysis:{job.pk}:status", "running")
        fenced_update(
            type(job).objects.filter(pk=job.pk),
            handle.token,
            updates={"progress": 50, "status": "running"},
        )
        result = {"report_id": job.pk, "status": "done"}
        guard.mark_done(key, result=result, ttl=timedelta(hours=24))
        return result
    finally:
        lock.release(handle)

API overview

idempotency_key(payload, namespace=...): deterministic key from JSON-canonicalized payload.

IdempotencyGuard.try_begin / try_begin_or_reclaim / mark_done / get_result: at-most-once start; reclaim stale pending after crash; optional JSON memo on completion.

DistributedLock.acquire / release / extend: lease plus monotonic fencing token (Lua).

FenceGate.set_if_fresh: atomic fenced Redis string writes.

fenced_update(queryset, token, updates=...): fenced Django/Postgres UPDATE in one statement.

Typed public API (py.typed). Optional Celery helper: fencekit.celery.idempotent_task.

Observability (optional)

Pass :class:~fencekit.hooks.FenceKitHooks to IdempotencyGuard, DistributedLock, and FenceGate, or use the OTel factory:

from fencekit import DistributedLock, FenceKitHooks, IdempotencyGuard
from fencekit.otel import otel_hooks

hooks = otel_hooks()  # pip install "fencekit[otel]"
guard = IdempotencyGuard(redis, hooks=hooks)
lock = DistributedLock(redis, hooks=hooks)

Hook callbacks must not raise; fencekit swallows errors so metrics cannot break jobs.

Celery (optional)

from datetime import timedelta

from fencekit.celery import idempotent_task
from fencekit import DistributedLock, IdempotencyGuard, idempotency_key

guard = IdempotencyGuard(redis)
lock = DistributedLock(redis)

@shared_task(bind=True)
@idempotent_task(
    guard,
    lock,
    key=lambda batch_id: idempotency_key({"batch_id": batch_id}, namespace="analysis"),
    lock_resource=lambda batch_id: f"analysis:{batch_id}",
    idempotency_ttl=timedelta(hours=24),
    lock_ttl=timedelta(minutes=5),
    retry_on_in_progress=True,
)
def analyze_batch(self, batch_id: str) -> dict:
    ...

Comparison

Short view. Sources and nuance: docs/COMPARISON.md.

Dedup start Celery plugin Stale-write fencing Postgres helper
fencekit Yes Manual Yes fenced_update
celery-once / celery-singleton Yes Yes No No
redis-py Lock No No No No
relier Yes Yes Partial (framework) App-owned

fencekit complements celery-once. celery-once dedupes scheduling; fencekit rejects writes from a worker whose lock TTL already expired.

Local demo (no cloud)

Redis via Docker on your machine. No hosted services, no monthly bill.

docker compose -f examples/reference/docker-compose.yml up -d
pip install -e .
python examples/reference/demo_stale_fence.py
python examples/reference/demo_idempotency.py

See examples/reference/README.md.

Guarantees

Claim Status
At-most-once start within idempotency TTL Yes (SET NX)
Memoized result after mark_done(..., result=...) Yes (within TTL)
Mutual exclusion while lock TTL held (single Redis primary) Best-effort lease
Stale holder blocked via FenceGate / fenced_update Yes (when used)
Exactly-once delivery No
Safety under Redis failover / split brain No
Writes that skip the fencing token No

fencekit does not implement Redlock. Fencing only works when the storage layer checks the token in the same operation as the write.

Development

REM Windows (CMD)
python -m pip install -e ".[dev]"
python -m ruff check src tests
python -m mypy src
python -m pytest -m "not integration" -q

Full suite (Redis on localhost:6379):

set FENCEKIT_REDIS_URL=redis://localhost:6379/15
python -m pytest -q
# Linux/macOS with uv
uv sync --extra dev
uv run pytest

CI runs lint, type-check, and tests on Python 3.10–3.13 with Redis. Releases publish to PyPI via Trusted Publishing (OIDC, no long-lived token).

License

MIT

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