fastapi-stream-lease

Limit simultaneously active SSE, LLM token streams, and WebSocket sessions across FastAPI/Starlette workers with Redis. Set a per-user limit, a global limit, or both. An extra connection receives HTTP 429 before streaming begins.

Request rate limiters answer “how many requests arrived this minute?” This package answers “how many streams are open right now?” It is useful when a connection can remain open for seconds or minutes. For a general-purpose distributed semaphore, consider py-redis-limiters or py-redis-semaphore.

Install

Requires Python 3.10+ and Redis 5.0+.

With Redis 5 and redis-py 8+, construct your client with redis.from_url(url, protocol=2): redis-py 8 defaults to RESP3, which Redis 5 does not support. See the redis-py protocol documentation.

pip install 'fastapi-stream-lease[fastapi]'

The fastapi extra supplies FastAPI for the HTTP helpers; the core package only requires redis.

Try it locally

The runnable SSE example accepts one API key from STREAM_DEMO_TOKEN and uses it as a demo identity. Start Redis, clone this repository, then run:

git clone https://github.com/agustin18/fastapi-stream-lease.git
cd fastapi-stream-lease
pip install -e '.[fastapi]' uvicorn
export STREAM_DEMO_TOKEN=local-secret
export REDIS_URL=redis://localhost:6379/0
uvicorn examples.sse_demo:app

In another terminal, open two streams, then try a third with the same key:

curl -N -H 'X-API-Key: local-secret' http://localhost:8000/stream

The first two requests stream events; the third receives 429 with a Retry-After header until a slot is freed. Replace the demo API key with your application's authenticated user or account ID before production use. Never use an unverified request parameter as the user ID.

FastAPI integration

from contextlib import asynccontextmanager

from fastapi import Depends, FastAPI, Request
from fastapi.responses import StreamingResponse
import redis.asyncio as redis

from fastapi_stream_lease import (
    LeaseConfig,
    StreamLeaseManager,
    StreamLeaseRejected,
    StreamLeaseUnavailable,
)

# Set explicit timeouts so slow Redis calls do not block worker threads
redis_client = redis.from_url(
    "redis://localhost:6379",
    socket_timeout=1.0,
    socket_connect_timeout=1.0,
)
manager = StreamLeaseManager(
    redis_client,
    LeaseConfig(max_per_user=2, max_global=500, lease_seconds=30),
)


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Verify cluster configuration consistency on worker startup (fail-fast on mismatch or outage)
    await manager.verify_cluster_config(strict=True)
    yield
    # Clean teardown: drain telemetry callbacks and close resources
    await manager.close(drain=True, timeout=5.0)
    await redis_client.aclose()


app = FastAPI(lifespan=lifespan)


async def authenticated_user_id() -> str:
    # Illustrative placeholder: replace with your auth dependency (e.g. API key or JWT sub).
    # For fully runnable code, see examples/sse_demo.py and examples/websocket_demo.py.
    return "user-123"


@app.exception_handler(StreamLeaseRejected)
async def rejected(request: Request, exc: StreamLeaseRejected):
    return exc.as_response()


@app.exception_handler(StreamLeaseUnavailable)
async def unavailable(request: Request, exc: StreamLeaseUnavailable):
    return exc.as_response()


@app.get("/stream")
async def stream(user_id: str = Depends(authenticated_user_id)):
    async def events():
        yield "data: token or event\n\n"

    # 1-Line Protected StreamingResponse (auto-acquires, wraps, and cleans up on errors)
    return await manager.stream(user_id, events())

    # Or manually acquire and convert:
    # lease = await manager.acquire(user_id)
    # return lease.as_streaming_response(events())

Close the Redis client in your application's lifespan shutdown handler. Reuse the same StreamLeaseManager and key_prefix across workers that share limits. max_per_user=0 or max_global=0 disables that limit; the global count is unavailable when global tracking is disabled.

For WebSockets, keep the context open for the whole session:

async with manager.lease(user_id) as lease:
    while True:
        message = await websocket.receive_text()
        await websocket.send_text(message)

The manager context and async with lease both renew while open. Handle normal WebSocket disconnects in your route as usual. If renewal fails or the lease expires, StreamLeaseLost interrupts the stream or context. Catch it at the application boundary if you want to record a metric or send an application-specific WebSocket close code. wrap(auto_renew=False) disables automatic renewal; use it only if you renew the lease yourself.

Behavior and limits

• Acquisition, renewal, expiration cleanup, and release use atomic Redis Lua scripts. The keys share a Redis Cluster hash tag, so a user and global limit can be checked in one script.
• Every lease expires after lease_seconds without a successful renewal. wrap() and manager.lease() renew every half interval by default. Transient Redis connection errors trigger fast retries across the remaining lease TTL (Adaptive Grace Period), preventing temporary hiccups from dropping active streams.
• If Redis is unavailable on initial acquisition, StreamLeaseUnavailable (HTTP 503) is raised by default (fail_open=False). Set fail_open=True in LeaseConfig if your application prefers allowing streams during Redis outages (graceful degradation).
• Normal completion or cancellation attempts immediate release. If Redis is unavailable during release, the lease is removed after expiration; cleanup of the key itself uses a longer TTL. An async iterator abandoned without being closed may also hold its slot until expiration. Use contextlib.aclosing() if your own consumer stops iteration early.
• get_active_count(user_id) counts active leases for one identity; get_active_count() counts globally when max_global is enabled. Neither is a historical usage metric.
• All workers sharing limits must use the same key prefix and compatible limit settings. Lease expiration is measured by Redis, avoiding clock differences among application workers.

Distributed Guarantees & Failure Model

Fail-Open Fallback Lease Lifecycle

When fail_open=True is enabled in LeaseConfig, the manager grants fallback leases during Redis outages to maintain service availability:

• Completely Unthrottled Fallback: While Redis is unavailable, fallback acquisitions are intentionally unthrottled; neither per-user nor global limits are enforced, even within a single worker process (no local in-memory semaphore is maintained).
• Local Time Basis: Fallback leases use time.monotonic() locally and are isolated to the executing worker process.
• No Retroactive Registration: Active fallback leases do not attempt retroactive registration into Redis when connectivity returns. They complete locally and release normally.

Production and Operational Guide

• Redis Client Timeouts: Always configure explicit timeouts on your Redis client (e.g. socket_timeout=1.0, socket_connect_timeout=1.0). Without timeouts, an unreachable Redis instance can block asyncio event loop execution indefinitely.
• Fail-Open vs. Fail-Closed Strategy:
  • fail_open=False (Default): Raises StreamLeaseUnavailable (HTTP 503) when Redis is unreachable. Enforces limits during transient network partitions at the cost of rejecting requests when the backend is down. (Note: asynchronous Redis replication or master failover can still lose recently acknowledged writes if a master fails before syncing to its replica).
  • fail_open=True: Automatically grants in-memory fallback leases when Redis encounters network or timeout errors. Keeps streaming endpoints open during outages, with the operational trade-off that limits are not coordinated across workers until Redis recovers. Authentication, authorization, and script syntax errors never fail open.
• Definitive Revocation vs. Network Errors: If Redis explicitly reports that a lease is missing or expired (renew() returning 0) or encounters an unhandled execution error, wrap() and lease() cancel the stream immediately to prevent exceeding limits. Transient network disconnects trigger rapid retries until the monotonic lease deadline is reached.
• Observability and Lifecycle Hooks (Best-Effort Telemetry Contract): LeaseConfig provides zero-dependency callback hooks (supporting both sync and async callables) to plug directly into Prometheus, Datadog, StatsD, or Sentry:

  config = LeaseConfig(
      on_acquired=lambda lease: PROMETHEUS_ACTIVE.inc(),
      on_released=lambda lease, reason: PROMETHEUS_ACTIVE.dec(),
      on_rejected=lambda uid, reason: PROMETHEUS_REJECTED.labels(reason=reason).inc(),
      on_lost=lambda lease, reason: PROMETHEUS_LOST.labels(reason=reason).inc(),
      on_backend_error=lambda exc: PROMETHEUS_BACKEND_ERRORS.inc(),
      hook_queue_size=1024,
  )
  

  • Best-Effort Delivery: Lifecycle callbacks are designed strictly for out-of-band telemetry and monitoring. If callbacks execute slower than event arrival and fill hook_queue_size, new events are dropped with a rate-limited log warning to preserve event-loop responsiveness. Never rely on lifecycle hooks for financial billing, credit deduction, or security-critical audits.
  • on_released receives a deterministic termination reason when delivered (completed, cancelled, error, lost, or manual). Lifecycle hooks remain best-effort telemetry signals and should not be treated as an authoritative source of active lease state.
  • Async vs Sync Hook Execution: Synchronous hooks are offloaded to an internal thread pool via asyncio.to_thread to protect the event loop. Asynchronous hooks execute directly on the event loop and must remain cooperative (do not perform blocking synchronous calls like time.sleep() or blocking I/O inside an async callback). If a synchronous callback is already executing in the thread pool, manager.close(timeout=...) will wait up to the timeout, but Python cannot forcibly terminate an active OS thread.
  • Dispatcher telemetry properties for operational monitoring: manager.dispatcher.queued_count, manager.dispatcher.dropped_count, manager.dispatcher.error_count, and manager.dispatcher.queue_depth.
  • On application shutdown, flush all pending telemetry events gracefully:

  await manager.close(drain=True, timeout=5.0)
  

• Cluster Configuration Drift Detection: In distributed environments with multiple worker processes or Kubernetes pods, ensure all instances share identical limit configurations. Canonical configuration is registered atomically via SET ... NX (persistent key {prefix}:config with no TTL expiration to prevent split-brain during rolling deploys):

  # Logs a warning on drift or raises ConfigurationMismatchError if strict=True.
  # Retries transient errors during Sentinel failovers; raises StreamLeaseUnavailable
  # on prolonged outages to trigger fail-fast Kubernetes CrashLoopBackOff.
  await manager.verify_cluster_config(strict=True)
  

  During transient Redis reconnects or Sentinel master elections (which typically resolve in 1–3 seconds), verify_cluster_config() retries across a short bounded window (retry_attempts=3, retry_delay=0.1s by default). If the coordination backend remains unavailable past all retries, strict=True raises StreamLeaseUnavailable to trigger fail-fast container exit so Kubernetes restarts the container or does not route traffic to unverified pods.

Changing Cluster Configuration Safely

Because {prefix}:config is persistent (stored with SET ... NX without TTL expiration) to prevent transient split-brain during normal rolling deployments, changing limit settings (e.g. updating max_global, max_per_user, lease_seconds, or fail_open) across an active cluster requires an intentional operational migration:

1. Option A: Prefix Versioning (Recommended for Zero-Downtime Blue/Green): Update your configuration's key_prefix (e.g. from myapp:streams:v1 to myapp:streams:v2). New worker pods establish and register their new canonical configuration immediately under the new prefix, while old pods gracefully drain active leases under the old prefix.
2. Option B: Configuration Reset for In-Place Rolling Updates: If you need to keep the exact same prefix:
   • Drain or stop existing worker instances.
   • Wait for remaining active leases to naturally expire (or revoke them).
   • Delete the canonical configuration key in Redis:

     redis-cli DEL "{my_prefix}:config"
     

   • Start the updated worker instances. The first new pod will atomically register the updated configuration fingerprint with SET ... NX, and subsequent pods will verify compatibility against it.

• Redis Failover & Sentinel Support: Automatically classifies ReadOnlyError (thrown when hitting a replica during master election) and ConnectionError as transient conditions, enabling adaptive renewal retries to ride out failovers without dropping active streams. Note that the Sentinel configuration in docker-compose.sentinel.yml uses aggressive test timings (down-after-milliseconds 1000, failover-timeout 5000); production environments should use standard recommended operational timeouts (down-after-milliseconds 5000–30000ms, failover-timeout 60000–180000ms).
• Redis Cluster Support: All keys use Redis hash tags ({prefix}:user:... and {prefix}:global), guaranteeing user and global sorted sets reside on the same hash slot for atomic multi-key Lua operations without CROSSSLOT errors. Validated under real 6-node sharded topologies (docker-compose.cluster.yml) with automated slot failover, MOVED redirection recovery, and drift verification (tests/test_cluster.py).
• Reproducible Concurrency Benchmarks: Run throughput and latency benchmarks against your local Redis instance with pre-warmed connection pool and multi-run statistics:

  docker compose run --rm backend uv run python benchmarks/bench_lease_concurrency.py --count 1000 --concurrency 50 --runs 3
  

• Docker Compose Testing Stack: Run the test suite and distributed coordination topologies cleanly:

  # Standard unit and integration test suite:
  docker compose run --rm backend uv run pytest
  
  # Redis Sentinel failover & chaos test suite:
  docker compose -f docker-compose.sentinel.yml up -d --wait
  docker compose -f docker-compose.sentinel.yml run --rm backend uv run pytest -o addopts='' tests/test_sentinel.py -vv -s
  
  # Redis Cluster 6-node multi-shard test suite:
  docker compose -f docker-compose.cluster.yml up -d --wait
  docker compose -f docker-compose.cluster.yml run --rm backend uv run --all-extras pytest -o addopts='' tests/test_cluster.py -vv -s
  

Examples directory

• examples/sse_demo.py: Server-Sent Events with API key authentication.
• examples/websocket_demo.py: WebSocket streams with standard close codes (1008 Policy Violation, 1013 Try Again Later).
• examples/openai_streaming_demo.py: LLM token streaming with official openai SDK and simulated fallback.
• examples/prometheus_metrics_demo.py: Prometheus metrics integration with zero-dependency lifecycle hooks.
• examples/sse_client_resilient.py: Resilient Python SSE client with exponential backoff & jitter.

Contributing and security

See CONTRIBUTING.md for the local workflow and SECURITY.md for private vulnerability reports. Changes are proposed through pull requests and merged by the maintainer after CI passes. The package is licensed under MIT.

CI checks formatting, lint, strict static typing, Redis 5, 7, and 8 behavior, Redis Sentinel and 6-node Redis Cluster failover chaos validation, package build, and 100% combined statement and branch coverage. Reports and feedback from production deployments are welcome for continuously documenting operational limits.