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aiofence

aiofence

codecov

Multi-reason cancellation contexts for Python asyncio. Inspired by Go's context.Context, aiofence provides a cancellation context that propagates hierarchically through your application via ContextVar — no need to thread events, flags, or tokens through every call signature. Declare cancellation sources once at the boundary — inner code just wraps cancellable work in a context manager and doesn't care about the actual reasons, though it can inspect them if needed.

The flagship use case is client disconnect. An inference or agent service burns GPU time and provider spend on requests nobody is listening to any more, and ASGI gives you exactly one shot at noticing. DisconnectMiddleware turns that one-shot signal into an ambient cancellation source, so any code below it can stop the work the moment the client goes away — with no Request in its signature and no wiring through the call stack. See Client disconnects.

Motivation

asyncio has been steadily adopting structured concurrency patterns — TaskGroup (3.11) and asyncio.timeout() (3.11) both came from trio and anyio. But one gap remains: asyncio can cancel tasks mechanically, but it can't tell you why you were cancelled, doesn't offer a non-raising timeout (move_on_after), and forces you to propagate cancellation sources through every call signature. When multiple sources exist (timeout, client disconnect, graceful shutdown), it gets messy fast:

async def handle_request(request, shutdown_event, timeout=30):
    try:
        async with asyncio.timeout(timeout):
            while not shutdown_event.is_set():
                chunk = await get_next_chunk()
                if request.is_disconnected():
                    break
                await process(chunk)
    except TimeoutError:
        ...
    except asyncio.CancelledError:
        # shutdown? disconnect? something else?
        ...

For a deeper dive into the problem and design rationale, see this Medium post.

aiofence solves this. Declare all cancellation sources once, composably. The callee doesn't even know cancellation exists:

with (
    on_timeout(30)
    .event(shutdown, code="shutdown")
    .move_on_cancel()
) as fence:
    result = await fetch_and_transform()

if not fence.cancelled:
    await save(result)
else:
    print(fence.cancel_reasons)       # (CancelReason(message='timed out after 30s', ...),)
    print(fence.cancelled_by("shutdown"))  # True / False

Or raise instead of inspect:

with on_timeout(30).raise_on_cancel() as fence:
    result = await fetch_and_transform()
# raises FenceCancelled if timed out

What about asyncio.shield()?

shield() prevents cancellation from reaching shielded code, but it works from the opposite direction — you protect everything that must not be cancelled. In practice this means wrapping database writes, state transitions, logging, and cleanup individually, and each function needs to know whether it's cancel-safe.

aiofence comes at it differently: most code doesn't know cancellation exists. You only wrap the expensive, safely-interruptible parts — the operations you want to cancel. For example, in an LLM inference service, you don't want to cancel database queries or response formatting. You want to cancel the LLM call that's burning GPU time for a client that already disconnected:

with (
    on_event(client_disconnect)
    .timeout(budget)
    .move_on_cancel()
) as fence:
    result = await llm.generate(prompt)  # cancellable

await db.save(result or fallback)  # always runs, no shield needed

Why not anyio?

anyio is one of the best async libraries in the Python ecosystem, and its CancelScope is a more powerful and general cancellation model than what asyncio provides natively. aiofence is narrower in scope and makes different trade-offs:

  1. Drop-in for existing asyncio code. anyio builds an explicit scope tree that replaces asyncio's cancellation model — its own cancel delivery, shielding, deadline aggregation, and cross-task propagation. If your app is already built on pure asyncio, adopting anyio is a significant migration. aiofence works directly with asyncio's cancel()/uncancel() counter protocol — no new runtime, no new cancellation model. If asyncio evolves its cancellation primitives, aiofence stays compatible.

  2. Different design philosophy. anyio's approach is a broad CancelScope over the whole operation, with CancelScope(shield=True) around the parts that must survive. aiofence takes the inverse: most code runs unaware of cancellation, and you wrap only the expensive, safely-interruptible parts with a Fence.

Features

Composable triggers — chain timeouts, events, deadlines, and custom triggers into a single Fencing. Each call returns a new immutable builder, so configs are safe to share and extend:

fencing = on_timeout(30, code="budget").event(shutdown, code="shutdown")

# extend per-operation
with fencing.timeout(5, code="db").move_on_cancel() as fence:
    await query_db()

Context propagation — store a Fencing in a ContextVar at the boundary, read it anywhere with get_current_fencing(). No need to pass configs through every call signature:

# HTTP handler boundary
with bind_fencing(on_event(disconnect, code="disconnect").timeout(30)):
    await handle_request()

# deep inside, no arguments needed
async def process():
    with get_current_fencing().move_on_cancel() as fence:
        await do_work()

Typed cancellation reasons — after cancellation, inspect which trigger fired. Each reason carries a machine-readable code for programmatic matching:

if fence.cancelled_by("disconnect"):
    log("client left")
elif fence.cancelled_by("budget"):
    return cached_result

Guarded cancellation — a trigger firing is not always a reason to cancel. Decline a reason while a precondition holds, scoped to one code so the rest of the fence keeps working:

with get_current_fencing().unless(generation.is_done, code="disconnect").move_on_cancel() as fence:
    async for chunk in upstream:   # keeps draining after the finish reason
        yield chunk

Native asyncio — works with asyncio's cancel()/uncancel() counter protocol. Compatible with TaskGroup, asyncio.timeout(). No new runtime, no dependencies.

Client disconnects

For Starlette and FastAPI, this is what aiofence is mainly built for. DisconnectMiddleware owns the request's receive channel — one reader, replayed to everything below it — and binds its disconnect event to the current Fencing context via bind_fencing() for the whole request. Installing it is the whole setup: when the client disconnects, any fence created from get_current_fencing() — anywhere in the call stack — is cancelled with code="disconnect" (DISCONNECT_CODE). Declaring DisconnectFencing on a route is optional, and only needed for a per-route code:

from starlette.middleware import Middleware
from aiofence.contrib.starlette import DISCONNECT_CODE, DisconnectMiddleware

app = FastAPI(middleware=[Middleware(DisconnectMiddleware)])   # outermost, required

@app.get("/work")
async def handler():
    with get_current_fencing().timeout(30, code="budget").move_on_cancel() as fence:
        await long_work()

    if fence.cancelled_by(DISCONNECT_CODE):
        return Response(status_code=499)

The real value is that the binding is ambient, so service-layer code doesn't need to know about HTTP, requests, or disconnect events — it reads the cancellation context via get_current_fencing():

# handler — no fencing wiring at the boundary either
@app.get("/generate")
async def handler(prompt: str):
    result = await generate_response(prompt)
    return {"status": "ok", "result": result}

# service layer — no request, no fencing in the signature
async def generate_response(prompt: str) -> str:
    # canceled on timeout or global disconnect event
    with (
        get_current_fencing()
        .timeout(30, code="budget")
        .move_on_cancel()
    ) as fence:
        result = await llm.generate(prompt)

    if fence.cancelled_by("disconnect"):
        return "client disconnected, skipping"
    if fence.cancelled_by("budget"):
        return await get_cached_response(prompt)
    return result

Code with no dependency and no Request to hand can read the event straight from the ambient request:

from aiofence.contrib.starlette import get_disconnect_event

async def deep_helper():
    gone = get_disconnect_event()          # None when the middleware isn't installed

Why this is the hard part

An ASGI receive channel has exactly one useful reader — receive() is a queue pop, not a broadcast — while a request routinely has several interested parties: StreamingResponse's disconnect listener, sse-starlette's, Request.is_disconnected(), and your own code. Three properties make the arbitration correct, and hand-rolled watchers usually miss at least one:

  • One reader, above everything else. On hypercorn, daphne and granian http.disconnect is delivered exactly once, so whoever reads it first consumes it and every other listener starves. A dependency cannot arbitrate — Starlette captures the raw receive before any dependency runs, so there is no reference left to wrap. Only a middleware sits above all of them.

  • Replay, don't discard. The usual watcher loop drops everything that isn't a disconnect, which steals body chunks: the loser of that race gets {"body": b"", "more_body": False}, and Starlette accepts it as a complete, empty body. Silent truncation, no exception, no log. DisconnectMiddleware forwards every message downstream in order and unchanged.

  • "Stream ended" is not "client left". Per the ASGI spec http.disconnect means the stream ended, and every server sends it once the response is complete. A watcher that can't tell the two apart fires on every successful request — and takes BackgroundTasks down with it. The middleware tracks response completion in a wrapped send, so only a disconnect arriving before the response finished sets the event.

Full reasoning in Disconnect Delivery — Design Rationale and Architecture.

Requires starlette (installed with FastAPI). No additional dependencies.

Documentation

Caveats

Nested Fences are not supported. Entering a Fence while another is active on the same task raises RuntimeError. Use sequential fences or get_current_fencing() composition instead. See #12 for details and progress.

The disconnect dependencies require DisconnectMiddleware and raise RuntimeError without it. There is no fallback on purpose — see Why this is the hard part and the API guide.

Requirements

Python 3.12+. No dependencies.

License

MIT

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