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.
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 / FalseOr raise instead of inspect:
with on_timeout(30).raise_on_cancel() as fence:
result = await fetch_and_transform()
# raises FenceCancelled if timed outshield() 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 neededanyio 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:
-
Drop-in for existing asyncio code.
anyiobuilds 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, adoptinganyiois a significant migration.aiofenceworks directly with asyncio'scancel()/uncancel()counter protocol — no new runtime, no new cancellation model. If asyncio evolves its cancellation primitives,aiofencestays compatible. -
Different design philosophy.
anyio's approach is a broadCancelScopeover the whole operation, withCancelScope(shield=True)around the parts that must survive.aiofencetakes the inverse: most code runs unaware of cancellation, and you wrap only the expensive, safely-interruptible parts with aFence.
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_resultNative asyncio — works with asyncio's cancel()/uncancel() counter protocol. Compatible with TaskGroup, asyncio.timeout(). No new runtime, no dependencies.
disconnect_fencing binds a client-disconnect trigger to the current Fencing context via bind_fencing(). When the client disconnects, any active Fence — anywhere in the call stack — is cancelled with code="disconnect":
from aiofence.contrib.starlette import disconnect_fencing
@app.get("/work")
async def handler(fencing: Fencing = Depends(disconnect_fencing)):
with fencing.timeout(30, code="budget").move_on_cancel() as fence:
await long_work()
if fence.cancelled_by("disconnect"):
return Response(status_code=499)The real value is that disconnect_fencing calls bind_fencing() internally, so service-layer code doesn't need to know about HTTP, requests, or disconnect events — it reads the cancellation context via get_current_fencing():
from aiofence.contrib.starlette import disconnect_fencing
# handler — declares cancellation sources at the boundary
@app.get("/generate")
async def handler(
prompt: str,
_ = Depends(disconnect_fencing),
):
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 resultRequires starlette (installed with FastAPI). No additional dependencies.
- API Guide — usage, patterns, and examples
- Architecture — how it works, cancellation flow, design decisions
- Why Suppress — why
CancelledErroris suppressed instead of raised - CPython Task Cancellation — how
asyncio.Taskcancellation works under the hood
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.
Python 3.12+. No dependencies.
MIT