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Graph/event-loop-blocking

AntiPattern

Async Work Blocks Event Loop

event-loop-blocking

Blocking calls (sleeping, subprocess waits, or thread-lock contention) run inside async handlers so the event loop can’t make progress; exceptions propagate through callbacks, and timing assumptions break when wait flags are ignored.

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Public graph metadata

Updated6/26/2026

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30 linked nodes

MATCHESSolution

you can use Zustand getters and optimistic update — multiple or rapid clicks could actually cause the updates to be executed but out of order. Tension: no optimistic update so u see that delay (lag) you said about.

MATCHESSolution

Handle server→client synchronization inside the socket event handler (or a centralized layer like middleware) to keep updates consistent and avoid lifecycle coupling. Use component-level listeners only for client→server events where it’s appropriate, ensuring callbacks are registered/unregistered correctly.

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Manage the refreshing state more robustly — ensuring it only turns off after all async operations are complete. Tension: remove the arbitrary timeout. Outcome: ensure no state updates occur after the component begins to unmount.

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Wrap updates that suspend with startTransition

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As long as you lock more than a single thing at a time, you risk deadlocks. — lock more than a single thing at a time. Tension: You hold B waiting for A, they hold A waiting for B. Outcome: one of you has to abort or you're stuck.

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You can configure your worker with a Workflow interceptor — Temporal workflows and activities. Tension: we don't have Sentry logging anymore. Outcome: catch all exception raised during your activities and workflow execution.

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single worker running async loop. Outcome: So you have a single worker running async loop and you block that loop.

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Keep the websocket handler running with a receive loop after accept()

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If you convert all operations to perform asynchronously (using `aiosqlite`) , the issue will be mitigated. — When a route in FastAPI is listed as asynchronous (`async def`). Tension: that doesn't fully solve the inherent single writer problem of Sqlite. Outcome: Here's a fully operational update of the FastAPI server logic:.

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To manage background processes. Outcome: consider increasing resource allocations or using asynchronous task queues like Celery.

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python interpreter just pauses one task and looks at other — In your scenerio where you use asynchronous. Tension: it is not completly usesless. Outcome: Think it like a round-robin.

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Change the engine async fixture from session scope to function scope (remove scope="session") so all async fixtures/tests run on the same event loop, preventing the cross-loop Future/Task error.

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Using `asyncio.sleep()` in a loop is perfectly fine. Tension: every time you `await` the sleep, you effectively yield control back to the event loop. Outcome: calling `asyncio.sleep(0)` does not sleep at all, but only yields control back to the event loop.

MATCHESSolution

the reason for the various threads appearing in the logs — when you pass a synchronous generator to `EventSourceResponse`. Tension: a normal `def` function instead of `async def`. Outcome: please take a look at the implementation of the `EventSourceResponse` class.

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Ensure the server yields to the asyncio event loop while processing (e.g., add an `await asyncio.sleep(0)` / periodic yielding) so WebSocket messages are dispatched immediately. Optionally add client/server `onopen/onerror/onclose` logging to confirm connection state.

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any time you have an I/O bound process with lots of idle time — waiting for user input, waiting for a TLS handshake. Tension: wrapping it in an async task can let other code run.

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Initialize Eureka using the async API (e.g., `eureka_client.init_async(...)`) and/or move initialization into an appropriate async startup hook so it doesn’t start a new event loop at import time.

MATCHESSolution

Handle each relevant webhook event separately according to Stripe’s documentation (including `checkout.session.async_payment_succeeded` if you use async payment methods) rather than assuming `checkout.session.completed` is a universal catch-all. Fix the switch logic by adding `break` (or restructuring cases) so `checkout.session.completed` does not fall through to the `checkout.session.async_payment_failed` logic.

MATCHESSolution

a way to do that is an async function. Tension: first awaits `initialize payment` and then awaits the `handlePay`.

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Ensure the S3 download runs in a way that doesn’t block the event loop (i.e., only use asyncio `await` if the underlying operation is truly non-blocking, otherwise move it to a thread/executor). Use `asyncio.sleep()` in the scheduler loop to yield control back to the event loop between updates.

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An async function was passed to useActionState.

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Or you can use `async/await` and `try/catch` — createAsyncThunk. Outcome: return data.

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Avoid running multiple DB operations concurrently on the same session by removing asyncio.gather and iterating sequentially, and/or use an async_scoped_session so each task uses its own session.

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Use virtual threads for blocking DB/IO work to improve scalability under the same small pool, or switch to a reactive database driver/event-loop model to avoid blocking carrier threads; adjust concurrency/throttling accordingly (semaphore/backpressure) rather than assuming the current JDBC + thread pool design remains optimal.

MATCHESSolution

Try to to decouple thread creation from task execution. — The CPU maintains a queue and a pool of worker threads (only 3). Tension: Clients submit tasks (like your cpu.execute()). Outcome: Each worker takes a task from the queue, processes it, and picks the next.

MATCHESSolution

Use asynchronous sending with callbacks. — If you're using KafkaTemplate.send() without handling the ListenableFuture returned. Tension: you're effectively blocking the calling thread until the message is acknowledged by the Kafka broker. Outcome: The addCallback method allows you to execute code when the send operation succeeds or fails, without blocking the main thread.

MATCHESSolution

There are workarounds, depending on your usecase — calling `.notify_one()` / `.notify_all()` on a destructed `std::atomic`. Tension: There is a C++ Paper - P2616R4 - which would fix this problem. Outcome: using `std::binary_semaphore` delegating `.wait()` and `.notify_xxx()` to a separate atomic variable that has a longer lifetime manually call the futex syscalls and bypass the stdlib.

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Rewrite the test as an async test and run it with an async test runner (e.g., pytest.mark.asyncio), using await on the async ORM methods (acreate/acount) instead of asyncio.run().

MATCHESSolution

the goroutine blocks forever on the channel send because nobody is reading — When the parent context is cancelled, the goroutine blocks forever on the channel send because nobody is reading. Tension: if the result is ready at the exact moment the context cancels, which case fires?

MATCHESSolution

Use Component.Task (TaskSource) for all async work inside components — inside components. Tension: it auto-cancels when the component is destroyed.

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