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Graph/event-loop-blocking-misuse

AntiPattern

Event Loop Blocking Misuse

event-loop-blocking-misuse

Blocking or mis-wired async work (e.g., time.sleep in async code, async DB mocks returning coroutines, or calling blocking subprocess/run directly) prevents the event loop from progressing, causing hangs, missing awaits, or test/runtime failures.

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Updated6/23/2026

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30 linked nodes

MATCHESSolution

handle a scenario when the code is fine but backend went offline — prefetching data with usePrefetchQuery. Tension: prefetch works.

MATCHESSolution

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.

MATCHESSolution

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.

MATCHESSolution

delete the async from `fake_execute` — your `AsyncContextMock` needs to handle both use cases in your endpoint `await conn.execute()` and `async with conn.execute()`. Outcome: just make it a regular function so it returns your context manager directly, no coroutine wrapper.

MATCHESSolution

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

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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:.

MATCHESSolution

Using a `session-scoped` pytest fixture, for managing the event loop — which ensures the same event loop will be used. Outcome: loop.close().

MATCHESSolution

I also offer an alternative `executor` class which can preserve the contextvar values across threads — when YOUR code is the one making the `loop.run_in_executor` call. Tension: in this example, the code making this is the framework code. Outcome: but that can only be used when YOUR code is the one making the `loop.run_in_executor` call.

MATCHESSolution

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.

MATCHESSolution

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.

MATCHESSolution

using `magicmock` to mock it could lead to unusual or unexpected behavior when checking for call counts — Since `get_item` might be an asynchronous function in your middleware. Tension: using `magicmock` to mock it could lead to unusual or unexpected behavior. Outcome: which is designed to work with async functions.

MATCHESSolution

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.

MATCHESSolution

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.

MATCHESSolution

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.

MATCHESSolution

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

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.

MATCHESSolution

bound it with a "progress ceiling" — a process emitting bytes but making NO semantic progress. Tension: a process emitting bytes but making NO semantic progress (livelock) would be shielded forever. Outcome: re-arms recovery after a long no-progress window even while bytes flow.

MATCHESSolution

An async function was passed to useActionState.

MATCHESSolution

Do not use `Thread.stop()`. Tension: you need to really validate your assumptions of what is possible in your complicated code base.

MATCHESSolution

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.

MATCHESSolution

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

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

I am seeing an increase in latencies in requests that do succeed — I have a logic of the sort :. Tension: none of them enforce a timeout on the total duration of the request. Outcome: Then properly close the connection in a finally / try-resource block.

MATCHESSolution

adding a pause to your task after connecting — You can also use a 'sleep(delay)' in mysql, to make statements last longer. Tension: to prove your tasks can make parallel statements. Outcome: You'll have time to show processlist by hand now.

MATCHESSolution

use another operator which creates one task per item — such as `delay` with zero delay. Tension: to get a better interleaving. Outcome: subject1.delay(0, TimeUnit.MILLISECONDS, scheduler).subscribe(log::info);.

MATCHESSolution

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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