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Graph/blocking-io-in-async

AntiPattern

Blocking Async Operations

blocking-io-in-async

Blocking calls inside async code—thread sleeps, synchronous HTTP libraries, or awaiting a coroutine-returning mock—freeze the event loop or break async context handling, so other tasks don’t progress and tests/reporting become misleading.

Node Details

Public graph metadata

Updated7/13/2026

Connections

30 linked nodes

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.

MATCHESSolution

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

use httpx or aiohttp e.g: — async def test_api(request: Request):. Tension: requests(which is synchronous) inside async function. Outcome: async with client.stream("POST", "http://127.0.0.1:8000/test_api",json={} ) as response: async for chunk in response.aiter_bytes(chunk_size=1234): yield chunk.

MATCHESSolution

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

MATCHESSolution

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.

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

use `pytest_asyncio` and the async fixture — If you don't want to utilize an `AsyncClient` like the one by `httpx`. Tension: ensuring that the FastAPI app's lifespan context correctly works.

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

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

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

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

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

How can I get hold of the query metrics in this async setup? — The Couchbase documentation mentions to switch to the Reactive and Async APIs. Tension: the blocking API is really just a wrapper: it contains both the rows and the metadata (including metrics). In the reactive API this is split. Outcome: you can also call `result.metaData()` to access metrics, warnings, and the rest of the metadata.

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

future.cancel(true); — httpHardTimeoutScheduler.schedule(() -> {. Tension: if (!future.isDone() && !future.isCancelled()). Outcome: keep your latency low on your side of the wire.

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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