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Graph/blocking-calls-timeout-misinterpretation

AntiPattern

Blocking Sleep/Requests Misleads Timeouts

blocking-calls-timeout-misinterpretation

Blocking calls (time.sleep, synchronous requests, or overly trusting measured wait_for time) make concurrency and timeout handling look correct while underlying tasks are stalled or mis-attributed, causing async work to be committed as pending and retries/enqueues to proceed incorrectly.

Node Details

Public graph metadata

Updated7/27/2026

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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.

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Use a cleanup function to clear the timeout, or simulate latency with Chrome DevTools throttling or MSW delay instead

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Prevent or debounce user interactions until hydration completes — before hydration completes. Tension: especially in slow networks.

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maybe you can swap your post to axios, because it has a timeout property — if you only want to do this once. Tension: some requests take too long to download content (about a minute). Outcome: can you in anyway batch your requests, so you are sending more requests in order to receive smaller responses?

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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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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

Disable this feature altogether — On this page you'll see how to change the configuration values or to disable it programatically or via the Sentry editor configuration window. Tension: the screen can be blocked for upwards of 9 seconds. Outcome: Increase the timeout to, say 12 or 15 seconds.

MATCHESSolution

try reducing Sentry's http_connect_timeout and http_timeout options — If you do need it, and slow connections happen randomly. Tension: slow connections happen randomly. Outcome: Sentry\init([ 'http_connect_timeout' => 2, // The default is two seconds. 'http_timeout' => 5 // Reduce these values and test if Sentry still sends events. ]);.

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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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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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Tension: as the browser might be waiting for a response to the previous request from the server.

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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.

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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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making sure you pace your requests to stay below those limits — API rate limits. Tension: allowing room for your normal operations, too. Outcome: handle any 429 responses gracefully to retry.

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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.

MATCHESSolution

Increasing the timeout, pool size and pooling in the connection string helped in my case. — I faced the same issue where the first connection attempt or a connection after a longer period would immediately time out. Outcome: I added these parameters: `Timeout=60;Command Timeout=60;Pooling=true;MinPoolSize=1;MaxPoolSize=200`.

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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

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.

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catch(TimeoutException | UnhandledAlertException e) — I was able to make the test pass with this code. Tension: I have to wait 160 seconds for the timeout to be thrown. Outcome: result = true;.

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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.

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Check the actual time spent in `wait_for` — If it is significantly more than what you asked for. Tension: assume the system slept and ignore the flag. Outcome: Check the actual time spent in `wait_for`. If it is significantly more than what you asked for, assume the system slept and ignore the flag.

MATCHESSolution

If you start the server and wait several minutes before visiting any pages — does it still take several minutes for that first page? Tension: long startup in general or something request specific. Outcome: Figuring out if it is a long startup in general or something request specific could be a good spot to start.

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Fixed 30s retry on 429 keeps hammering. — when clearly rate-limited. Tension: keeps hammering. Outcome: Exponential backoff + hard rejection during cooldown.

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

The correct approach is to use standardized methods — to ensure reliable and consistent timing measurements across different server setups. Tension: inaccurate latency metrics. Outcome: tracking the start time using `Date.now()` at the moment the request is received.

MATCHESSolution

Fix the integral controller's anti-windup guards — The budget nudge-up fired on `tokensUsedInWindow > 0 && consecutive429s === 0`. Tension: a freshly-restarted proxy with one request satisfies this immediately. Outcome: Gate budget increases on: - Minimum traffic duration (e.g. 1 hour of history) - Minimum budget consumption (e.g. 5%+ used) - No 429s in recent window.

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