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Graph/deadlock-and-lock-ordering-mismanagement

AntiPattern

Locking and Deadlocks

deadlock-and-lock-ordering-mismanagement

Thread coordination fails because code holds multiple locks (or releases/holds them at the wrong times), so competing tasks wait on each other until deadlock or stalled progress occurs despite async/event-loop design.

Node Details

Public graph metadata

Updated7/6/2026

Connections

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 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

I suggests you use rapyer, Which takes special care to handle deadlock problems. — Since you are using json models. Tension: deadlock problems.

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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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.

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.

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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.

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

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

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

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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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In general this calls for a mutex. — If the language does not provide mutexes out of the box. Outcome: you can create a mutex.

MATCHESSolution

if all you're trying to do is share something between multiple threads — consider using `Arc` instead. Outcome: this implements a thread-safe reference counted smart pointer.

MATCHESSolution

Cause of the deadlock.

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

Your code doesn't use any shared state (or even objects) between the different threads — running this code in a multithreaded environment. Tension: The only thing that may looks marignally relevant is calling the static `OPCPackage.open` method. Outcome: there shouldn't be any problem running this code in a multithreaded environment.

MATCHESSolution

use a set to define which are currently running, and remove from set at end rather than before calling `process(client)` — You could use a counter (AtomicInteger) instead of `HashSet`, or `Semaphore`. Tension: your locks don't prevent more than MAX_THREAD_POOL running threads at once. Outcome: which is intended for this type of use.

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

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

Use synchronization primitives, locks, or other publication mechanisms that establish a happens-before between the write and subsequent read

MATCHESSolution

Mysql driver 9.0.0+ (currently 9.1.0) has ReentrantLock(s) now — IF they were not hooked on mysql internal synchronized blocks. Tension: it should have helped. Outcome: and it should work as this enabled the virtual thread to go do something else.

MATCHESSolution

Only if all threads of your program use `seq_cst` memory order for operations and fences. — The C++ guarantee of sequential consistency for data-race free programs only applies if all atomic operations are `seq_cst`, or if you use equivalent fences. Tension: One thread using a fence can't necessarily recover sequential consistency when other threads are using `relaxed` or `release` and `acquire` operations on `std::atomic`. Outcome: use `seq_cst` memory order for operations and fences.

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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