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QUESTION
I want to install packages from poetry.lock
file; using poetry install
.
However, the majority of packages throw the exact same error, indicating a shared fundamental problem.
What is causing this? What is the standard fix?
Specification:
- Windows 10,
- Visual Studio Code,
- Python 3.8.10 & Poetry 1.1.11,
- Ubuntu Bash.
Terminal:
rm poetry.lock
poetry update
poetry install
ANSWER
Answered 2022-Mar-23 at 10:22This looks to be an active issue relating to poetry. See here - Issue #4085. Some suggest a workaround by downgrading poetry-core
down to 1.0.4.
There is an active PR to fix the issue.
QUESTION
I just switched from ForkPool to gevent with concurrency (5) as the pool method for Celery workers running in Kubernetes pods. After the switch I've been getting a non recoverable erro in the worker:
amqp.exceptions.PreconditionFailed: (0, 0): (406) PRECONDITION_FAILED - delivery acknowledgement on channel 1 timed out. Timeout value used: 1800000 ms. This timeout value can be configured, see consumers doc guide to learn more
The broker logs gives basically the same message:
2021-11-01 22:26:17.251 [warning] <0.18574.1> Consumer None4 on channel 1 has timed out waiting for delivery acknowledgement. Timeout used: 1800000 ms. This timeout value can be configured, see consumers doc guide to learn more
I have the CELERY_ACK_LATE
set up, but was not familiar with the necessity to set a timeout for the acknowledgement period. And that never happened before using processes. Tasks can be fairly long (60-120 seconds sometimes), but I can't find a specific setting to allow that.
I've read in another post in other forum a user who set the timeout on the broker configuration to a huge number (like 24 hours), and was also having the same problem, so that makes me think there may be something else related to the issue.
Any ideas or suggestions on how to make worker more resilient?
...ANSWER
Answered 2022-Mar-05 at 01:40For future reference, it seems that the new RabbitMQ versions (+3.8) introduced a tight default for consumer_timeout
(15min I think).
The solution I found (that has also been added to Celery docs not long ago here) was to just add a large number for the consumer_timeout
in RabbitMQ.
In this question, someone mentions setting consumer_timeout to false, in a way that using a large number is not needed, but apparently there's some specifics regarding the format of the configuration for that to work.
I'm running RabbitMQ in k8s and just done something like:
QUESTION
I was using pyspark on AWS EMR (4 r5.xlarge as 4 workers, each has one executor and 4 cores), and I got AttributeError: Can't get attribute 'new_block' on . Below is a snippet of the code that threw this error:
...
ANSWER
Answered 2021-Aug-26 at 14:53I had the same error using pandas 1.3.2 in the server while 1.2 in my client. Downgrading pandas to 1.2 solved the problem.
QUESTION
I have the following 2 query plans for a particular query (second one was obtained by turning seqscan off):
The cost estimate for the second plan is lower than that for the first, however, pg only chooses the second plan if forced to do so (by turning seqscan off).
What could be causing this behaviour?
EDIT: Updating the question with information requested in a comment:
Output for EXPLAIN (ANALYZE, BUFFERS, VERBOSE)
for query 1 (seqscan on; does not use index). Also viewable at https://explain.depesz.com/s/cGLY:
ANSWER
Answered 2022-Feb-17 at 11:43You should have those two indexes to speed up your query :
QUESTION
Question in short
I have migrated my project from Django 2.2 to Django 3.2, and now I want to start using the possibility for asynchronous views. I have created an async view, setup asgi configuration, and run gunicorn with a Uvicorn worker. When swarming this server with 10 users concurrently, they are served synchronously. What do I need to configure in order to serve 10 concurrent users an async view?
Question in detail
This is what I did so far in my local environment:
- I am working with Django 3.2.10 and Python 3.9.
- I have installed
gunicorn
anduvicorn
through pip - I have created an
asgi.py
file with the following contents
ANSWER
Answered 2022-Feb-06 at 21:43When running the gunicorn
command, you can try to add workers
parameter with using options -w
or --workers
.
It defaults to 1
as stated in the gunicorn documentation. You may want to try to increase that value.
Example usage:
QUESTION
I'm working on a React Native application. My Android builds began to fail in the CI environment (and locally) without any changes.
...ANSWER
Answered 2021-Sep-03 at 11:46Go to your package.json file and delete as many dependencies as you can until the project builds successfully. Then start adding back the dependencies one by one to detect which ones have troubles.
Then you can manually patch those dependencies by acceding them on node_modules/[dependencie]/android/build.gradle and setting androidx.core:core-ktx: or androidx.core:core: to a specific version (1.6.0 in my case).
QUESTION
Herb Sutter, in his "atomic<> weapons" talk, shows several example uses of atomics, and one of them boils down to following: (video link, timestamped)
A main thread launches several worker threads.
Workers check the stop flag:
...
ANSWER
Answered 2022-Jan-05 at 14:48mo_relaxed
is fine for both load and store of a stop
flag
There's also no meaningful latency benefit to stronger memory orders, even if latency of seeing a change to a keep_running
or exit_now
flag was important.
IDK why Herb thinks stop.store
shouldn't be relaxed; in his talk, his slides have a comment that says // not relaxed
on the assignment, but he doesn't say anything about the store side before moving on to "is it worth it".
Of course, the load runs inside the worker loop, but the store runs only once, and Herb really likes to recommend sticking with SC unless you have a performance reason that truly justifies using something else. I hope that wasn't his only reason; I find that unhelpful when trying to understand what memory order would actually be necessary and why. But anyway, I think either that or a mistake on his part.
The ISO C++ standard doesn't say anything about how soon stores become visible or what might influence that, just Section 6.9.2.3 Forward progress
18. An implementation should ensure that the last value (in modification order) assigned by an atomic or synchronization operation will become visible to all other threads in a finite period of time.
Another thread can loop arbitrarily many times before its load actually sees this store value, even if they're both seq_cst
, assuming there's no other synchronization of any kind between them. Low inter-thread latency is a performance issue, not correctness / formal guarantee.
And non-infinite inter-thread latency is apparently only a "should" QOI (quality of implementation) issue. :P Nothing in the standard suggests that seq_cst
would help on an implementation where store visibility could be delayed indefinitely, although one might guess that could be the case, e.g. on a hypothetical implementation with explicit cache flushes instead of cache coherency. (Although such an implementation is probably not practically usable in terms of performance with CPUs anything like what we have now; every release and/or acquire operation would have to flush the whole cache.)
On real hardware (which uses some form of MESI cache coherency), different memory orders for store or load don't make stores visible sooner in real time, they just control whether later operations can become globally visible while still waiting for the store to commit from the store buffer to L1d cache. (After invalidating any other copies of the line.)
Stronger orders, and barriers, don't make things happen sooner in an absolute sense, they just delay other things until they're allowed to happen relative to the store or load. (This is the case on all real-world CPUs AFAIK; they always try to make stores visible to other cores ASAP anyway, so the store buffer doesn't fill up, and
See also (my similar answers on):
- Does hardware memory barrier make visibility of atomic operations faster in addition to providing necessary guarantees?
- If I don't use fences, how long could it take a core to see another core's writes?
- memory_order_relaxed and visibility
- Thread synchronization: How to guarantee visibility of writes (it's a non-issue on current real hardware)
The second Q&A is about x86 where commit from the store buffer to L1d cache is in program order. That limits how far past a cache-miss store execution can get, and also any possible benefit of putting a release or seq_cst fence after the store to prevent later stores (and loads) from maybe competing for resources. (x86 microarchitectures will do RFO (read for ownership) before stores reach the head of the store buffer, and plain loads normally compete for resources to track RFOs we're waiting for a response to.) But these effects are extremely minor in terms of something like exiting another thread; only very small scale reordering.
because who cares if the thread stops with a slightly bigger delay.
More like, who cares if the thread gets more work done by not making loads/stores after the load wait for the check to complete. (Of course, this work will get discarded if it's in the shadow of a a mis-speculated branch on the load result when we eventually load true
.) The cost of rolling back to a consistent state after a branch mispredict is more or less independent of how much already-executed work had happened beyond the mispredicted branch. And it's a stop
flag so the total amount of wasted work costing cache/memory bandwidth for other CPUs is pretty minimal.
That phrasing makes it sound like an acquire
load or release
store would actually get the the store seen sooner in absolute real time, rather than just relative to other code in this thread. (Which is not the case).
The benefit is more instruction-level and memory-level parallelism across loop iterations when the load produces a false
. And simply avoiding running extra instructions on ISAs where an acquire or especially an SC load needs extra instructions, especially expensive 2-way barrier instructions, not like ARM64 ldapr
.
BTW, Herb is right that the dirty
flag can also be relaxed
, only because of the thread.join
sync between the reader and any possible writer. Otherwise yeah, release / acquire.
But in this case, dirty
only needs to be atomic<>
at all because of possible simultaneous writers all storing the same value, which ISO C++ still deems data-race UB. e.g. because of the theoretical possibility of hardware race-detection that traps on conflicting non-atomic accesses.
QUESTION
I got this issue
...ANSWER
Answered 2022-Jan-03 at 14:37Solved downgrading to the nov 2021 version of opencv
QUESTION
I have the following code that runs two TensorFlow trainings in parallel using Dask workers implemented in Docker containers.
I need to launch two processes, using the same dask client, where each will train their respective models with N workers.
To that end, I do the following:
- I use
joblib.delayed
to spawn the two processes. - Within each process I run
with joblib.parallel_backend('dask'):
to execute the fit/training logic. Each training process triggers N dask workers.
The problem is that I don't know if the entire process is thread safe, are there any concurrency elements that I'm missing?
...ANSWER
Answered 2021-Dec-24 at 05:12This is pure speculation, but one potential concurrency issue is due to if client is None:
part, where two processes could race to create a Client
.
If this is resolved (e.g. by explicitly creating a client in advance), then dask
scheduler will rely on time of submission to prioritize task (unless priority
is clearly assigned) and also the graph (DAG) structure, there are further details available in docs.
QUESTION
I'm working on a react PWA using Firebase services. By PWA I mean it uses service workers, has Firestore offline data persistence enabled, and is supposed to log the user in as long as the session data is stored in the browser.
The problem I'm having is after a user is authenticated, I want the user to be able to turn off wifi and mobile data, and be able to open the app again, and the app treat the user like the user is authenticated. This all works fine on desktop browsers Chrome, and Firefox. (For some reason not on Safari)
However, when I use the latest Chrome and Firefox mobile browsers, the service workers work well but after turning off wifi an mobile data, the app doesn't treat the user like they are logged in and a error message in the console appears that reads "inner auth error". It unfortunately doesn't give much more information than that.
To check for a user I'm using the onAuthStateChanged listener in my App.tsx like this:
...ANSWER
Answered 2021-Dec-28 at 09:04This error is occurring because if getAuth() is called or initializeAuth is defined with the browserPopupRedirectResolver, it will error on mobile and in Safari when offline. You can read how to fix it here: https://github.com/firebase/firebase-js-sdk/issues/5529
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