Comments (5)
It finally works by doing these steps:
- Deleting every prefect python packages
- Deleting the
.prefect
folder - Reinstalling prefect with
pip3 install -U prefect --pre
note: I didn't used the --pre
to install it earlier.
I now have the latest version of prefect
% prefect version
Version: 3.0.0rc17
API version: 0.8.4
Python version: 3.11.5
Git commit: a2572677
Built: Wed, Aug 14, 2024 11:24 AM
OS/Arch: darwin/arm64
Profile: devtest
Server type: server
Pydantic version: 2.8.2
And the dashboard is reachable!
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Hey @dqueruel-fy!
If you want to get more logging from your local server, you can set PREFECT_LOGGING_SERVER_LEVEL
to DEBUG
either as an environment variable or in your Prefect profile with prefect config set PREFECT_LOGGING_SERVER_LEVEL=DEBUG
. The output from that increased log level will hopefully give us more info about why you aren't able to access the UI of your local server.
from prefect.
Hey @dqueruel-fy !
If you want to get more logging from your local server, you can set
PREFECT_LOGGING_SERVER_LEVEL
toDEBUG
either as an environment variable or in your Prefect profile withprefect config set PREFECT_LOGGING_SERVER_LEVEL=DEBUG
. The output from that increased log level will hopefully give us more info about why you aren't able to access the UI of your local server.
Thanks @desertaxle for the quick answer !
I've tried it but I don't see any difference in the logs. I remember that, when it was working, I add more log/warnings after starting the local server, but now there is no logs at all.
~ % prefect config set PREFECT_LOGGING_SERVER_LEVEL=DEBUG
Set 'PREFECT_LOGGING_SERVER_LEVEL' to 'DEBUG'.
Updated profile 'dev'.
~ % prefect server start
___ ___ ___ ___ ___ ___ _____
| _ \ _ \ __| __| __/ __|_ _|
| _/ / _|| _|| _| (__ | |
|_| |_|_\___|_| |___\___| |_|
Configure Prefect to communicate with the server with:
prefect config set PREFECT_API_URL=http://127.0.0.1:4200/api
View the API reference documentation at http://127.0.0.1:4200/docs
Check out the dashboard at http://127.0.0.1:4200
I've tested it on another port, but I get the same issue:
prefect server start --port 6000
___ ___ ___ ___ ___ ___ _____
| _ \ _ \ __| __| __/ __|_ _|
| _/ / _|| _|| _| (__ | |
|_| |_|_\___|_| |___\___| |_|
Configure Prefect to communicate with the server with:
prefect config set PREFECT_API_URL=http://127.0.0.1:6000/api
View the API reference documentation at http://127.0.0.1:6000/docs
Check out the dashboard at http://127.0.0.1:6000
from prefect.
This is finally due to the combination of prefect
and prefect-ray
. Without prefect-ray
, prefect local server is working properly.
The current setup that is working for me for both prefect
and prefect-ray
is:
prefect
version3.0.0rc10
prefect-ray
versionprefect-ray-0.4.0rc2
(I haven't specified it in pip).
I haven't tried all rc though but the latest ones rc17, rc18 seems to have issues with prefect-ray
from what I have tested.
from prefect.
Interesting! I can also reproduce with the most recent RC versions of prefect
and prefect-ray
. I suspect this has something to do with prefect-ray
misbehaving when we load integrations.
from prefect.
Related Issues (20)
- Work queue concurrency limit not working (as expected)
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- Make Flow Version Available in the Runtime HOT 1
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- Generic Secure Block HOT 4
- Task hangs due to multiprocessing.Pool.join() HOT 1
- PREFECT_API_URL not recognized even though it is set HOT 5
- Serializable isolation level for transactions
- Error on KubernetesJob.publish_as_work_pool()
- Cannot pass dict as a parameter 'data' to Completed state on Prefect v3.0.0rc16 HOT 4
- flow.to_deployment().serve() does not work HOT 4
- Deployment Concurrency Limits HOT 2
- Add json serializer for tasks that return a pydantic model
- flow run execute with wrong order when lower priority queue contain many flow runs HOT 2
- Add volume configuration in worker.json HOT 3
- K8s worker fails monitoring flow and sets it to crashed.
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