Icon doesn't show when enter new page via router and hover on the block

Dynamic icon shows when fresh the page, but doesn't show on new paged entered via router

Please fix this, as you should be provide a delay option or some similar thing, the default theme switch animation is greater then 100ms.
@Snippetors I will remove your plugin from awesome list if this is still not fixed in 2022/6/22. vuepress-plugin-copy-code2 could be a demo.

@Mister-Hope Thank you for reminding, and we noticed that we need to refactor the plugins for the breaking changes introduced in 2.0.0-beta.40. It may take some time but we will try our best to fix it in time.

It's not related to the breaking changes, your plugin is not working in lower versions of vuepress. Themes may have a switch animation, so you should delay your querySeletor after the dom is changed, so you will need a delay option.

@Mister-Hope thank you for your explanation. Yes, I was just wondering if I should also refactor the plugins with the fix to fit the latest breaking changes, or just have the dependency to vuepress fixed to 2.0.0-beta.25 for now.
So let me fix the bug first, then I will refactor the plugins a little bit in another PR to catch the latest version of vuepess.

@Mister-Hope The bug has been fixed in #57 , and the new version 1.1.3 has been released, please take a look when you have time


Check if indexed RAM bundle and loadFromString

Closing this, since we have a PR open in React Native repo itself.


Dask annotations not working when connecting to an existing cluster

I have noticed that Prefect does not respect the dask resources annotations when using an existing cluster
Minimal reproducible example:
I have setup a local distributed cluster like this:
First I spin up a local scheduler:
dask scheduler

And then I start 2 workers. The 1st one has 1 thread and 1 "annotation" resource available and the other one has 3 threads and no specified special resources available:
dask worker --nthreads '1' --resources "annotation=1"  tcp://<IP_ADDRESS>:8786 --name special_worker

&
dask worker --nthreads '3'  tcp://<IP_ADDRESS>:8786 --name only_regular_tasks

Suppose we have the following flow that gets executed 6 times and submits to Dask its tasks for execution:
#!/usr/bin/env python3
import dask
from prefect import flow, task
from prefect_dask.task_runners import DaskTaskRunner
from time import sleep

@task
def show_number(x: int):
    print(x)

@task
def say_hello():
    print("Hello!")
    sleep(4)

@flow(task_runner=DaskTaskRunner(address="tcp://<IP_ADDRESS>:8786"))
def example_flow(x):
    show_number.submit(x)
    with dask.annotate(resources={'annotation': 1}):
        say_hello.submit()

if __name__ == "__main__":
    for i in range(6):
        example_flow(i)

I would expect  say_hello() tasks to execute only on the special_worker  and the show_number() tasks to whichever available.
However this is not the case and I get:
On the 1st special worker:
dask worker --nthreads '1' --resources "annotation=1"  tcp://<IP_ADDRESS>:8786 --name special_worker
2022-11-02 01:40:21,707 - distributed.nanny - INFO -         Start Nanny at: 'tcp://<IP_ADDRESS>:40111'
2022-11-02 01:40:21,911 - distributed.worker - INFO -       Start worker at:   tcp://<IP_ADDRESS>:38027
2022-11-02 01:40:21,911 - distributed.worker - INFO -          Listening to:   tcp://<IP_ADDRESS>:38027
2022-11-02 01:40:21,911 - distributed.worker - INFO -           Worker name:             special_worker
2022-11-02 01:40:21,911 - distributed.worker - INFO -          dashboard at:         <IP_ADDRESS>:44211
2022-11-02 01:40:21,911 - distributed.worker - INFO - Waiting to connect to:    tcp://<IP_ADDRESS>:8786
2022-11-02 01:40:21,911 - distributed.worker - INFO - -------------------------------------------------
2022-11-02 01:40:21,911 - distributed.worker - INFO -               Threads:                          1
2022-11-02 01:40:21,911 - distributed.worker - INFO -                Memory:                   1.92 GiB
2022-11-02 01:40:21,911 - distributed.worker - INFO -       Local Directory: /tmp/dask-worker-space/worker-5zbq1zho
2022-11-02 01:40:21,911 - distributed.worker - INFO - -------------------------------------------------
2022-11-02 01:40:21,915 - distributed.worker - INFO -         Registered to:    tcp://<IP_ADDRESS>:8786
2022-11-02 01:40:21,915 - distributed.worker - INFO - -------------------------------------------------
2022-11-02 01:40:21,916 - distributed.core - INFO - Starting established connection
0
Hello!
Hello!
3
Hello!
Hello!

On the 2nd only_regular_tasks worker:
dask worker --nthreads '3'  tcp://<IP_ADDRESS>:8786 --name only_regular_tasks
2022-11-02 01:40:44,071 - distributed.nanny - INFO -         Start Nanny at: 'tcp://<IP_ADDRESS>:37631'
2022-11-02 01:40:44,271 - distributed.worker - INFO -       Start worker at:   tcp://<IP_ADDRESS>:41407
2022-11-02 01:40:44,271 - distributed.worker - INFO -          Listening to:   tcp://<IP_ADDRESS>:41407
2022-11-02 01:40:44,271 - distributed.worker - INFO -           Worker name:         only_regular_tasks
2022-11-02 01:40:44,271 - distributed.worker - INFO -          dashboard at:         <IP_ADDRESS>:43921
2022-11-02 01:40:44,271 - distributed.worker - INFO - Waiting to connect to:    tcp://<IP_ADDRESS>:8786
2022-11-02 01:40:44,271 - distributed.worker - INFO - -------------------------------------------------
2022-11-02 01:40:44,271 - distributed.worker - INFO -               Threads:                          3
2022-11-02 01:40:44,271 - distributed.worker - INFO -                Memory:                   5.76 GiB
2022-11-02 01:40:44,271 - distributed.worker - INFO -       Local Directory: /tmp/dask-worker-space/worker-b0x7pdsc
2022-11-02 01:40:44,271 - distributed.worker - INFO - -------------------------------------------------
2022-11-02 01:40:44,276 - distributed.worker - INFO -         Registered to:    tcp://<IP_ADDRESS>:8786
2022-11-02 01:40:44,276 - distributed.worker - INFO - -------------------------------------------------
2022-11-02 01:40:44,276 - distributed.core - INFO - Starting established connection
Hello!
1
2
Hello!
4
5

As you can see the say_hello() tasks are getting executed on the 2nd worker that does not have the appropriate --resources "annotation=1" available
Relevant versions used in a Python 3.10 env: prefect==2.6.5, prefect-dask==0.2.1, dask==2022.10.2, distributed==2022.10.2

Ah this used to work and was the intended way to use annotations. I think this may be caused by https://github.com/PrefectHQ/prefect/pull/6527 — it'll require further investigation though.

@madkinsz I also encountered this while using dask_kubernetes to create dask cluster. some tasks have their correct annotations and others don't have any. it seems like there is a problem with the context manager

We made an optimization to task submission but that means that tasks are submitted in the background now, which means that submission can actually occur outside of the context. I'm working on a fix.

@madkinsz do you mind sharing the PR? I'd like to keep track of this issue and provide help if needed

I just encountered this issue as well. I am using this config for the DaskTaskRunner:
cluster_class="dask_jobqueue.SLURMCluster",
    cluster_kwargs={
        "account": "...",
        "queue": "...",
        "cores": 5,
        "processes": 1,
        "memory": "5 GB",
        "walltime": "24:00:00",
        "worker_extra_args": [
            "--resources TEST=1",
        ],
    }

And then submit task with:
with dask.annotate(resources={"TEST": 1}):
    for i in range(10):
        task.submit(i)

This executes 5 tasks simultaneously on the same worker. As far as I can tell the limiting factor is the number of cores. Because if I set "cores": 1 only a single task is submitted at a time.

Also experiencing this problem with temporary clusters on ECS. Workers can be started with resources configures as @tibuch showed with worker_extra_args in the cluster_kwargs e.g.
"worker_extra_args": [ "--resources", "MEMORY=4098"]

But using with dask.annotate(resources={"MEMORY": 4098}): doesn't prevent multiple tasks being submitted to workers.

Hi @andreas-ntonas, thank you for the very detailed reproduction steps.
I'm working on reproducing this issue, but in my testing with the latest prefect and prefect-dask, I'm not able to reproduce this, and I believe I'm seeing the behavior you were expecting.
On the special worker:
$ dask worker --nthreads '1' --resources "annotation=1"  tcp://<IP_ADDRESS>:8786 --name special_worker
2023-09-13 15:57:23,709 - distributed.nanny - INFO -         Start Nanny at: 'tcp://<IP_ADDRESS>:35097'
2023-09-13 15:57:23,927 - distributed.worker - INFO -       Start worker at:     tcp://<IP_ADDRESS>:34437
2023-09-13 15:57:23,927 - distributed.worker - INFO -          Listening to:     tcp://<IP_ADDRESS>:34437
2023-09-13 15:57:23,927 - distributed.worker - INFO -           Worker name:             special_worker
2023-09-13 15:57:23,927 - distributed.worker - INFO -          dashboard at:           <IP_ADDRESS>:42291
2023-09-13 15:57:23,927 - distributed.worker - INFO - Waiting to connect to:      tcp://<IP_ADDRESS>:8786
2023-09-13 15:57:23,927 - distributed.worker - INFO - -------------------------------------------------
2023-09-13 15:57:23,927 - distributed.worker - INFO -               Threads:                          1
2023-09-13 15:57:23,927 - distributed.worker - INFO -                Memory:                   3.13 GiB
2023-09-13 15:57:23,927 - distributed.worker - INFO -       Local Directory: /tmp/dask-scratch-space/worker-uwkqglq5
2023-09-13 15:57:23,927 - distributed.worker - INFO - -------------------------------------------------
2023-09-13 15:57:23,932 - distributed.worker - INFO - Starting Worker plugin shuffle
2023-09-13 15:57:23,932 - distributed.worker - INFO -         Registered to:      tcp://<IP_ADDRESS>:8786
2023-09-13 15:57:23,932 - distributed.worker - INFO - -------------------------------------------------
2023-09-13 15:57:23,933 - distributed.core - INFO - Starting established connection to tcp://<IP_ADDRESS>:8786
Hello!
16:00:12.727 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:00:21.908 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:00:30.204 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:00:38.761 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:00:47.142 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:00:55.426 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:02:41.596 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:02:50.030 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:03:03.527 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:03:11.621 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:03:21.032 | INFO    | Task run 'say_hello-0' - Finished in state Completed()
Hello!
16:03:29.293 | INFO    | Task run 'say_hello-0' - Finished in state Completed()

On the regular worker:
$ dask worker --nthreads '3' tcp://<IP_ADDRESS>:8786 --name only_regular_tasks
2023-09-13 15:57:56,149 - distributed.nanny - INFO -         Start Nanny at: 'tcp://<IP_ADDRESS>:45717'
2023-09-13 15:57:56,398 - distributed.worker - INFO -       Start worker at:     tcp://<IP_ADDRESS>:34377
2023-09-13 15:57:56,398 - distributed.worker - INFO -          Listening to:     tcp://<IP_ADDRESS>:34377
2023-09-13 15:57:56,398 - distributed.worker - INFO -           Worker name:         only_regular_tasks
2023-09-13 15:57:56,398 - distributed.worker - INFO -          dashboard at:           <IP_ADDRESS>:42241
2023-09-13 15:57:56,398 - distributed.worker - INFO - Waiting to connect to:      tcp://<IP_ADDRESS>:8786
2023-09-13 15:57:56,398 - distributed.worker - INFO - -------------------------------------------------
2023-09-13 15:57:56,398 - distributed.worker - INFO -               Threads:                          3
2023-09-13 15:57:56,398 - distributed.worker - INFO -                Memory:                   9.40 GiB
2023-09-13 15:57:56,398 - distributed.worker - INFO -       Local Directory: /tmp/dask-scratch-space/worker-sz_hhz3t
2023-09-13 15:57:56,398 - distributed.worker - INFO - -------------------------------------------------
2023-09-13 15:57:56,402 - distributed.worker - INFO - Starting Worker plugin shuffle
2023-09-13 15:57:56,403 - distributed.worker - INFO -         Registered to:      tcp://<IP_ADDRESS>:8786
2023-09-13 15:57:56,403 - distributed.worker - INFO - -------------------------------------------------
2023-09-13 15:57:56,403 - distributed.core - INFO - Starting established connection to tcp://<IP_ADDRESS>:8786
0
16:00:08.917 | INFO    | Task run 'show_number-0' - Finished in state Completed()
1
16:00:17.455 | INFO    | Task run 'show_number-0' - Finished in state Completed()
2
16:00:26.501 | INFO    | Task run 'show_number-0' - Finished in state Completed()
3
16:00:34.491 | INFO    | Task run 'show_number-0' - Finished in state Completed()
4
16:00:43.324 | INFO    | Task run 'show_number-0' - Finished in state Completed()
5
16:00:51.269 | INFO    | Task run 'show_number-0' - Finished in state Completed()
0
16:02:32.554 | INFO    | Task run 'show_number-0' - Finished in state Completed()
1
16:02:46.101 | INFO    | Task run 'show_number-0' - Finished in state Completed()
2
16:02:59.269 | INFO    | Task run 'show_number-0' - Finished in state Completed()
3
16:03:07.540 | INFO    | Task run 'show_number-0' - Finished in state Completed()
4
16:03:16.945 | INFO    | Task run 'show_number-0' - Finished in state Completed()
5
16:03:25.199 | INFO    | Task run 'show_number-0' - Finished in state Completed()

I know it's been some time since the original report, would you be willing to test this again using these versions:

prefect==2.13.0
prefect-dask==0.2.5
dask==2023.9.1
distributed==2023.9.1

And then let me know if you're still having the same trouble?

I'm going to close this one out as fixed, as we're unable to reproduce this on our end.  There were a LOT of improvements to how tasks are handled between November and today, and I believe this was fixed as a side-effect.
If anyone is still having trouble with this, please open a new issue with repro steps.

Hey @chrisguidry
Although this is fixed, there is a race condition somewhere as I see different tasks having other task annotations, I can't really provide a reproducible example due to the nature of the problem but it occur in flows that looks like the below
with annotate(priority=1000):
    task1.map(...)

with annotate(priority=-1000):
    task2.map(...)

@BitTheByte thanks for the feedback, can you open a fresh issue with all the details you have available (prefect* and dask* versions, the behavior you're seeing and what you expect, etc)?


[Enhancement] move memory release out of lock in DynamicCache iterate operation (backport #31396)

Release memory while holding DynamicCache's lock may cause other operation hang. Move it out of lock.
Fixes #31396
What type of PR is this:

[ ] BugFix
[ ] Feature
[x] Enhancement
[ ] Refactor
[ ] UT
[ ] Doc
[ ] Tool

Does this PR entail a change in behavior?

[ ] Yes, this PR will result in a change in behavior.
[x] No, this PR will not result in a change in behavior.

If yes, please specify the type of change:

[ ] Interface/UI changes: syntax, type conversion, expression evaluation, display information
[ ] Parameter changes: default values, similar parameters but with different default values
[ ] Policy changes: use new policy to replace old one, functionality automatically enabled
[ ] Feature removed
[ ] Miscellaneous: upgrade & downgrade compatibility, etc.

Checklist:

[ ] I have added test cases for my bug fix or my new feature
[ ] This pr needs user documentation (for new or modified features or behaviors)

[ ] I have added documentation for my new feature or new function

Bugfix cherry-pick branch check:

[x] I have checked the version labels which the pr will be auto-backported to the target branch

[ ] 3.2
[ ] 3.1
[ ] 3.0
[ ] 2.5

[FE Incremental Coverage Report]
:heart_eyes: pass : 0 / 0 (0%)

[BE Incremental Coverage Report]
:heart_eyes: pass : 25 / 26 (96.15%)
file detail

path
covered_line
new_line
coverage
not_covered_line_detail

:large_blue_circle:
src/util/dynamic_cache.h
25
26
96.15%
[255]


[SPARK-26774][CORE] Update some docs on TaskSchedulerImpl.

A couple of places in TaskSchedulerImpl could use a minor doc update on
threading concerns.  There is one bug fix here, but only in
sc.killTaskAttempt() which is probably not used much.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/testing-k8s-prb-make-spark-distribution-unified/8220/
Test PASSed.

Merged build finished. Test PASSed.

@pghandi999 @Ngone51 @jiangxb1987 @markhamstra
Nothing major here, I just thought a few doc updates would help this part of the code.  (I did discover a race condition, but one that is probably irrelevant most of the time.)  I actually originally filed this jira b/c I thought the problem was much worse, but in any case I still think its worth trying to update this a bit.
I will be gone next week so no rush on this, but thought I'd post this before I forgot about it completely.

Test build #102682 has started for PR 23874 at commit 3646b74.

Oops, @pgandhi999 I got your handle wrong the first time, so pinging you again :)

Is the HashMap executorIdToRunningTaskIds also protected by "this"? If not, should it be protected?

Test build #102682 has finished for PR 23874 at commit 3646b74.

This patch fails Spark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/102682/
Test FAILed.

Test build #4566 has started for PR 23874 at commit 3646b74.

Test build #4566 has finished for PR 23874 at commit 3646b74.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Is the HashMap executorIdToRunningTaskIds also protected by "this"? If not, should it be protected?

IIUC executorIdToRunningTaskIds has already been protected, maybe we shall also update its comment.

@jiangxb1987 ok, makes sense. LGTM.

Merging to master.


Add pipeline file to user story branch

This PR was merged with testing-controller branch since it had the changes to the folder and post and comment properties which was needed to pass the build


Animation looks like Enso's frozen/non responsive

Discord username
No response
What type of issue is this?
Permanent – Occurring repeatably
Is this issue blocking you from using Enso?

[ ] Yes, I can't use Enso because of this issue.

Is this a regression?

[ ] Yes, previous version of Enso did not have this issue.

What issue are you facing?
When I have switched from one project to another by Ctrl+o the animation played several time and froze on grey logo representation. For the user It  looks like it's broken and it hangs on it for a long time.
Expected behaviour
Animation playing until Enso's ready to display the graph
How we can reproduce it?
open project X (can be small)
wait till it fully loads
press ctrl+o
chose some large project
observe the animation
Screenshots or screencasts
https://user-images.githubusercontent.com/108271897/236809371-866dde69-28be-4c86-87ba-040d8cfc18bc.mp4
Enso Version
2023.5.6 nightly
Browser or standalone distribution
Standalone distribution
Browser Version or standalone distribution
standalone
Operating System
Windows
Operating System Version
Win11pro 22H2 22621.1555
Hardware you are using
12th Gen Intel(R) Core(TM) i9-12900HK / RTX3060 Laptop / Nvidia Drivers 531.68

Sure, here it is:
https://github.com/enso-org/enso/assets/108271897/1dde0e9f-9229-412a-a57d-32f47fc5f0ea

@Procrat would your PR (https://github.com/enso-org/enso/pull/6321) fix this?

@Procrat would your PR (#6321) fix this?

It might, but I've never encountered this bug before, so I wouldn't bet on it.

Reproduced and profiled (see attached file). I believe this is strictly a performance issue related to initialization of all node views, and possibly drop of the ones from previously loaded project. The spinner locks up, because the whole main thread is busy for a long time. We cannot run animations while the main thread is locked for such a long time on a single task.

Profile-20230515T115534.zip

Thanks @Frizi. I believe that in such a case, it is a WONTFIX for now. We should get back to it when we improve the performance of node/graph initialization. Probably after new FRP lands.


When closing Gitea, it displays wrong tasks number left on queue

2021/02/16 11:46:10 ...ue/queue_bytefifo.go:185:Terminate() [D] redis: notification-service Closing with -1 tasks left in queue
2021/02/16 11:46:10 ...ue/queue_bytefifo.go:185:Terminate() [D] unique-redis: pr_patch_checker Closing with -1 tasks left in queue

The queue has changed a lot


transition to sqlalchemy-redshift

This is only a proposal, I'm not going to merge this myself!

@binarydud ^

Sorry about not paying attention. I'm at re:invent this week so I will try
to merge when I get back to my hotel
On Wed, Oct 7, 2015 at 8:02 AM Thomas Grainger<EMAIL_ADDRESS>wrote:

@binarydud https://github.com/binarydud ^
—
Reply to this email directly or view it on GitHub
https://github.com/binarydud/redshift_sqlalchemy/pull/33#issuecomment-146222439
.

@binarydud awesome thanks!


Feature request : add “station availability” in map screen

Is it possible to change the color of the lightning ⚡ in the map marker ?
E.g.

red lightning: station full
green lightning : station empty
yellow lightning : half full (for stations with multiple slots)

I think it is much easier than to see if the station is empty or not 👍

To match a charging station entry from GoingElectric with the availability data from NewMotion, the app uses multiple pieces of information, such as the operator and the number, type and power of available connectors (as the location usually doesn't match exactly). This is only possible with the "detailed" request of the NewMotion API, where only one station can be requested at a time.
So to requesting the availabilities for many stations in the map view would cause many requests at the same time, which consumes a larger amount of data and also sometimes leads to NewMotion returning an error (probably to prevent bots from collecting large amounts of data through their API).
A compromise could be to show the availability (in a compact view like in the favorites list) directly after tapping on the charging station, and not only after scrolling up to see the connectors.

The compromise is good 👍
Here is an example from a iOS app :
When a user zoom out the the stations are summarized without displaying availability.

User zoom in and see the availability of each station .
I think this reduce data .

Does this makes sense ?

Here is an example from a iOS app :

Do you know what data that app uses for chargers and availability? Is it one from the charger operators/payment providers or is it data from GoingElectric?
If I would only be using e.g. NewMotion data this would be no problem, the challenging thing is to combine that with GE.

Good question 😀
The main app is this one here :
https://apps.apple.com/de/app/laden/id1436430456
The screenshot above is from the beta version I will test in the moment .
They have renamed their product .
More infos here :
https://pumpapp.co/
Maybe a hint :
I wrote to them some weeks ago that the "Allego" stations in Berlin won't show any information .
They have fixed this quickly on the server side .
Would you contact them from to developer to developer or should I ask ? (They speak german too)
For inspiration I can send you some screenshots from the apps when you don't have an iOS device .

Maybe a hint :
I wrote to them some weeks ago that the "Allego" stations in Berlin won't show any information .
They have fixed this quickly on the server side .

Hm, okay, so probably they operate an own server that collects and distributes the charger information from GoingElectric and the availability data. I would not like to do this for EVMap at the moment to keep the complexity low. At some point there will be a new GoingElectric API (with some new features), so things will need to be rewritten anyway.


istio helm install fail after uninstall

Bug Description
Failed to helm install istio after uninstall

install version 1.13.4 using helm
uninstall

helm delete istiod -n istio-system
helm delete istio-base -n istio-system
kubectl delete namespace istio-system

install

kubectl create namespace istio-system
helm install istio-base istio/base -n istio-system

helm install istiod istio/istiod -n istio-system --wait

Error message
Error: INSTALLATION FAILED: Internal error occurred: failed calling webhook "validation.istio.io": failed to call webhook: Post "[https://istiod.istio-system.svc:443/validate?timeout=10s":](https://istiod.istio-system.svc/validate?timeout=10s%22:) dial tcp <IP_ADDRESS>:443: connect: connection refused

Work around - delete validatingwebhookconfiguration
kubectl delete validatingwebhookconfiguration istio-validator-istio-system

Version
client version: 1.13.4
control plane version: 1.13.4
data plane version: 1.13.4 (1 proxies)

Client Version: v1.24.1
Kustomize Version: v4.5.4
Server Version: v1.23.5

Additional Information
No response

Could be similar issues
#27501
#36526
#35244
#33585 when installation fails and you do an upgrade, then deployment succeeds with this error
validationController Skip patching webhook, webhook "istio-validator-istio-system" not found

I ran into the same error, exact scenario @arunvc  mentioned above..
Error: INSTALLATION FAILED: Internal error occurred: failed calling webhook "validation.istio.io": Post "https://istiod.istio.svc:443/validate?timeout=10s": dial tcp 10.xx.xx.xx:443: connect: connection refused

worked the work around mentioned by @arunvc  as well,

delete validatingwebhookconfiguration

kubectl delete validatingwebhookconfiguration istiod-default-validator

Install again.


Fixes packmol module compatibility with recent OpenMM and MDTraj versions

Relatively recently, OpenMM added bond order handling, but our packmol module had not been updated to handle this, causing failures -- specifically, the bonds array passed into mdtraj.topology.from_dataframe now has four entries per bond ( (atom1, atom2, type1, order)) but the logic here was still treating it as if it only contained atoms. This resulted in type1 and order getting set to numbers larger than or equal to the number of atoms in the system, causing downstream failures.
This fixes the issue.

Would love a timely review and merge from someone, as I am using this for a class I'm teaching, and this issue had broken some functionality I was using.

(With the exception of one import, changes are isolated to around line 192, but Atom also seems to have stripped out a few trailing spaces in the process. Apologies for the slightly messy changelog.)


Don't need to register controllers manually

You can define inherited hook on base controller. Example:
http://play.crystal-lang.org/#/r/7kn
all the hooks can be found in this spec: https://github.com/manastech/crystal/blob/119ccc89065165bc937b3417e5ac2af2bab6e056/spec/compiler/codegen/hooks_spec.cr

Wow that's pretty neat :+1:


linux-51 is dead.

Type of Request
bug
Infrastructure Environment
LUCI, Github, Cocoon scheduler, Autosubmit, etc...
What is happening?
linux-51 is dead.

Steps to reproduce
Step 1:
Step 2:
..
Step n:
Expected results
I expect to see X when Y is finished.

Ethernet port connection was disabled by itself, reseated network cable to restart the network service.


我下载了 Oil-Polution-Dataset，运行代码时报错了。

=> creating log/oilpollution/pidnet_small/pidnet_small_oil_raw_2023-05-09-14-46
<class 'datasets.elanroad.ElanRoad'>
Epoch: [1/175] Iter:[5/169], lr: ['0.009999'], Loss: 145.18, Acc:0.00, Semantic loss:
Traceback (most recent call last):
File "tools/train.py", line 221, in
main()
File "tools/train.py", line 184, in main
train(config, epoch, config.TRAIN.END_EPOCH,
File "/home/Oil-Polution-Dataset-with-PIDNet/tools/../utils/function.py", line 42, in train
losses, _, acc, loss_list = model(images, labels, bd_gts)
File "/home/.conda/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/.conda/envs/pytorch/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 169, in forward
return self.module(*inputs[0], **kwargs[0])
File "/home/.conda/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/Oil-Polution-Dataset-with-PIDNet/tools/../utils/utils.py", line 54, in forward
loss_sb = self.sem_loss(outputs[-2], bd_label)
File "/home/.conda/envs/pytorch/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/home/Oil-Polution-Dataset-with-PIDNet/tools/../utils/criterion.py", line 105, in forward
return sb_weights * self._ohem_forward(score[0], target)
File "/home/Oil-Polution-Dataset-with-PIDNet/tools/../utils/criterion.py", line 81, in _ohem_forward
min_value = pred[min(self.min_kept, pred.numel() - 1)]
IndexError: index -1 is out of bounds for dimension 0 with size 0

-1 is out of bound .  so you can change this way.
if min(self.min_kept, pred.numel() - 1) >0 :
min_value = pred[min(self.min_kept, pred.numel() - 1)]
else:
min_value = 1
hope you helpful~

Try changing the BASE_SIZE parameter in config file.
It solves the error mostly!!


File watcher dislikes forward slashes in folder path

According to the log:
2019-07-25 09:52:09.7717 #8568 [Warn] SyncTrayzor.Services.FileWatcher: Ignoring change to
 C:\Users\Jakob Borg\dossiers\2018\201801009\some\file\path, as it isn't in C:\Users\Jakob
 Borg\dossiers/2018/201801009\

Thanks! I'll try and get a release out this weekend.


Ethereum transactions

Hey, @belopash , @tmcgroul !
Shall we support sighash and wildcard contract filters right away?

It would be nice

Hey, @belopash , @tmcgroul !
Shall we support sighash and wildcard contract filters right away?

Hey, @belopash , @tmcgroul !
Shall we support sighash and wildcard contract filters right away?
What if we add sighash support in a future release? Will we have to resync archive?

No, sighash is already archived by this PR.

In that case let's support sighash. I'll update the gateway

how about such interface:
ethereumTransactions: [{contract: "*", selector: "0x095ea7b3"}]?

I'm already putting sighash everywhere. Any reason why selector is better?

Only because i've already put selector in acala handlers.
Ok let it be sighash

Has moonriver archive been migrated to new release? If yes, I think it's better to merge two eth test projects


Fixed an issue with query parameters not properly handling arrays

Hi,
I think I have hit a small issue this morning with query parameters passed as a "csv array". So my GET request would look something like this:
/v1.0/test_array_csv_query_param?items=one,two,three
And I was getting parameter items like this:
[u'o', u'n', u'e', u',', u't', u'w', u'o', u',', u't', u'h', u'r', u'e', u'e']
(A string cast to a list).
Please take a look at my suggested fix for this in this pull request. I have only supported the "csv" and "pipes" collectedFormat attributes from the swagger spec currently (http://swagger.io/specification/#parameterObject). Tabs and spaces don't make much sense to me as query parameters.
Let me know what you think guys. I've added a couple of tests that hopefully show the behaviour.

@danballance could you check the decreasing code coverage?

Thanks for contributing :bow:

Yes, no problem, I should have a gap tomorrow :)

:+1:


[Feature] Kysely CommonJs Export

Overview
This adds a CommonJS export for the @powersync/kysely-driver package. Previously only a ESM export was provided.
React Native typically transpiles import statements to require statements, but this might be fickle in some cases - potentially in React Native web.
How this works
See this for reference. The output of this module has changed to:

The cjs export will be used if the module is required e.g. const {} = require('@powersync/kysely-driver'). The ESM export will be used if the module is imported e.g. import {} from '@powersync/kysely-driver';
The CommonJS export is transpiled via an additional tsconfig.json file. The contents of this file use require statements for internal modules. This means this package will require CJS versions of those modules if they provide them. Kysely provides CJS exports.

This should help with https://github.com/powersync-ja/powersync-js/issues/262

Closing this for now. The original purpose of this was to help support React Native web, but React Native web was incorrectly importing the kysely package (not this driver package).


Concurrent processing of settings

Given https://github.com/sbt/sbt/issues/2798 and https://github.com/sbt/sbt/issues/2807
steps

Start sbt server on terminal1 where a build is located: sbt server
Start sbt client on terminal2 from anywhere like ~/temp/: sbt client localhost:5001
On terminal1 project echo-server
On terminal2 project echo-client
On terminal1 type run
On terminal2 type name

expectation
On terminal1 blocks on run, on terminal2 I see "echo-client". In other words, run doesn't block other terminal from querying settings.

Oh! This is what I'm working on. Query settings. WIP in https://github.com/sbt/sbt/pull/2935.


Assignment Reports

Been thinking that we can make the autograder demo look very good by adding some simple reports.
Some that come to mind are:

Course report that has assignments on x-axis and number of submissions on the y-axis. So we know how many submissions were made for each assignment (since we already have some great students who fail to even submit ...)

Same as above but the average score on the y-axis.

Aggregate marks with averages and standard deviations. Similar to what we have on Neon but aggregates only ... not for each assignment.

This is all low priority. Let me know if you guys want to add another TA to this coding effort so that we can delegate some of this to them. I will relieve them of other grunt work duties if they want to do this instead.

@soachishti @BilalZaib Please take a look above.

Got it.
If its possible to add another TA then it would be cool to work in little bigger team :) We could breakdown this to smaller tasks (single report for instance) so that it would be easier for them to start.

Sure. You can talk to a TA of your choice and bring them on board. If you can find enough tasks for them and can manage them you can even have both of them here. I can do the data entry myself =]
Let me know in either case.

One report I can think of is for each course ... on the x-axis is the time (this comes from due date of different assignments of the course). We can show average marks and the standard deviation both on the y-axis (using something like a box plot).
Second, we can have the number of submissions for assignments over time for a course.

Ok, now that we have all the PRs closed, do we have any update on this one?

I will talk to other TA's to have their progress and then I will update you.

@recluze Bilal will work on this on weekend.

@BilalZaib Are you working on this?

Not working but I'll work tomorrow IA

@BilalZaib Please make sure you create a separate file for the report views. We want to keep the main views.py file clean from the extra features we're adding now.


Add support for MacOS Arm64.

This adds a profile for arm64 on Mac os. Probably things could be simplified more with os-maven-plugin, but I didn’t want to touch more.
I added the arch name property, so that all OS can benefit from it, but right now it’s only filed on macOS 64.
This actually fixes #10. I am happy to build on MacOS 64 (I actually did, and I have the dylib right here, but it felt strange to sent a binary without asking).
I tested this and it fixes https://github.com/classgraph/classgraph/issues/890, too

Great work, thank you @michael-simons!

Take note that I did not check in the native lib that I build on my system, this is missing so that things work completely. It felt strange pushing that binary.

@michael-simons Do you have any idea how to solve the new/current build issue on Windows-x86?
I haven't built this in a long time, and I don't remember anything about the mingw integration (which was set up using egor-tensin/setup-mingw@v2).

Take note that I did not check in the native lib that I build on my system, this is missing so that things work completely. It felt strange pushing that binary.

Right, I understand -- I think the GitHub action auto-pushes, but you would have to be a repo contributor for that to work.
I didn't document how I built and pushed this jar, so I'm going to have to think through how to push an update for this! I think I published manually, since I didn't set up mvn-release for this project... @Roberto-Gentili do you remember?

"Quick look"… Tja… Anyhow, works now, see #16

Take note that I did not check in the native lib that I build on my system, this is missing so that things work completely. It felt strange pushing that binary.

Right, I understand -- I think the GitHub action auto-pushes, but you would have to be a repo contributor for that to work.
I didn't document how I built and pushed this jar, so I'm going to have to think through how to publish an update for this! I think I published manually, since I didn't set up mvn-release for this project... @Roberto-Gentili do you remember?

To release you need to include in the commit message the string "Release new version"

To release you need to include in the commit message the string "Release new version"

@Roberto-Gentili Of course! I forgot about that :-)  Thank you!


GH2887: Enforce bash scrips LF line endings

fixes #2887

If already cloned repo endings can be fixed after this is merged by executing (as attributes are cached)

git rm --cached -r .
git reset --hard

@devlead


verify Industrial University Of Ho Chi Minh City

Please visit my university website on https://iuh.edu.vn

@vinhngoSTS I am sorry, the domain iuh.edu.vn is removed from our trusted domains list because it was abused in the past. If you are the student of this school, please enroll to GitHub Student Developer Program. Then apply for JetBrains educational subscription with your GitHub account (GitHub tab at https://www.jetbrains.com/shop/eform/students).


Issues on Embed sequences with TM-vec.

Hi researchers, thanks for sharing such awesome work.
But when I run TM-VEC locally, I encounter the following problems.

For ipynb/repo_EMBED.ipynb

#Load the ProtTrans model and ProtTrans tokenizer
tokenizer = T5Tokenizer.from_pretrained("Rostlab/prot_t5_xl_uniref50", do_lower_case=False )
model = T5EncoderModel.from_pretrained("Rostlab/prot_t5_xl_uniref50")

Error:
OSError: Can't load tokenizer for 'Rostlab/prot_t5_xl_uniref50'. If you were trying to load it from https://huggingface.co/models, make sure you don't have a local directory with the same name. Otherwise, make sure 'Rostlab/prot_t5_xl_uniref50' is the correct path to a directory containing all relevant files for a T5Tokenizer tokenizer.
Solution:
I finally solved the problem by downloading prot_t5_xl_uniref50 locally instead of using the URL to download. But I guess it may be due to the version of Transformers, because in https://huggingface.co/Rostlab/prot_t5_xl_uniref50/tree/main, the code used in Use in Transformers is as follows, different from code used in ipynb/repo_EMBED.ipynb.
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("Rostlab/prot_t5_xl_uniref50")
model = AutoModelForSeq2SeqLM.from_pretrained("Rostlab/prot_t5_xl_uniref50")

For https://github.com/flatironinstitute/deepblast/wiki/Searching-proteins
It says "Say that you have a file called my_proteins.fasta", but my_proteins.fasta is not used below. This may be a minor issue that may cause confusion for users.

Thanks for your response.

Hi @maovshao thank you for the notes!  Glad that you got this working.  Yes, we normally download prot_t5_xl_uniref50 locally, since its 10 min download, and easier to reuse with a local copy.
Agreed, I think this would be great to include in the README.  Feel free to suggest edits via pull request -- otherwise we'll update with the comments in this thread later this week.

Thanks for your quick reply.
I've suggested edits via pull request in https://github.com/tymor22/tm-vec/pull/27.
I hope this simple modification will make the work more user-friendly.

This should now be resolved with the updated README.  Thanks!


Remove visibility of transcribers Open Data status from Coords pages

Was part of #847
For discussion: do coords need to know the open data status of individuals?

Surely syndicate coordinators need access to this information?

They need to know in order to allocate work that has to be open.


Bug changing margin

I don't know why, but if you change the default value of the parameter margin, it will do weird things.
For now, until it is fixed, just don't change this value.

Another option is to just remove this parameter, think about it

This issue was here for so long, so I decide to fix it deleting the possibility to change the margin of some things.
The things you are not goin to be capable to change the margin now are completly unnecessary.
The important things don't have bugs, so you will be capable to do it in the future.


add remote storage

Add ability to use remote storage things like https://github.com/datproject/dat-http.
I think there were two parts:

Deciding on remote storage
Replicating to local storage

I think @maxogden and I talked about an API for this but can't remember...

@joehand Some news?
We are facing issues with dat caused by ISP firewall blocks (something like DPI), so http storage/transport will probably fix it.


fleek apply on MacOS 13.3.1 errors out with no details

Describe the bug
fleek apply on MacOS errors out with no details
To Reproduce
Steps to reproduce the behavior:
fleek apply after first installation on MacOS 13.3.1
Expected behavior
At least output an error message?
Environment

OS: MacOS 13.3.1
Shell: bash
fleek version 0.8.3

Additional context
 [d]  debug enabled
 [d]  git autopush: false
 [d]  git autocommit: false
 [d]  git autopull: false
 [*]  Apply fleek configuration
 [d]  skipping git
 [✓]  Writing configuration files
 [d]  skipping git
  ERROR
  ERROR   Error: exit status 1
  ERROR
 [d]  Command stderr:

 [d]
      ExecutionID:45295bf2858a4aee875aea9bd86f8d84

I have already confirmed this is unrelated to #149

My .fleek.yml:
    fleeks: cd /Users/joey/.local/share/fleek
bling: high
ejected: false
flakedir: .local/share/fleek
git:
    autocommit: false
    autopull: false
    autopush: false
    enabled: false
name: Fleek Configuration
packages:
    - helix
paths:
    - $HOME/bin
    - $HOME/.local/bin
programs:
    - dircolors
shell: bash
systems:
    - arch: aarch64
      hostname: bishop.local
      os: darwin
      username: joey
unfree: true

And the contents of ~/.local/share/fleek:

please follow the upgrade guide here (https://getfleek.dev/docs/upgrade) and try with the latest version of fleek. Let me know if that solves your issue.

Thanks for reporting your success, I appreciate it!


Update ghcr.io/robert-koch-institut/mex-backend Docker tag to v0.27.0

This PR contains the following updates:

Package
Type
Update
Change

ghcr.io/robert-koch-institut/mex-backend
service
minor
0.25.0 -> 0.27.0

Release Notes

robert-koch-institut/mex-backend (ghcr.io/robert-koch-institut/mex-backend)
v0.27.0
Compare Source
Added

configure backoff rules for graph commits
validate that the number of merged edges is as intended
implement graph flushing connector method
add endpoint for flushing the neo4j database (when running in debug)

Removed

remove open-api schema customization, not needed anymore by the current editor
remove purge-script, this is an HTTP endpoint now

v0.26.0
Compare Source
Added

added an endpoint for getting a person by name from LDAP

Changes

updated to mex-common 0.45.0 and mex-model 3.4.0

Configuration
📅 Schedule: Branch creation - At any time (no schedule defined), Automerge - At any time (no schedule defined).
🚦 Automerge: Disabled by config. Please merge this manually once you are satisfied.
♻ Rebasing: Whenever PR becomes conflicted, or you tick the rebase/retry checkbox.
🔕 Ignore: Close this PR and you won't be reminded about this update again.

[ ] If you want to rebase/retry this PR, check this box

This PR has been generated by Renovate Bot.

handled in https://github.com/robert-koch-institut/mex-editor/pull/192


Update to iqm-client 16.0

Looks like iqm-client 16.x does not support Python 3.12 (whereas 15.x supports all Python versions), so we cannot make this upgrade yet.

Now iqm-client 17.0 has been released and supports all Python versions, but it is producing errors. Needs further investigation.

17.1 again has the Python < 3.12 restriction.


challenge 6

[x] Top-level README “Table of Contents” is updated
[x] README for this challenge is complete
- [x] Summary, Description, Approach & Efficiency, Solution
- [x] Picture of whiteboard
- [] Link to code
[x] Feature tasks for this challenge are completed
[x] Unit tests written and passing
- [x] “Happy Path” - Expected outcome
- [ ] Expected failure
- [ ] Edge Case (if applicable/obvious)


Create Toast component

Follow Spectre.css toasts component.

@ccontreras added you as a contributor (9fa23be).


Technical/graphics api abstraction

here is the start of the API to insert a Metal/Sokol back end. There is no more GL code in the Graphics class.

Happy to go with upper camel case if thats the preference? Doesn’t bother me either way as long as we are consistent :)
For now yes, I've tried to get most of the ALL_CAPS stuff out


Automated cherry pick of #3731: Fix tolerations for Kubernetes >= 1.24

Cherry pick of #3731 on release-1.5.
#3731: Fix tolerations for Kubernetes >= 1.24
For details on the cherry pick process, see the cherry pick requests page.

Codecov Report

Merging #3745 (eb4750a) into release-1.5 (e4bb9a2) will decrease coverage by 16.02%.
The diff coverage is n/a.

@@               Coverage Diff                @@
##           release-1.5    #3745       +/-   ##
================================================
- Coverage        50.15%   34.13%   -16.03%
================================================
  Files              304      132      -172
  Lines            25854    15618    -10236
================================================
- Hits             12967     5331     -7636
+ Misses           11211     9801     -1410
+ Partials          1676      486     -1190

Flag
Coverage Δ

integration-tests
34.13% <ø> (?)

kind-e2e-tests
?

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

pkg/controller/crdmirroring/crdhandler/utils.go

pkg/agent/nodeportlocal/k8s/annotations.go

...kg/controller/networkpolicy/antreanetworkpolicy.go

...kg/agent/controller/networkpolicy/audit_logging.go

pkg/ovs/openflow/ofctrl_meter.go

pkg/ipam/ipallocator/allocator.go

.../flowexporter/connections/conntrack_connections.go

pkg/controller/networkpolicy/clustergroup.go

pkg/util/k8s/client.go

pkg/legacyapis/system/install/install.go

... and 426 more

/test-all

/test-e2e
/test-conformance

/skip-networkpolicy
/skip-conformance
manually verified above tests.


Python2 Support

For the ones that are still using Python2, I have prepared this version with small changes that enables Python2 support. The most important change is to support reading the Pickle protocol=3 in Python2. Then it works like a charm.
https://github.com/loretoparisi/word2word
$ python
Python 2.7.16 (default, Mar  4 2019, 09:01:38)
[GCC 4.2.1 Compatible Apple LLVM 10.0.0 (clang-1<IP_ADDRESS>)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> from word2word import Word2word
>>> en2fr = Word2word("en", "fr")
>>> print(en2fr("apple"))
[u'pomme', u'pommes', u'pommier', u'tartes', u'fleurs']

Python2 will retire soon. Only 2 months left.
https://pythonclock.org


Code and Script

Thank you for sharing your work!

The LearningRateMonitor is not defined in train.py, causing a Callback error [Compvis].
"Bilnear" in finetune_data might need to be changed [Compvis].
The Laion-retrieval currently seems to be not working [Diffuser].
For nudity removal (I followed the setting in Diffuser), I generated 200 prompts with people/body based on your llm generation code and used them for class-prompt, setting the caption_target as "nudity, nsfw" as suggested by the authors. This will generate 1,000 safe images in the data path. Does it work correctly? or did I miss something?

Hi, Thanks for the interest in our work and your queries.

We are not using LearningRateMonitor but will also remove this from the code.
You are correct, Lanczos will be better than bilinear. Will update to that in the next commit.
I am aware of the issues with laion-retrieval not working. In the meantime, we have also provided the prompts that we used for all the experiments in the paper and hope that's useful.
For nudity removal, you are correct that the 1000 images generated in the data path should be safe images. Generating prompts from the llm for "people, men, women" works better. Including "body" in the llm prompting can lead to prompts that lead to unsafe images. Thanks for your suggestion.


Component with floating point scale is dropped in TTF

I just noticed if scale of a component in a UFO2 file is less than 1 (like 0.962916503511) it will not appear in the final TTF. Is this a problem or an undesired behaviour?

that is weird...
What do you mean it does not appear? Is it not in the glyf table (e.g. if you dump the font with TTX)?
Can you provide a reproducer?

The glyph that contains the component will become empty in the TTF. Can't post the file but I can email the file to you?

please, thanks! cosimo [at] anthrotype [dot] com
UFO2...we don't use or test that much any more since we switched from robofab to defcon, but they are supposedly supported.

well, i do see them in the TTX file, and I can also render them just fine
    <TTGlyph name="uniFBB2" xMin="7" yMin="728" xMax="131" yMax="851">
      <contour>
        <pt x="69" y="728" on="1"/>
        <pt x="43" y="728" on="0"/>
        <pt x="7" y="761" on="0"/>
        <!-- [...] -->
      </contour>
      <instructions/>
    </TTGlyph>

    <!-- [...] -->

    <TTGlyph name="uniFBB4" xMin="9" yMin="730" xMax="244" yMax="850">
      <component glyphName="uniFBB2" x="118" y="30" scale="0.9629" flags="0x4"/>
      <component glyphName="uniFBB2" x="2" y="29" scale="0.9629" flags="0x4"/>
    </TTGlyph>

    <!-- [...] -->

    <TTGlyph name="uniFBB6" xMin="9" yMin="663" xMax="233" yMax="908">
      <component glyphName="uniFBB4" x="0" y="-35" scale="0.95734" flags="0x4"/>
      <component glyphName="uniFBB2" x="56" y="117" scale="0.929" flags="0x4"/>
    </TTGlyph>

The screenshot below is from fontview. I typed the characers U+FBB6 U+FBB4 and U+FBB2

they are definitely in the compiled TTF. Where you don't see them appearing?

I opened it in the file in the Glyphs app, I guess the app didn't read the components but you're right I can see them too. Sorry for the inconvenience. I had similar issues with Robofont while generating when the component was removed after generating, that's why I chose to use fontmake.


need single line output for CNAME records with awless list records

Hi,
For a CNAME record command like this awless records | grep CNAME,  it is printing ttl on a second line like this. That makes it hard to write scripts that parse the output.
| awls-c6380b5c | CNAME | alias.domain.com.       | real-host.amazonaws.com
| 60     |
If you could print them all one one line that would be great on your next update.

You should not use the default display format (table) to parse outputs in scripts. Tables are human readable and they may introduce line-breaks if entries are too long.
Use rather the csv (./awless list records --format csv) or tsv (./awless list records --format tsv) format that will be much easier to parse.
That being said, there was a bug in 0.0.19 in which ./awless list records --format csv/tsv also added new lines inside records (which broke CSV/TSV format). This is now fixed on master and will be in next release.
Thanks for the bug report.

sounds good. thanks for making this handy tool available as open source.


Multiple redirection rules

hi,
i want to have a route that has multiple permissions, and only be accessible if all of them are met,
and i want a different redirection rule for each of them,
for example:
{
    only: ['isAuthorized', 'admin'],
    redirectTo: {
        admin: {
            state: 'home'
        },
        isAuthorized: {
            state: 'login'
        }
    }
}

what is the best way to accomplish this?

Between values in array operator OR is used to create alternative. If you need AND operator between permissions define additional PermRole containing set of those.

why would it use OR operator for it, in case of OR operator all the permissions would have to be rejected for the redirect rule to be triggered... in which case which one would it turn to...
this doesnt make any sense...

@masterspambot, it there any way to achieve this without creating a role.


algo: Added a menu driven implementation of Binary Search Tree

Title : Added a menu driven implementation of Binary Search Tree
Issue no : https://github.com/himanshu-03/Python-Data-Structures/issues/46
Description
A binary search tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree. Wikipedia
I have added insertion, searching and traversing (preorder, inorder, postorder) of the tree.
Checklist

[ ] I have read and agree to abide by the Code of Conduct
[ ] I have read and followed the Contributing Guidelines

Great job!
Thank you for contributing. Do give this repository a star if you feel like ✨


Added wifi scan API

Just needed the functionality for a project I'm working on. Feel free to modify to your liking. Or not :)
The RequestScan API is not very well documented:
https://developer.gnome.org/NetworkManager/stable/gdbus-org.freedesktop.NetworkManager.Device.Wireless.html#gdbus-method-org-freedesktop-NetworkManager-Device-Wireless.RequestScan
... so I did what everyone else who has written a wrapper for this command and passed in an empty option map.
---- Autogenerated Waffleboard Connection: Connects to #116

Also, let me know if there is a better way to submit contributions, re: your versionist requirements.

Thanks again for the new contribution! It definitely makes sense to expose RequestScan there.
As for VersionBot, please take a look at my last commit: https://github.com/resin-io-modules/network-manager/pull/114/commits/79b37ee671fa2c84ed046fa329fe04fcb17a4b24
The commit contains two footer fields in the commit message: Change-Type: patch and Connects-To: hashtag-issue-number. This one in particular will need a minor version bump, since we are adding a new feature. Change-Type: minor. Connects-To will need a new issue created as well.
Just for a bit more info: internally VersionBot uses versionist: https://github.com/resin-io/versionist. And VersionBot's repo is https://github.com/resin-io-modules/resin-procbots.
However I see that our CircleCI build is not triggered for some reason. I need to check with another team member why this is the case. There are some linting and formatting checks running on CircleCI, and those definitely need to happen before we merge it.
Let's change the new method from scan to request_scan to be more close to the original method.
You may undo the commit on the same branch and create a new one with a new commit message. Let's also change the main part of the commit message to something like: "Expose RequestScan through WiFiDevice::request_scan" or something similar.
BTW, I am exploring the option of converting this crate to use libnm instead of directly communicating with NetworkManager through the D-Bus API. There is a Rust generator that can create automatically bindings to it: https://github.com/gtk-rs/gir. libnm is the official NetworkManager client library and it handles all the D-Bus stuff internally. I still have not looked very closely at this, but it looks quite promising.

Alright, we enabled the CircleCi builds. I think once you recommit, they will be triggered. The important one with the linting and formatting checks is ci/circleci: test.
It turns out I will still have to make a second PR, as VersionBot still does not support fully user-contributed PRs. Not a big issue for me though.

@spiderkeys thanks a lot for the changes. I will test it and merge it early next week when I get back from vacation. No problem for the CI, I will have to recreate the PR anyway.
For libnm it will probably be even easier to make the bindings, since the Gir tool will generate automatically Rust code for them. I tried it a couple of weeks ago again and saw how it works, but never tried to run the bindings, as I had to do some manual work to get it all running. Hopefully I will have more time for this soon, as it is not only interesting, but it will provide full coverage of what NetworkManager provides. I will probably still have to add some Rust code on top of it for convenience, but let's see how that goes.

Closing the PR in favor of #117, which is the same code.


Are api down?

I'm not anymore able to resolve APIs at https://movies.api-fetch.website/
Are they down? Any new mirror?

Yeah, looks like it's down 😕 https://downforeveryoneorjustme.com/movies.api-fetch.website


Problems with dockerized Rstudio working directory to run TM functions

Hello,
I have encountered a few different problems with using TM through Rstudio.
When I use the dockerized version (opened as instructed in https://mpicbg-scicomp.github.io/tissue_miner/user_manual/TM_R-UserManual.html#prepare-the-movie-data), I have access to all TM functions, but don't seem to be able to access the folders where my data is held (I think this is because the working directory can't change from home to another directory).  I thought maybe copying my data to this home directory will solve the problem, but don't know how to access it.
From my local (undockerized) RStudio, I can of course change the working directory and access my data, but is it possible to set up RStudio to use TM this way also in Windows? This option doesn't seem to appear in the manual for Windows.
I will emphasize that I have been running the quickstart tutorial functions through docker on my data no problem, but would like to use the broader options available through RStudio.
Another issue I have encountered when trying to install and use TM on a different computer. It seems like the download of the TM docker image works ok, but when trying to run the "tm sm make_db" command, permission is denied. Does the data need to be saved in a specific folder?
I understand these issues may be not directly related to TM, and may be quite basic, but nevertheless would like to raise them here.
Thanks,
Yonit Maroudas-Sacks

Hi Yonit,
Could you give me the specs of the Windows (7 or 10, home/family/professionnel/server) and the Docker version installed? Could you also tell me which shell you use (powershell, cygwing, etc...)?
There is indeed very limited section dedicated to  Windows because we don't have windows machines. In principle it works but the settings may be tricky.  With this info I try to get back to you this week-end.

Hi, both computers I am working on have Windows 10 Enterprise 2015, and Docker Quickstart Terminal (which has since been deprecated, but it seems we cannot download the newer Docker toolbox on these computers).
It seems that the second issue I wrote about is solved by saving the files in certain folders instead of others, so please don't worry about that part.  So, to make it clear, I'm able to run tm commands through the docker terminal, but not through RStudio.
Thanks very much!

Not easy, but I suspect that if you use the old Docker Quickstart Terminal you have Virtualbox installed. If it is the case, then you need to specifically include the shares (D: or other mount points)  directly in Virtualbox: Settings > Shared folders
Once this is done in Virtualbox, Docker will be able to see the shares too. I hope this helps.
Another possibility is to install a Linux in a Virtualbox and run docker from the virtualized Linux. I did that a lot for testing purposes.

Hi Raphael, the first option does indeed work, so now everything seems to be working smoothly. Thanks very much for your help!
Yonit


Add check for both path and file

Overview
Describe the changes present in the pull request
Related Github Issue
Include a link to the related GitHub issue, if applicable
Testing
The agent includes a suite of tests which should be used to
verify your changes don't break existing functionality. These tests will run with
Github Actions when a pull request is made. More details on running the tests locally can be found
here,
For most contributions it is strongly recommended to add additional tests which
exercise your changes.

Codecov Report

Merging #907 (9df0c23) into main (6a6228f) will decrease coverage by 5.11%.
The diff coverage is 50.00%.

@@            Coverage Diff             @@
##             main     #907      +/-   ##
==========================================
- Coverage   81.72%   76.61%   -5.11%
==========================================
  Files         184      184
  Lines       18591    18591
  Branches     3257     3257
==========================================
- Hits        15193    14244     -949
- Misses       2489     3342     +853
- Partials      909     1005      +96

Files Changed
Coverage Δ

newrelic/common/agent_http.py
54.70% <50.00%> (-41.47%)
:arrow_down:

... and 59 files with indirect coverage changes
:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


[docs] - Setting headers on document after prod build

I am working with libvips to compile it to wasm with emscripten. the wasm module  needs access to sharedarraybuffer API, which can be only enabled by sending Cross-Origin-Embedder-Policy and Cross-Origin-Opener-Policy headers from document with values require-corp and same-origin respectively. it works just fine with vite because in dev server I can set any headers.
but in prod mode there's no 'server' that I can found in doc. how do I enable SharedArrayBuffer in prod mode? any other way to set headers?
In my one observation I found all request in prod are going to https://tauri.localhost is that a local server?

maybe related: #1522

https://tauri.localhost Is actually a "custom protocol" - so not really a server in the sense that other apps can just listen in on some port over loopback.
But as to the proper solution I am not sure ATM. You could always ship a server along with core (and set its headers appropriately). Not sure though that this would solve your problem elegantly.

Also, it would be helpful to track the system you are using. Can you please add the results of tauri info ?

Unfortunately there's no way to set response headers in Linux yet :(

If you're using Windows or macOS, you can set custom headers using on_web_resource_request.

Tested it and it still didn't work, see https://github.com/tauri-apps/tauri/issues/1522#issuecomment-1103394012

Sad. my full fledged app is ready and working but only in dev mode :P what a tragedy.
let me know if I can try something from my side, but I am not exactly proficient in rust.
@nothingismagick  you mentioned I can try shipping my own server. How does that work? will it be equally safe? assuming it will open a tcp port on client machine.

You can use a localhost server instead of the custom protocol with https://github.com/tauri-apps/tauri-plugin-localhost though it doesn't allow you to set custom headers yet.

It does work on Windows though if you set the headers using on_web_resource_request crossOriginIsolated is true and SharedArrayBuffer is set.

You can use a localhost server instead of the custom protocol with tauri-apps/tauri-plugin-localhost though it doesn't allow you to set custom headers yet.

Just updated it to allow you to set the headers (it works on macOS with the localhost server).

I am looking into this over this weekend, few questions I had

what are the security implications of using localhost server? I assume it opens a port on client machine.
using on_web_resource_request will not need localhost plugin but then if I understand correctly app will not work on linux. is that tauri limitation or platform webview limitation? if it's tauri limitation any plan to resolve it?
is localhost plugin guaranteed to work on all platforms? assuming the security implications are not that huge.

I missed attaching my system information above, my bad. here's output of  tauri info
Environment
  › OS: Windows 10.0.19043 X64
  › Webview2: 101.0.1210.39
  › MSVC:
      - Visual Studio Build Tools 2019
  › Node.js: 16.13.1
  › npm: 8.1.2
  › pnpm: 6.27.1
  › yarn: 1.22.17
  › rustup: 1.24.3
  › rustc: 1.60.0
  › cargo: 1.60.0
  › Rust toolchain: stable-x86_64-pc-windows-msvc

Packages
  › @tauri-apps/cli [NPM]: 1.0.0-rc.10
  › @tauri-apps/api [NPM]: 1.0.0-rc.5
  › tauri [RUST]: 1.0.0-rc.9,
  › tauri-build [RUST]: 1.0.0-rc.8,
  › tao [RUST]: 0.8.4,
  › wry [RUST]: 0.16.0,

App
  › build-type: bundle
  › CSP: default-src blob: data: filesystem: ws: wss: http: https: tauri: 'unsafe-eval' 'unsafe-inline' 'self' img-src: 'self'
  › distDir: ../dist
  › devPath: http://localhost:3000/
  › framework: React
  › bundler: Rollup

App directory structure
  ├─ .git
  ├─ .github
  ├─ .vscode
  ├─ dist
  ├─ node_modules
  ├─ public
  ├─ src
  ├─ src-tauri
  └─ vite
Done in 16.57s.

I am using yarn with vite

what are the security implications of using localhost server? I assume it opens a port on client machine.
Yeah your app assets will be accessible from other applications.

using on_web_resource_request will not need localhost plugin but then if I understand correctly app will not work on linux. is that tauri limitation or platform webview limitation? if it's tauri limitation any plan to resolve it?
on_web_resource_request only works on the Tauri custom protocol (the default implementation for production apps - the ones you create using tauri build). It doesn't work on Linux yet because webkit2gtk only added custom headers support on version 2.36 and that release is not available in older distros, see #3961

is localhost plugin guaranteed to work on all platforms? assuming the security implications are not that huge.
It will work on all platforms.

Your issue is actually that you're creating a second window with the main label, try changing WindowBuilder::new(app, "main", WindowUrl::App("index.html".into())) to WindowBuilder::new(app, "second", WindowUrl::App("index.html".into())). The label must be unique.

Since we can set the headers on supported platforms, I'll close this one and track the crossOriginIsolated issue in #1522


merge

Looks like this was a pull-request submitted by mistake. I'm closing it.

uuups!
Sorry, my bad, I tried to rebase but somehow it ended up the opposite way...
Guess i'm not very used to github, it's a bit confusing for these things.
Thanks!


feat(wrangler): able to deploy complex worker to Workers for Platforms

What this PR solves / how to test:
We (https://webstudio.is) would like to deploy complex (Remix-based) customer applications to Workers for Platforms, which is not possible currently using wrangler and requires a custom script.
Adding an option platformNamespace to wrangler makes it possible to:

Upload all generated static assets to the KV store.
Upload the worker to the namespace instead of the normal Workers' namespace.

Associated docs issues/PR:

[insert associated docs issue(s)/PR(s)]

Author has included the following, where applicable:

[ ] Tests
[x] Changeset

Reviewer has performed the following, where applicable:

[x] Checked for inclusion of relevant tests
[x] Checked for inclusion of a relevant changeset
[ ] Checked for creation of associated docs updates
[ ] Manually pulled down the changes and spot-tested

Fixes # [insert issue number].
No issue opened.

@andrasbacsai thank you for submitting this PR. Since this has the potential to expand the scope of Wrangler quite a bit, we will need some time to sync up with the Workers for Platforms team and have them review as well.

@andrasbacsai thank you for submitting this PR. Since this has the potential to expand the scope of Wrangler quite a bit, we will need some time to sync up with the Workers for Platforms team and have them review as well.

Sure! Thanks for the reply! Just so you know, I've tested it out and it works perfectly. It uploads all the necessary assets to a KV store and publishes the customer worker to the dispatch namespace.
However, it needs a bit different worker to be able to retrieve the assets; due to that, we are using a SPA (Remix based), and the asset names are different in the index.html than the asset names in the KV store (it has an extra hash in the filenames). We need to use the asset manifest file to reroute all files to the correct KV store key names.
I place here the worker's full code (not that long), so if anyone faces the same issue, this could be helpful.
import { getAssetFromKV } from "@cloudflare/kv-asset-handler";
import { createRequestHandler } from "@remix-run/cloudflare";
// Location of the build Remix SPA
import * as build from "../build";
import manifestJSON from "__STATIC_CONTENT_MANIFEST";

const assetManifest = JSON.parse(manifestJSON);
const handleRemixRequest = createRequestHandler(build, process.env.NODE_ENV);
export default {
  async fetch(
    request: Request,
    env: Env,
    ctx: ExecutionContext
  ): Promise<Response> {
    try {
      const url = new URL(request.url);
      const ttl = url.pathname.startsWith("/build/")
        ? 60 * 60 * 24 * 365 // 1 year
        : 60 * 5; // 5 minutes
      const asset = assetManifest[url.pathname.replace(/^\/+/, '')]
      let finalRequest = request

      // If the asset is found in the assetManifest json, we simple request it with the right KV store key name

      if (asset) {
        finalRequest = new Request(url.origin + '/' + asset, {
          ...request
        });
      }
      return await getAssetFromKV(
        {
          request: finalRequest,
          waitUntil(promise) {
            return ctx.waitUntil(promise);
          },
        },
        {
          ASSET_NAMESPACE: env.__STATIC_CONTENT,
          ASSET_MANIFEST: assetManifest,
          cacheControl: {
            browserTTL: ttl,
            edgeTTL: ttl,
          },
        }
      );
    } catch (error) {
    }

    try {
      const loadContext = env;
      return await handleRemixRequest(request, loadContext);
    } catch (error) {
      return new Response("An unexpected error occurred", { status: 500 });
    }
  },
};

Looping in @tanushreesharma-cf since this falls within the scope of her team's work. Could you take a look at what this PR is proposing? Let's discuss how we want to handle this in wrangler.

hey @tanushreesharma-cf , just bumping this :) could you please take a look so we can discuss the best way to move forward?


Auto-detect encoding?

Documentation says

--encoding: Encoding to use for reading text files [default: utf-8]

But different files have different encodings.  Chinese PDF is being read correctly and characters are showing up correctly, but a .txt file in the same folder that's encoded in GB2312 is being garbled in both the search results and the file display.
Probably it should default to detecting the encoding for each file independently and then converting them internally to whatever the embedding expects (UTF8?)
https://pypi.org/project/chardet/

Yep, you're absolutely right. This should be granular on a per-file basis. I can look into auto-detecting encoding, but that might be time consuming for ever file, and it might be error prone. In any case, v0.2 should have better controls for customizing how Semantra works per file.


add module to caddyserver.com

Hi,
It would be nice if we could install the module from https://caddyserver.com/download. This way user don't need to compile caddy themselves with the module enabled.
This could help adoption.
thank you for considering this
Rudy

Done! thank you for the reminder.

wow thank you!


Assertion failed: p (rd.h: rd_malloc: 101)

Description
I have a console app which works as my consumer, and it works inside docker. The problem is at some point consumer stops consuming messages, and when I open docker logs, I see this message:
Assertion failed: p (rd.h: rd_malloc: 101)
Then I restart my docker, and consumer starts to work again. It happens both on 0.11.5 and 0.11.6. Can you help me to figure out why I receive this message, please?
How to reproduce
This is my code:
    static void Main(string[] args)
    {
        try
        {
            Console.WriteLine("!!! CORE OUTBOUND QUEUE CONSUMER STARTED !!!\n");

            var consumerConfig = new Dictionary<string, object>
            {
                { "group.id", _configuration.GetValue<string>("Kafka:GroupId") },
                { "bootstrap.servers", _configuration.GetValue<string>("Kafka:BootstrapServers") },
                { "enable.auto.commit", _configuration.GetValue<bool>("Kafka:Consumer:EnableAutoCommit") },
                { "auto.offset.reset", _configuration.GetValue<string>("Kafka:Consumer:AutoOffsetReset") },
                { "log.connection.close", false }
            };

            var topics = new List<string> { _configuration.GetValue<string>("Kafka:Consumer:Topics") };

            RunPoll(consumerConfig, topics);
        }
        catch (Exception ex)
        {
            Console.WriteLine($"Date: [{DateTime.Now.ToString("dd.MM.yyyy HH:mm:ss:ffffff")}], Exception: [{ex.ToString()}]");
        }
    }

    private static void RunPoll(Dictionary<string, object> consumerConfig, List<string> topics)
    {
        try
        {
            using (var consumer = new Consumer<string, OutboundMessage>(consumerConfig, new StringDeserializer(Encoding.UTF8), new MessageDeserializer()))
            {
                consumer.OnError += (_, error)
                    => Console.WriteLine($"Date:[{DateTime.Now.ToString("dd.MM.yyyy HH:mm:ss:ffffff")}], Error: [{error}]");

                consumer.OnConsumeError += (_, msg)
                    => Console.WriteLine($"Date:[{DateTime.Now.ToString("dd.MM.yyyy HH:mm:ss:ffffff")}], Error consuming from topic/partition/offset [{msg.TopicPartitionOffset}]: [{msg.Error}]");

                consumer.OnOffsetsCommitted += (_, commit) =>
                {
                    if (commit.Error.Code != ErrorCode.NoError)
                    {
                        Console.WriteLine($"Date: [{DateTime.Now.ToString("dd.MM.yyyy HH:mm:ss:ffffff")}], Failed to commit offsets: [{commit.Error.Reason}]");
                    }
                };

                consumer.OnPartitionsAssigned += (_, partitions) =>
                {
                    consumer.Assign(partitions);
                };

                consumer.OnPartitionsRevoked += (_, partitions) =>
                {
                    consumer.Unassign();
                };

                consumer.OnMessage += async (_, msg) =>
                {
                    var numTries = 0;

                    while (msg.Value.MaxNumAttempts == null || numTries < msg.Value.MaxNumAttempts)
                    {
                        numTries++;

                        var response = await Helper.SendRequestAsync(msg.Value); // Here I send http request to some service

                        if (response != null && (response.Code >= 0 || (response.Code < 0 && msg.Value.AllowedToCommitNegativeResultCodes != null && msg.Value.AllowedToCommitNegativeResultCodes.Contains(response.Code))))
                        {
                            if (!msg.Value.SendCallback)
                            {
                                var committedOffsets = await consumer.CommitAsync(msg);

                                if (committedOffsets.Error.Code == ErrorCode.NoError)
                                {
                                    break;
                                }
                            }
                            else
                            {
                                var responseMessage = new InboundMessage
                                {
                                    Topic = msg.Value.Topic,
                                    ProcessId = msg.Value.ProcessId,
                                    PortalName = msg.Value.PortalName,
                                    ServiceName = msg.Value.ServiceName,
                                    OperationName = msg.Value.OperationName,
                                    OperationStepName = msg.Value.OperationStepName,
                                    Code = response.Code,
                                    Message = response.Message,
                                    Data = response.Data,
                                    CallbackOperationName = msg.Value.CallbackOperationName,
                                    CallbackRetryIntervalInMs = msg.Value.CallbackRetryIntervalInMs,
                                    AllowedToCommitNegativeResultCodes = msg.Value.AllowedToCommitNegativeResultCodes
                                };

                                var responseProducerResult = await _responseProducer.ProduceAsync(msg.Value.Topic + ".response", responseMessage);

                                if (responseProducerResult.Error.Code == ErrorCode.NoError)
                                {
                                    var committedOffsets = await consumer.CommitAsync(msg);

                                    if (committedOffsets.Error.Code == ErrorCode.NoError)
                                    {
                                        break;
                                    }
                                }
                            }
                        }

                        await Task.Delay(msg.Value.RetryIntervalInMs);
                    }
                };

                consumer.Subscribe(topics);

                Console.WriteLine($"Date: [{DateTime.Now.ToString("dd.MM.yyyy HH:mm:ss:ffffff")}], Subscribed to: [{string.Join(", ", consumer.Subscription)}]");

                while (true)
                {
                    consumer.Poll(TimeSpan.FromMilliseconds(100));
                }
            }
        }
        catch (Exception ex)
        {
            Console.WriteLine($"Date: [{DateTime.Now.ToString("dd.MM.yyyy HH:mm:ss:ffffff")}], RunPoll Exception: [{ex.ToString()}]");
        }
    }

Checklist
Please provide the following information:

[x] Confluent.Kafka nuget version: 0.11.6
[ ] Apache Kafka version:
[ ] Client configuration:
[ ] Operating system:
[ ] Provide logs (with "debug" : "..." as necessary in configuration)
[ ] Provide broker log excerpts
[ ] Critical issue

Looks like your host, or container, is out of (virtual) memory. What memory constraints do you have set?

Should I send configuration of the kafka? Or configuration of the docker container where my consumer is running (dockerfile)?

the docker container where your consumer is running - librdkafka it is failing when it is trying to allocate memory, implying the container doesn't have enough resources. You could also try tuning down the queued.max.messages.kbytes on the consumer.

@mhowlett The default value for queued.max.messages.kbytes is 1048576. If I make it down to, let's say, 500000, should I also tune down fetch.message.max.bytes(initial maximum number of bytes per topic+partition to request when fetching messages from the broker) on the consumer and queue.buffering.max.kbytes on the producer to the same value?
Also, if I have 3 partitions per topic, it means that local consumer queue will take up 3x1048576 space, right?

@mhowlett Also, I have a question about queued.min.messages property. The default value is 100000. In the description it says: Minimum number of messages per topic+partition librdkafka tries to maintain in the local consumer queue.  What if I don't have that amount of messages? Should I also tune it down?

@mhowlett After decreasing queued.max.messages.kbytes value to 300000, now I get this message and consumer stops.
Assertion failed: p (rd.h: rd_calloc: 95)

@mhowlett After decreasing queued.max.messages.kbytes value to 300000, now I get this message and consumer stops.
Assertion failed: p (rd.h: rd_calloc: 95)

again, this is librdkafka failing when it tried to allocate memory. queued.max.messages.kbytes is the maximum amount of memory, per partition, that librdkafka will attempt to allocate. suggest being more aggressive with this setting, or increasing the amount of memory available to your application.

@issatayev Is this still an issue?


AttributeError: module 'scrape' has no attribute 'scrape'

AttributeError: module 'scrape' has no attribute 'scrape'## Description
I'm working on python code based on a book, however text,title= scrape.scrape(html) line has an error.
I looked for the possible attributes but couldn't figure it out.
If someone knows possible code, or alternative code let me know.
If someone knows the attributes of scrape, please help me out.
Code is shown below,
import urllib.request
import cchardet
import scrape
if name =='main':
url='https://ja.wikipedia.org/wiki/日本'
with urllib.request.urlopen(url) as res:
byte = res.read()
html=byte.decode(cchardet.detect(byte)['encoding'])
text,title= scrape.scrape(html)
print('[title]:',title)
print('[text]:',text[:300])

Build: [e.g. 3180 - type "About" in the Command Palette]
Operating system and version: [e.g. macOS 13.5.1, python 3.11]

close


feat: skel bba

Related Issue
resolve: #31
Description
skeletoning bba
Checklist
Thank you for your contribution.
Before submitting this PR, please make sure:

[x] Applying goimports
[ ] Test case
[ ] End of Work

comm_test.go has conflict !

done!

LGTM:)


Ability to disable mappings (cli)

Cool project! :)
Snapshots sadly break the history a bit as searge isn't available for them.
As an alternative to working out a way of dealing with presentation of a history where some mappings are not available on some versions I'd suggest a way of specifying which mappings get generated on the CLI.

This has been implemented in https://github.com/zlataovce/takenaka/commit/820557eb198cd1a77685f88f9dbfb889123f855a for the next minor version (1.2.0). Thank you for your feedback!


NpzDeserializer not copying data for non-native ChainerX devices

NpzDeserializer when deserializing to ChainerX ndarrays assumes that the device is a native device https://github.com/chainer/chainer/blob/master/chainer/serializers/npz.py#L180-L182   If the device happens to be a for instance CUDA device, no data is transferred. This is of course not tested but probably should be.

This seems to be an issue for HDF5 as well.


Expand client details (and hide less-important fields)

With the increasing amount of datatypes user may get confused/disoriented. We want to add a way to hide selected variables (saved into the user config), and select a particular displayable to provide a zoomed-in view more prominently.

Not doing it for v1.3b


Epic name field required

When i pushing finging on Jira software he required epic name. I set up epic name id. Epic name it required field on Jira. How i can set up on Dojo this field?

What happens if you do the steps from the docs? https://defectdojo.readthedocs.io/en/latest/features.html?highlight=jira#jira-integration

I complete all steps. Jira integration works. I can pushing all issue type(Task, story, bug, security etc), but cant epic. On Jira epic issue have required fields: theme and epic name. Theme is name of finding, but epic name i dont know and Dojo may be too. Epic name id(10102, default) on Jira settings on Dojo correctly set up, because he pushing finding but got error "Epic name required".

So are you trying to push a finding to JIRA as an epic? Or are you creating an epic from an engagement? The first one won't work because findings don't send epic name. The second one should work.

If there's an exception when pushing to JIRA, defect dojo prints the metadata from JIRA. Can you paste it here? Maybe we can easily set the epic name field if we see that it is present in the metadata.

So are you trying to push a finding to JIRA as an epic?
Yes

Or are you creating an epic from an engagement?

How i can this do?

I want create issue on Jira with subtask for each hosts. It's real with Dojo?

Can you paste it here?

fields from Jira is too much and i can't give information from pre-prod jira

epic name should be fixed by https://github.com/DefectDojo/django-DefectDojo/pull/3609

epic name should be fixed by https://github.com/DefectDojo/django-DefectDojo/pull/3609

In #3782 we fixed the engagement to epic mapping which allows you to have all findings in an engagement be part of an Epic.
Please let us know if this solves your usecase.


IDA adaptive time stepping

Description
This PR makes several changes to adaptive time-stepping in IDA. Previously, the t_eval decided both the points at which we store the solution and the points to explicitly stop the IDA solver. Now, the time-stepping has been broken down into t_eval (which retains the same behavior) and t_interp, which uses IDA's internal Hermite interpolator to efficiently store the solution. Additionally, we default to saving the adaptive time steps, which gives us full-order solution accuracy without negatively impacting the solve speed with periods or dense t_eval vectors.
This PR cleans up the main solve loop of the IDA solver and clearly delineates saving the full solution y vs. specific output variables.
Example: adaptive time outputs (new) vs. fixed outputs

The above picture shows the difference in resolution between the new adaptive time-stepping scheme and the previous approach without affecting the performance. The markers show every data point available in sol.t
Period/drive cycles improvements
parameter_values = pybamm.ParameterValues("Chen2020")
parameter_values.set_initial_stoichiometries(1)

experiment = pybamm.step.CRate(0.1, period = period, duration = 36000)
sim = pybamm.Simulation(
    model,
    solver=solver,
    parameter_values=parameter_values,
    experiment=experiment,
)

sim.solve()

The above figure shows the solve time for a full C/10 discharge. The new IDA solver is strictly faster than the old IDA and the Casadi solver. For the SPM, the IDA vs. Casadi timings are closer because IDA is a DAE solver while Casadi is using an ODE solver. Adding CVODE to pybamm could be future work to further improve our ODE speed.
For small periods, the new IDA solver is about an order of magnitude faster than the old IDA. For large periods, it's about half an order of magnitude faster than Casadi.
In a parameter estimation context, you can also post-interpolate the adaptive time-stepping solution without specifying a t_interp or period for just the variable of interest (such as voltage) which will dramatically improve the performance.
Adaptive time-stepping (no period)
parameter_values = pybamm.ParameterValues("Chen2020")
parameter_values.set_initial_stoichiometries(0)

experiment = pybamm.Experiment([f"Charge at {C_rate}C until 4.2 V"])
sim = pybamm.Simulation(
    model,
    solver=solver,
    parameter_values=parameter_values,
    experiment=experiment,
)

sim.solve()

When t_eval or a period is not set for an experiment, the new IDA is strictly faster than the previous IDA. Additionally, adaptive time-stepping has much better performance for slower simulations that previously used a dense t_eval vector by default.
Fixes #4312
Type of change
Please add a line in the relevant section of CHANGELOG.md to document the change (include PR #) - note reverse order of PR #s. If necessary, also add to the list of breaking changes.

[x] Optimization (back-end change that speeds up the code)

Key checklist:

[x] No style issues: $ pre-commit run (or $ nox -s pre-commit) (see CONTRIBUTING.md for how to set this up to run automatically when committing locally, in just two lines of code)
[x] All tests pass: $ python run-tests.py --all (or $ nox -s tests)
[x] The documentation builds: $ python run-tests.py --doctest (or $ nox -s doctests)

You can run integration tests, unit tests, and doctests together at once, using $ python run-tests.py --quick (or $ nox -s quick).
Further checks:

[x] Code is commented, particularly in hard-to-understand areas
[x] Tests added that prove fix is effective or that feature works

One general question I had: many of the idaklu tests use a dense t_eval and an identical t_interp, which is now the "slow" way of running the solver. When not specificly testing the interpolation code, I would use the most efficient / standard way of running solver.solve, which I believe would be t_eval = [start, stop] and t_interp = None or t_interp = np.linspace(start, stop, N)?

@martinjrobins good point. The most efficient way to run it is using the t_eval = [start, stop] and t_interp = None. A current limitation with this PR is that we do not have the Hermite interpolator available in python (adding it is difficult), so all the post-interpolation tests like sol[v](t) use linear interpolation, which is less accurate. I changed most tests to use t_interp = np.linspace(start, stop, N), which uses the Hermite interpolator.
Once this PR merges, we can fully migrate all the tests to using t_eval = [start, stop] and t_interp = np.linspace(start, stop, N). When we have more accurate post-interpolation, we can then change it to t_eval = [start, stop] and t_interp = None


Rasa X - Correcting action in Interactive Learning leads to invalid story beeing generated

Rasa version: 2.5.1
Rasa SDK version (if used & relevant):
Rasa X version (if used & relevant): 0.39.3 local mode
Python version: 3.8.5
Operating system (windows, osx, ...): Windows 10
Issue: When correcting a predicted action in rasa x interactive mode the generated story in the "story till now" window becomes invalid that means:
-the order of intents/actions may be wrong
-some intents/actions may be missing
Before correcting the action the generated story is correct.
Example:
Before correcting action:
version: "2.0"
stories:
- story: Story from Conversation ID db098d8a4d0744dc99d13a8122702bca
  steps:
  - intent: wants_consultation
  - action: utter_ask_contact_info
  - slot_was_set:
    - company: My Company AG
  - intent: inform
    entities:
    - company: My Company AG
  - action: utter_ask_name
  - intent: why
  - action: utter_explain_company
  - action: utter_ask_phone

After correcting "utter_explain_company" to
-"utter_explain_name"
-"utter_ask_name"
-"action_listen"
the generated story changes to:
version: "2.0"
stories:
- story: Story from Conversation ID 2eee1f1679fd4dc1b4109133cb56ca3c
  steps:
  - slot_was_set:
    - company: My Company AG
  - intent: wants_consultation
  - slot_was_set:
    - company: My Company AG
  - action: utter_explain_name
  - action: utter_ask_name

Error (including full traceback):
WARNING:rasax.community.services.event_consumers.event_consumer:Saving event failed due to an 'IntegrityError'. This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database.  This means that the event is already stored in the database. The event data was '{"sender_id": "2eee1f1679fd4dc1b4109133cb56ca3c", "event": "user", "timestamp":<PHONE_NUMBER>.194421, "metadata": {"rasa_x_flagged": false, "rasa_x_id": 14}, "text": "warum?", "parse_data": {"intent": {"id":<PHONE_NUMBER>076387037, "name": "why", "confidence": 0.9998337030410761}, "entities": [], "text": "warum?", "message_id": "c2848cee174f452490f28256643022f9", "metadata": {}, "intent_ranking": [{"id":<PHONE_NUMBER>076387037, "name": "why", "confidence": 0.9998337030410761}, {"id":<PHONE_NUMBER>962185965, "name": "are_we_done", "confidence": 0.000146308899275}, {"id": -3339746004478828891, "name": "thank_you", "confidence": 7.202406777651049e-06}, {"id":<PHONE_NUMBER>46646757, "name": "faq", "confidence": 5.361795047065243e-06}, {"id": -2131487487650428980, "name": "correct", "confidence": 2.570336619100999e-06}, {"id":<PHONE_NUMBER>859008286, "name": "wants_consultation", "confidence": 2.462720203766366e-06}, {"id": -5842810685277495392, "name": "inform", "confidence": 2.375314352320856e-06}]}, "input_channel": "rasa", "message_id": "c2848cee174f452490f28256643022f9"}'. (sqlite3.IntegrityError) UNIQUE constraint failed: conversation_event.conversation_id, conversation_event.timestamp, conversation_event.type_name
[SQL: INSERT INTO conversation_event (conversation_id, type_name, timestamp, intent_name, action_name, slot_name, slot_value, policy, is_flagged, data, evaluation, rasa_environment) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)]
[parameters: ('2eee1f1679fd4dc1b4109133cb56ca3c', 'user',<PHONE_NUMBER>.194421, 'why', None, None, None, None, 0, '{"sender_id": "2eee1f1679fd4dc1b4109133cb56ca3c", "event": "user", "timestamp":<PHONE_NUMBER>.194421, "metadata": {"rasa_x_flagged": false, "rasa_x_id": ... (771 characters truncated) ...<PHONE_NUMBER>95392, "name": "inform", "confidence": 2.375314352320856e-06}]}, "input_channel": "rasa", "message_id": "c2848cee174f452490f28256643022f9"}', None, 'production')]
(Background on this error at: http://sqlalche.me/e/13/gkpj)

Command or request that led to error:

Content of configuration file (config.yml) (if relevant):

Content of domain file (domain.yml) (if relevant):

Thanks for the issue, @desmarchris will get back to you about it soon!
You may find help in the docs and the forum, too 🤗


Overworld like the moon? Oxygen lack !

The details
Hi, i was thinking if you could add a feature activable via config or datapack that transform the overworld removing the oxygen. And maybe even change the sky, making the overworld looks like the outlands in world of warcraft!
THanks!

Oxygen lack, I'd love this idea.
But when addon implement this, there are some structural difficulties.
Suggest this to Beyond-Earth discord or Github first.

https://discord.gg/Xb2nPmN
https://github.com/MrScautHD/Beyond-Earth/issues

I will review again when If Beyond-Earth dev says no,


r0.10: ImportError: No module named tensorflow

My code runs well on r0.9, and after I upgrade to r0.10, and it runs failed. And my TF r0.10 is built from source also.

More information: since r0.10 needs setuptool > 1.7, and the installed setuptool is 0.98, then I update it to 27.3. And then I switch back to TF r0.9, encounter the same error.
Anyone use r0.10, and what's the version of setuptool used?

How did you tried to revert it back to previous build ?

I can't revert it back, it seems the python issue. Now, my yum can't work after I delete /usr/lib/python2.7/site-packages/. I am not sure whether such packages, like python, setuptools are OS related, and I use centos 7. I dowload the python 7.5.12 source code to rebuild it, and install. But it still can't work.
After I dowload setuptool27.3 and install it, even r0.9 can't work, and it can work well before...
root@hal-dev share]# yum
There was a problem importing one of the Python modules
required to run yum. The error leading to this problem was:
No module named yum
Please install a package which provides this module, or
verify that the module is installed correctly.
It's possible that the above module doesn't match the
current version of Python, which is:
2.7.5 (default, Sep 15 2016, 22:37:39)
[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)]
If you cannot solve this problem yourself, please go to
the yum faq at:
http://yum.baseurl.org/wiki/Faq
[root@hal-dev share]#
[alvin@hal-dev mnist]$
[alvin@hal-dev mnist]$ python convolutional.py
Traceback (most recent call last):
File "convolutional.py", line 31, in
import numpy
ImportError: No module named numpy
[alvin@hal-dev mnist]$

Here we have multiple issues !!
Because it's conflicting with YUM package manager and python modules, if possible could you provide cat convolutional.py

Firstly, my original r0.9 works well, then I want to upgrade to r0.10, since r0.10 need setuptool > 1.7, and I updated setuptools to 27.3 manually, then both r0.10 and r0.9 can't work. Then I do a lot of OPs to python, then yum can't work after I delete /usr/lib/python2.7/site-packages since I try to update it by re-install pip.
'convolutional.py' is the example of mnist in repo, and I haven't change it.

@vigneshstack I copy the 'site-packages' from another machine, and now the yum can work. But my r0.9 still can't work for the example 'tensorflow-r0.9/tensorflow/models/image/mnist'.. I follow the steps:
bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
mkdir _python_build
cd _python_build
ln -s ../bazel-bin/tensorflow/tools/pip_package/build_pip_package.runfiles/org_tensorflow/* .
ln -s ../tensorflow/tools/pip_package/* .
python setup.py develop

BTW, the following works well:
$ bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
$ bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu

@jart Could you take a look at this? Thanks.

The python issues are solved.
Hold on this issue, although I still can't run r0.10 due to my network connection while do configuring.

4 nodes get 4x performance improving, and the network is the bottleneck.


Crash when missing bounds in bit field slice

Writing %a[ in the bitfield line of an instruction crashes with
parse.nim(256)           ?
Error: unhandled exception: Line 4: Expected a number literal [ValueError]

Same issue as in #30, the result of get_unsigned isn't checked properly.
https://github.com/Stuffe/isa_spec/blob/1f21ac176d7a9822d226c45d76f9ad51af5e5a0b/isa_spec.nim#L339-L349

https://github.com/Stuffe/isa_spec/pull/35 fixed this.


Fix recursive set state

Moves setter inside a useState hook to avoid setting it on every render.
Fixes infinite render loop.

Accepted to test