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Attempting to make a nested alert, like in the source page: https://technet.microsoft.com/ja-jp/library/Gg398193(v=OCS.15)

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Should add option to force image from cdn

Some cdn eg. uploadcare has images in url without extension e.g. https://ucarecdn.com/90964191-dfa2-4a22-8118-8a9e460fff9b/
This then causes the image to appear in iframe as this condition fails:
if (url.match(/\.(jpeg|jpg|gif|png)$/) !== null)
I added a temporal solution for my project
if (url.match(/\.(jpeg|jpg|gif|png)$/) !== null || url.match(/ucarecdn.com/))
Would be nice to implement force option to show images without extension needed

Already answered here and here


Enabling windowed/non-window join

I'm a little surprised that this just compiled, and have some concerns about the correctness of the resulting pipeline. Once we push out some more testing capabilities we should evaluate whether the code here does the correct thing.

Agreed, would love to partecipate to setting up some more testing capabilities


CI: use osbuild and composer commits deployed in staging / production

Modify schutzbot/deploy.sh to try to use the actual commits of
osbuild and osbuild-composer deployed in staging / production for CI
runs on main (staging) and stable (production) branches. The same
applies for PRs to main and stable branches. For any other situation, use
the default values defined in deploy.sh.

@Gundersanne the change is finally working. Feel free to review when you have some spare time...


ENH: Add halfspace mode to Qhull

This pull request would add functionality to compute halfspace intersections using Qhull H mode (or equivalently, qhalf).
This is still a WIP as I do not have proper test coverage, but it seems to work.
We also need to prevent someone passing the H option to ConvexHull.
My biggest problem with this PR as it stands is how to feed the feasible point to Qhull: as the check is done in qh_new_qhull, there is no other way than passing it as a string in the mode option...
This would fix #6441 by providing a new interface to H mode.

Sorry that this PR is not moving very fast, but unfortunately I can't really allocate more of my time for this.
I implemented a suggestion of the change of API for qhull on another branch:
https://github.com/haudren/scipy/commit/5db94c5018fcd78b5b55430df071bbcef75b34f8
If you think that it is an acceptable solution, I can add it to this PR.
Another problem I am encountering, is that scipy assumes that the "Qt" option will always be passed, and the resulting hull will always have simplicial facets. Although this is fine in most situations, in the halfspace case, it can sometimes be problematic, as it results in duplication of intersection points.
Should we keep the code as-is and leave it to the user to deduplicate points ? Or should we adapt it to handle non-simplicial mode ? Note that I tried to simply remove "Qt" from required_options in HalfspaceIntersection, but I still get duplicated intersection points... Is the option re-enabled in another place ?

No worries about the delays, everyone here is volunteering their time, so constraints are well understood.
Allowing, optionally, non-simplical facets is probably fine. The problem is in specifying the data structure to expose it, given that numpy does not have a ragged array structure. It's however not possible to change the default behavior of Delaunay/ConvexHull any more.
I cannot immediately comment on the duplicate points issue, as I've never used the halfspace mode.
Regarding the patch to qhull --- looks OK. Another way to do it in order to avoid patching qhull code, could be to instead make a copy of the function (e.g. qh_new_qhull2) with the extra argument --- it could always assume halfspace mode so the code becomes a bit shorter.

I think I corrected most of the points that have been raised before. I still need to merge the Qhull patch, but it needs a bit more work before doing so. Please tell me what other corrections are necessary !
Cheers,

Hello,
I commited some more changes, I hope we're getting closer to something mergeable :cake:

The travis build failed, but I'm not sure why, as the tests fail on a seemingly unrelated module. I'll check it out later.

The travis build failed, but I'm not sure why, as the tests fail on a seemingly unrelated module. I'll check it out later.

See https://github.com/scipy/scipy/pull/6632--the problem should be fixed by rebasing on master.

LGTM from my side. Let's see if the Travis build works now...

All builds have passed :smile: Would you like me to squash a few of those commits together ?

Hum, I actually just checked and plugging the "leak" makes the program segfault when destroying the underlying qhull object. Moreover, I noticed an increase in errors when I free those points.
I think that qhull references that memory somehow: as soon as I have confirmation, I'll update the PR.

Ok, so one should not free this array...
If we look in libqhull_r.c the method qh_addpoint takes a pointer and passes along to qh_makenewfacets. In poly2_r.c, we can see that qh_newvertex is called (l.2343):
vertex->point= point;

Thus we should not free the array. Given that qhull frees all vertices whenever we close the hull, I don't think we have to free this pointer.

I think you still need to free the array, as qhull AFAICS doesn't do it
itself (it doesn't record the pointer to array returned).
.
Memory leaks can be tracked by running some example code in a
forever-loop, and seeing if the memory usage of the program grows with time.
.
In other parts of the code, we're careful to keep alive the numpy arrays
containing the points, and only let go of them once the qhull object
is destroyed. Also here, it would be easier if the array was numpy array
rather than malloc buffer so you could reuse the same mechanism. This
would require transcribing the for loop in qh_sethalfspace_all here.
.
It probably is easier to add a separate mechanism tracking the memory
pointers --- e.g. a Python list attribute on the _QHull object,
containing pointers cast to Python integers (<npy_intp>) keeping track
of the pointers. Or something similar.

There is most definitely a memleak:
import scipy.spatial as sp
import numpy as np

halfspaces = np.array([[1., 0., 0.],
                       [0., 1., 0.],
                       [-1., 0., -1.],
                       [0., -1., -1.]])

extra_halfspace = np.array([[0., -1., -0.8]])

feas_point = -np.array([0.5, 0.5])

for i in range(1000000):
  hs = sp.HalfspaceIntersection(halfspaces, feas_point, incremental=True)
  hs.add_halfspaces(extra_halfspace)
  hs.close()

Results in this figure:

(Obtained using mprof run/mprof plot)
I'll try to implement some of your ideas, but reproducing qh_sethalfspace_all should not be too hard, it is similar to the transformation between dual-halfspaces and points:
def qh_sethalfspace_all(halfspaces, feas_point):
    normals, offsets = halfspaces[:, :-1], halfspaces[:, -1]
    dists = normals.dot(feas_point) + offsets
    return normals/-dists

Ok I think I fixed the memory leak. I'm not that happy with the elegance of the solution, but it works just fine.
Note that valgrind still reports some memory being lost, but this time in QhullMessageStream:

==13423== 99 bytes in 99 blocks are definitely lost in loss record 329 of 911
==13423==    at 0x4C2CE8E: realloc (in /usr/lib/valgrind/vgpreload_memcheck-amd64-linux.so)
==13423==    by 0x50C6D43: _IO_mem_finish (memstream.c:134)
==13423==    by 0x50C297E: fclose@@GLIBC_2.2.5 (iofclose.c:63)
==13423==    by 0x1FBAD79C: __pyx_pf_5scipy_7spatial_5qhull_19_QhullMessageStream_8close (qhull.c:4000)
==13423==    by 0x1FBAD79C: __pyx_pw_5scipy_7spatial_5qhull_19_QhullMessageStream_9close (qhull.c:3932)
==13423==    by 0x1FBB6257: __Pyx_PyObject_CallMethO (qhull.c:45169)
==13423==    by 0x1FBB6257: __Pyx_PyObject_CallNoArg (qhull.c:45224)
==13423==    by 0x1FBB6257: __pyx_pf_5scipy_7spatial_5qhull_6_Qhull_6close (qhull.c:5904)
==13423==    by 0x1FBB6257: __pyx_pw_5scipy_7spatial_5qhull_6_Qhull_7close (qhull.c:5794)
==13423==    by 0x1FBB7295: __Pyx_PyObject_CallMethO (qhull.c:45169)
==13423==    by 0x1FBB7295: __Pyx_PyObject_CallNoArg (qhull.c:45224)
==13423==    by 0x1FBB7295: __pyx_pf_5scipy_7spatial_5qhull_10_QhullUser_2close (qhull.c:16102)
==13423==    by 0x1FBB7295: __pyx_pw_5scipy_7spatial_5qhull_10_QhullUser_3close (qhull.c:16045)
==13423==    by 0x499BE4: PyEval_EvalFrameEx (in /usr/bin/python2.7)
==13423==    by 0x499EF1: PyEval_EvalFrameEx (in /usr/bin/python2.7)
==13423==    by 0x4A1633: ??? (in /usr/bin/python2.7)
==13423==    by 0x44E4A4: PyRun_FileExFlags (in /usr/bin/python2.7)
==13423==    by 0x44EC9E: PyRun_SimpleFileExFlags (in /usr/bin/python2.7)
==13423==    by 0x44F903: Py_Main (in /usr/bin/python2.7)

Any idea if this is a new leak ? I'll try on a master copy to check.

That's probably unrelated issue. Possibly the reason is that QhullMessageStream.close calls fclose and free in the wrong order...

Merged, thanks a lot!

Always a pleasure to be able to contribute back to a great project!


chore: update homebrew installation note

📑 Description
chore: update homebrew installation note
This would be the formula page, https://formulae.brew.sh/formula/k8sgpt (after analytics update)
✅ Checks

[x] My pull request adheres to the code style of this project
[x] My code requires changes to the documentation
[x] I have updated the documentation as required
[ ] All the tests have passed

ℹ Additional Information
relates to https://github.com/Homebrew/homebrew-core/pull/159089

Thanks for this, I hadn't realised it had actually been contributed to homebrew formula mainline, which is why we ran a tap.

Please resolve conficts

should be good now.

Thanks for this, I hadn't realised it had actually been contributed to homebrew formula mainline, which is why we ran a tap.

yeah, make sense to me.

Thanks for this, I hadn't realised it had actually been contributed to homebrew formula mainline, which is why we ran a tap.

yeah, make sense to me.

How will this be updated when we have a new release?

Thanks for this, I hadn't realised it had actually been contributed to homebrew formula mainline, which is why we ran a tap.

yeah, make sense to me.

How will this be updated when we have a new release?

you can add this action into your release flow, that should be it, happy to help.

Thanks for this, I hadn't realised it had actually been contributed to homebrew formula mainline, which is why we ran a tap.

yeah, make sense to me.

How will this be updated when we have a new release?

you can add this action into your release flow, that should be it, happy to help.

Thanks,
Should that be part of this PR?

Thanks for this, I hadn't realised it had actually been contributed to homebrew formula mainline, which is why we ran a tap.

yeah, make sense to me.

How will this be updated when we have a new release?

you can add this action into your release flow, that should be it, happy to help.

Thanks, Should that be part of this PR?

No it should be separate PR, even we dont do per this PR, it would have homebrew maintainers/contributors updating them in patch.
Also for the action setup, it does require committer_token stuff.

@AlexsJones why did you close this?

FYI, these are the recent updates, https://github.com/Homebrew/homebrew-core/pulls?q=is%3Apr+k8sgpt

Hi, apologies this was done in error @chenrui333

Oh, no worries, :)

@AlexsJones thanks for the approval, any process of getting this merged? :)

I can't merge this until we have an action to auto update the brew core repository. Otherwise next release we will go out of date.  It looks like currently it's relying on manual PR's to homebred-core which I don't want to have to rely on

@AlexsJones just raised a homebrew release integration PR, let me know if that works for you
using this action, https://github.com/mislav/bump-homebrew-formula-action
some examples, https://github.com/cli/cli/blob/trunk/.github/workflows/homebrew-bump.yml


[Enhancement] Enable compile benchmark codes automatically

What type of PR is this：

[ ] bug
[ ] feature
[x] enhancement
[ ] refactor
[ ] others

Which issues of this PR fixes ：

Fix problems below:

now benchmark codes which depend google-benchmark are not compiled by default, which will cause compile errors if nobody notice
google-benchmark lib is installed first in dev machine which is not controlled by sr.
benchmark lib is a very useful tool, so we can add a bench dir to accumulate scripts and base codes for developing later.
aws-sdk-cpp-1.9.179 build error.

Problem Summary(Required) ：

Checklist:

[ ] I have added test cases for my bug fix or my new feature
[ ] I have added user document for my new feature or new function

[FE PR Coverage Check]
:heart_eyes: pass : 0 / 0 (0%)

[FE PR Coverage Check]
:heart_eyes: pass : 0 / 0 (0%)

run starrocks_admit_test

run starrocks_admit_test

run starrocks_admit_test

run starrocks_admit_test image


Added end-device installation manual to README.md

Checked and those are just instruction which are not in conflict with the code


Initial development discussion

This is to link to the initial discussion about the development of this pipeline:
https://github.com/alan-turing-institute/dymechh/issues/26

I'm going to be on leave for the 24 Nov. catch-up meeting, but here there are notes on the status for @AoifeHughes to update the team.


Autoscroll

When typing things, it doesn't automatically scroll down when you get to the bottom of the editor, you have to manually scroll so you can carry on seeing what you're typing.

Thanks for reporting @joedmck. I'll try to investigate what's the best way to sync the two of them, and see what can be done.

No problem @aero31aero, maybe have the left half as the "Easier on the eyes" color, and the right side white?


Hydra being slow to be scheduled causing bors to timeout

Context

Buildkite has a timeout. Hydra has timeouts. Bors waits on both of them to pass. Bors also has a timeout.
Test Case

N/A
Failure / Counter-example
https://github.com/input-output-hk/cardano-wallet/pull/2235#issuecomment-707697053

Resolution

QA

Stale, closing


Best way to backup the drupal vm?

Issue Type

Support Request

Your Environment
Vagrant 1.8.5 for Windows
VirtualBox 5.1.12 (Oracle)
Your OS

Windows 10

Summary
What is the best way to backup my Drupal VM?
Backup all at once,  backup important parts.
If there is a problem in the future, how can I then restore some of the working backups?
Thank you.

One of the main reasons for using Drupal VM is to have more-or-less ephemeral development environments. I often destroy and rebuild my VMs at least on a weekly basis, sometimes more frequently if I'm testing new infrastructure changes.
Because of that, there's no official/simple backup procedure. However, if you do need to be able to recover a VM, you'd back it up like any other VirtualBox VM—you can do snapshots through VirtualBox (or even triggered through a Vagrant plugin), and you can backup the VM files wherever you have VirtualBox set to store them.

Thank you.
I made a snapshot in Orvacle VM VirtualBox.

Perfect! See also: https://www.vagrantup.com/docs/cli/snapshot.html


Prevent user from multiple clics on pay button

Describe the bug
Hello,
It's possible to spam clic the payment button and this behavior must not be possible. Several cases has caused some unexpected webhook notifications on our side because the user was able to send multiple queries with few millisec of interval.
Our guess is that users either have a bad network connection or accidentally double-click the button.
To Reproduce
I was able to reproduce it with card payment, I didn't tried with other payment methods.
Steps to reproduce :

Put correct payment infos
Spam clic the Pay button or paste that script in the console :

document.getElementsByClassName("adyen-checkout__button__text")[0].click();
document.getElementsByClassName("adyen-checkout__button__text")[0].click();
document.getElementsByClassName("adyen-checkout__button__text")[0].click();
document.getElementsByClassName("adyen-checkout__button__text")[0].click();
document.getElementsByClassName("adyen-checkout__button__text")[0].click();
document.getElementsByClassName("adyen-checkout__button__text")[0].click();
document.getElementsByClassName("adyen-checkout__button__text")[0].click();

The dropin is sending multiple payments queries

Expected behavior
When the pay button is clicked, the button is disabled while the http query is sent.
Desktop (please complete the following information):

OS: Mac OS Sonoma
Browser Chrome
Version 125.0.6422.113

Hey @jmar212 ,
Which version of the Drop-in are you using? Did you by any change set the setStatusAutomatically to false?

I've come across a similar issue, not directly related to using the drop-in's own payment button, but instead using a custom button that calls the DropInElement.submit() method, and a drop-in with a configuration with showPayButton: false.
i.e.
// mounting the drop-in.
this.adyenDropin = this.adyenCheckout.create("dropin");
this.adyenDropin.mount("#adyen-dropin-container");
...

// later on in my custom button's handler
this.adyenDropin.submit();

I was mistakenly not disabling my custom button when it was clicked/tapped, meaning you could click it multiple times, in turn invoking this.adyenDropin.submit() multiple times too. If the card details in the drop-in are valid, this results in multiple successful payments being processed, despite the fact they're all linked to the same payment session, which I don't believe should be possible.
Web drop-in version: @adyen/adyen-web": "^5.66.0"

Hey @rsdev88  - if you are using the custom pay button, you are responsible for not letting Drop-in submit the payment multiple times as you have control of that by calling the submit() function. If you want us to have control over that, then do not use the custom pay button.
I am closing this thread the issue is not reproducible on the latest SDK version using the Adyen pay button.

Hi @ribeiroguilherme, I agree that in this situation I should prevent the custom button from calling submit() multiple times, but shouldn't there still be some deduplication in Adyen's backend based on the payment session ID? My understanding is that only one payment should be allowed per payment session ID, i.e. whichever endpoint the SDK is calling should be idempotent - or is that not true?

Hello @ribeiroguilherme,
Thanks for your reply!
I fixed the issue by calling in the onSubmit callback :  component.setStatus('loading');
I thought this behavior was managed automatically while the promise was resolved. I figured out after more research that this solution was working.


fix create tag on ui

example:

Wouldn't it be better to to that from specific form like release where you can also input tag message?

Agree, tags have messages, even if we don't display them yet, so there needs to be a form probably (thought I personally don't mind creating tags on CLI only).

I would considder this a feature or enhancement but not a bugfix

@codecov-io waiting result :)

Codecov Report

Merging #13467 (129e4cf) into master (3fd060e) will decrease coverage by 0.02%.
The diff coverage is 29.23%.

@@            Coverage Diff             @@
##           master   #13467      +/-   ##
==========================================
- Coverage   42.20%   42.17%   -0.03%
==========================================
  Files         695      695
  Lines       76368    76424      +56
==========================================
+ Hits        32228    32231       +3
- Misses      38862    38905      +43
- Partials     5278     5288      +10

Impacted Files
Coverage Δ

modules/auth/repo_branch_form.go
100.00% <ø> (ø)

modules/auth/repo_form.go
42.34% <ø> (ø)

routers/api/v1/repo/release.go
33.60% <0.00%> (ø)

routers/repo/release.go
23.74% <6.25%> (-0.98%)
:arrow_down:

routers/repo/branch.go
53.84% <8.33%> (-2.51%)
:arrow_down:

services/release/release.go
44.96% <45.71%> (+0.51%)
:arrow_up:

modules/git/repo_tag.go
61.68% <100.00%> (ø)

modules/util/timer.go
42.85% <0.00%> (-42.86%)
:arrow_down:

services/pull/check.go
48.90% <0.00%> (-3.65%)
:arrow_down:

services/pull/temp_repo.go
26.59% <0.00%> (-3.20%)
:arrow_down:

... and 7 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 3fd060e...129e4cf. Read the comment docs.


CentOS9/RHEL9: Migrate configuration files to /etc/redis

Pull Request (PR) description
Recent update in CentOS 9 Stream changed paths where configuration
files are installed and now these files are placed under /etc/redis
(since redis 6.0.9-2)[1].
This change updates the paths according to that migration[2].
[1] https://gitlab.com/redhat/centos-stream/rpms/redis/-/blob/8d691e9f5a8e9e01a060b624c40ff19680b6472e/redis.spec#L346
[2] https://gitlab.com/redhat/centos-stream/rpms/redis/-/commit/617715f9dabf108b475902585b9fc5283c0670da
This Pull Request (PR) fixes the following issues
n/a

CI is failing because of an issue with puppet-epel, which I'm fixing in https://github.com/voxpupuli/puppet-epel/pull/134 .

Just thinking out loud here: we don't need to ensure the old file is absent since there are few in place upgrades with EL. And if people do use leapp, leapp should take care of the move.

I'm looking at the code, but Redis is included in EL8 and EL9 so why do we still require EPEL in preinstall.pp on those OSes? We should also modify our helper to use the preinstall class. This probably means installing additional modules since they're soft dependencies. I opened https://github.com/voxpupuli/puppet-redis/pull/435. This does not yet exclude EPEL from EL8/EL9 (or rather, limit it to EL7), but it would be a good start for this.

Could you rebase this? I merged #435 and that should work. It removes the dependency on EPEL altogether for non-EL7.

Bleh, looks like bolt isn't built for EL9. From one problem to the next ... Personally I don't care for bolt and would be OK with excluding that on EL9 for now. Do you agree? Perhaps it also needs a ticket @ https://tickets.puppet.com/

Yeah I think that's reasonable. I've created a ticket to request puppet-bolt builds for CentOS 9, which I also mentioned in code comments.
https://tickets.puppetlabs.com/browse/MODULES-11275


feature reques: NACK support for udp packet lose

Hi, thanks for your interest in this project (that was written in about 24 hours some days ago, since i couldn't find a working and standalone RTSP server and i spent days trying to make gst-rtsp-server work with every possible input, and i failed).
NACKs are packets sent from a UDP server to a UDP client to signal some kind of errors, you mean that it would be nice if the server was able to detect packet losses from incoming streams (the ones sent by publishers) and send back NACKs when it happens?

yes,   ffmpeg's  rtsp  support nack.

The UDP streaming part of the protocol does not support NACK (neither does ffmpeg). Not part of the spec.  If you want re-transmit capability then RTSP is not the protocol.  ARQ style protocols, zixi and SRT offer this.


Add IPV6_BINDANY on FreeBSD

https://github.com/freebsd/freebsd/blob/master/sys/netinet6/in6.h#L493

r? @JohnTitor
(rust_highfive has picked a reviewer for you, use r? to override)

@bors r+

:pushpin: Commit 9578fa19428d051886aa464f8d67da6254da4137 has been approved by JohnTitor

:hourglass: Testing commit 9578fa19428d051886aa464f8d67da6254da4137 with merge 713a40e5283225a9239977a98c678027719063da...

:broken_heart: Test failed - checks-actions

 error: could not download file from 'static.rust-lang.org/rustup/release-stable.toml' to '/tmp/rustup-updateb91dXU/release-stable.toml'
error: caused by: failed to make network request
error: caused by: error sending request for url (static.rust-lang.org/rustup/release-stable.toml): connection error: Connection reset by peer (os error 104)
error: caused by: connection error: Connection reset by peer (os error 104)
error: caused by: Connection reset by peer (os error 104)

@bors retry

:hourglass: Testing commit 9578fa19428d051886aa464f8d67da6254da4137 with merge 6f48cce34f2d7da5063cc2e62c75765c07bdd232...

:broken_heart: Test failed - checks-actions

@bors retry

:hourglass: Testing commit 9578fa19428d051886aa464f8d67da6254da4137 with merge e4672151e8c245abe1304084e4fc7545b24b2806...

:broken_heart: Test failed - checks-actions

@bors retry

:hourglass: Testing commit 9578fa19428d051886aa464f8d67da6254da4137 with merge 5598401c182fc0289bc0f386651944624cb15581...

:sunny: Test successful - checks-actions, checks-cirrus-freebsd-11, checks-cirrus-freebsd-12, checks-cirrus-freebsd-13
Approved by: JohnTitor
Pushing 5598401c182fc0289bc0f386651944624cb15581 to master...


Bring back toggle render whitespace command

https://github.com/Microsoft/vscode/pull/11122#issuecomment-248019995
or expose API for the option

@alexandrudima is there any way to read the current whitespace settings like editor.getConfiguration().viewInfo.renderWhitespace from an extension?


Linux Homebrew

I have checked the following:

[X] I've searched existing issues and found nothing related to my issue.

Describe the feature you want to add
Linux build on homebrew would be nice
Mockups or Images of the feature
...

I believe this is not a feature that can be pursued as this application would be installed as a Cask which Linux homebrew explicitly does NOT support.

Right, flatpak is the way to go anyway


chore(deps): update pre-commit hook bridgecrewio/checkov to v2.3.356

This PR contains the following updates:

Package
Type
Update
Change

bridgecrewio/checkov
repository
patch
2.3.347 -> 2.3.356

Note: The pre-commit manager in Renovate is not supported by the pre-commit maintainers or community. Please do not report any problems there, instead create a Discussion in the Renovate repository if you have any questions.

Release Notes

bridgecrewio/checkov (bridgecrewio/checkov)
v2.3.356
Compare Source
Feature

terraform: Github Actions OIDC trust policy check - #5402

v2.3.355
Compare Source
v2.3.354
Compare Source
Feature

general: allow --var-file to be passed as environment variable - #5406
terraform: Add new policy to ensure AWS Transfer server only allows secure protocols - #5409

Platform

general: remove obsolete run config fallback API call - #5404

Documentation

gha: Update setup-python version in GitHub Actions.md - #5393

v2.3.353
Compare Source
v2.3.352
Compare Source
v2.3.351
Compare Source
Feature

terraform: new serialization methods for module and block - #5391

Bug Fix

terraform: pr for upgrade-checkov - #5400

v2.3.350
Compare Source
v2.3.349
Compare Source
Bug Fix

terraform: add TFDefinitionKey to get_entity_context_and_evaluations - #5392
terraform: consider new domain attribute in CKV2_AWS_19 - #5383

v2.3.348
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/run pipeline


Add Cassandra 3 support by using datastax java-driver for version 3

Currently Cassandra 3 is not working in DBeaver because some system tables were moved (see https://issues.apache.org/jira/browse/CASSANDRA-6717).
For example the table system.schema_keyspaces was moved to system_schema.keyspaces. Because of this the metadata can not be retrieved so the connection won't be established. This produces the following error message:

Datastax released a driver with Cassandra 3 support, version 3.0.0-rc1 (http://datastax.github.io/java-driver/). Using this driver should be enough to enable connections to Cassandra 3 servers.

I've changed driver to 3.0.rc1 work. Generally it works ok (on both Cassandra 2.x and 3.x). I had to change some model classes due to API changes, hopefully didn't break anything.
Do you have any CQL snippets I can test before release?

Here are a few queries, if you want to test more I would recommend https://docs.datastax.com/en/cql/3.0/cql/cql_reference/cqlCommandsTOC.html since it has plenty of examples.
CREATE KEYSPACE myKeyspace WITH REPLICATION = { 'class' : 'SimpleStrategy', 'replication_factor' : 3 };
CREATE TABLE myKeyspace.users (user_name varchar PRIMARY KEY, birth_year bigint);
INSERT INTO myKeyspace.users (user_name, birth_year) VALUES ('johndoe', 1970);
SELECT * FROM myKeyspace.users WHERE user_name = 'johndoe'
DELETE FROM myKeyspace.users WHERE user_name = 'johndoe'

Datastax has released stable Java Driver for Cassandra version 3.0.0 (http://www.datastax.com/dev/blog/datastax-java-driver-3-0-0-released). I would suggest using this version.

Ok, I'll take this into account, thanks for info.

Any updates on this? I don't mind using cqlsh so much but DBeaver is much nicer :D

Cassandra 3 driver will be added in version 3.6 (next one).

Excellent, thanks!

I can't see it in latest release 3.6.10, so whats happened?

Please clarify.
DBeaver 3.6+ uses DataStax driver 3.0.0.rc1.

I apologize for the ignorance, but I do not see anything related to Apache Cassandra or Datastax in Driver manager. I 'll really appreciate your help to resolve my problem. I also can't find any info about it,
P.S. I have a feeling that I misplaced the question, so sorry for this.

This is Community Edition.
In order to use Cassandra (and other NoSQL databases) you need Enterprise Edition (http://dbeaver.jkiss.org/download/enterprise/). It is also free.

Oh, I see... Thank you so much!

Even in 3.7.2 version, the client is not able to connect to Cassandra 3.0.3. Do we need to include any other dependency for the same, as the cassandra driver version is still showing as 2.x while creating a new connection

DBeaver uses DataStax driver 3.x which can connect to both Cassandra 2.x and 3.x. I'll fix driver description (which still says Cassandra 2.x).
Error above looks like some network issue (btw you can test it with telnet <ip> 9042).

Why do you guys keep the Community edition around, if Enterprise is free? I spent an hour trying to figure out where the Cassandra driver was...

Community edition is open-source, EE isn't.
And we have pretty silly web-site and very bad marketing. And "we" is actually "I" :)
Don't forget - DBeaver is still my hobby project.

it's not possible with community edition, you need enterprise edition as alreay mentioned.
However, it's not really free. Only the 2 weeks trial version is free.


syncbot: Unhandled rejection TypeError: Cannot read property 'username' of null

Function.fetchAuthorName (/usr/src/app/build/services/messenger/translators/front.js:98:94)
FrontTranslator.eventIntoMessages (/usr/src/app/build/services/messenger/translators/front.js:297:37)
Object.listenerMethod (/usr/src/app/build/services/messenger.js:28:50

This happened when a teammate had a username that didn't match between Discourse and the internal platforms (Front/Flowdock)


Add --base-types option for visualize textx command

By default base types are always rendered in the textx visualize command. That is distractive, especially for small models.
By default base types should be rendered only if explicitly asked for using --base-types CLI switch.

This is obsolete as there is no visualize command anymore and the base types will be removed. See #221


Cdp nlp service

One general comment - I'm not sure why the structure for this work is
health-patterns/services/nlp-insights/text-analytics/*
vs
health-patterns/services/nlp-insights/*
I don't see the value of the additional sub-folder for "text-analytics".  I think it could have been removed, but likely isn't worth it at this point (delay vs delivery)


investigate panic in TestDeleteService

Ilkers-MacBook-Pro:core ilgooz$ go test ./...
ok  	github.com/mesg-foundation/core/api	2.148s
ok  	github.com/mesg-foundation/core/api/client	0.858s
--- FAIL: TestDeleteService (0.00s)
panic: resource temporarily unavailable [recovered]
	panic: resource temporarily unavailable

goroutine 21 [running]:
testing.tRunner.func1(0xc4204560f0)
	/usr/local/Cellar/go/1.10.3/libexec/src/testing/testing.go:742 +0x29d
panic(0x1684260, 0x1acd668)
	/usr/local/Cellar/go/1.10.3/libexec/src/runtime/panic.go:502 +0x229
github.com/mesg-foundation/core/database/services.open(0x0, 0x17ca740, 0x1acd668)
	/Users/ilgooz/Programs/go/src/github.com/mesg-foundation/core/database/services/db.go:23 +0x19d
github.com/mesg-foundation/core/database/services.Save(0xc4203265f0, 0x0, 0x0, 0x0, 0x0)
	/Users/ilgooz/Programs/go/src/github.com/mesg-foundation/core/database/services/save.go:14 +0x97
github.com/mesg-foundation/core/api/core.(*Server).DeployService(0x1b340c8, 0x17d0840, 0xc4200220a8, 0xc420039598, 0xc4203bfa88, 0x2d2, 0x10f11c0)
	/Users/ilgooz/Programs/go/src/github.com/mesg-foundation/core/api/core/deploy.go:12 +0x32
github.com/mesg-foundation/core/api/core.TestDeleteService(0xc4204560f0)
	/Users/ilgooz/Programs/go/src/github.com/mesg-foundation/core/api/core/delete_test.go:24 +0x1d4
testing.tRunner(0xc4204560f0, 0x1775b50)
	/usr/local/Cellar/go/1.10.3/libexec/src/testing/testing.go:777 +0xd0
created by testing.(*T).Run
	/usr/local/Cellar/go/1.10.3/libexec/src/testing/testing.go:824 +0x2e0
FAIL	github.com/mesg-foundation/core/api/core	0.554s

may be related to https://github.com/mesg-foundation/core/issues/354

This bug didn't appear for long and the related issue #354 has been closed.
Closing this issue as well.


[BUG]Both pipenv and virtualenv/pip is being used

Detailed Description

Project structure contains both requirements.txt and Pipfile. As we are using pipenv, the former should there be no longer.
Possible Solution

Delete requirements.txt and change Travis CI setup.
Follow this link for reference.
Also change the "Adding dependencies" part of README.md

I don't think this should be done until we are entirely setup since a few programs don't support pipenv as of now and we don't want to limit ourselves.

@iit-technology-ambit/developers We will always be using both. requirements.txt is required for the backend while Pipfile makes it easy for development purposes.


⚠ Bofrost.es has degraded performance

In 9571d0f, Bofrost.es (https://www.bofrost.es) experienced degraded performance:

HTTP code: 200
Response time: 1439 ms

Resolved: Bofrost.es performance has improved in 01219ff after 6 minutes.


ipython showing up as vulnerable, but installed version looks OK

Hello, and thanks for the effort to create this!
I just tried out a test run against several projects. I bumped into this false positive result related to ipython.
$ pip-audit
Name         Version ID             Fix Versions
------------ ------- -------------- -----------------
...
ipython      7.27.0  PYSEC-2014-21  1.2.0
...

the installed ipython version is 7.27.0.
the vulnerable ipython version is 1.2.0 (also prevalent from the vuln-id that says 2014)

The right thing would have been to understand that the installed version is newer than the vulnerable version and not show this entry at all.
Let me know if I can help with any other information.

This seems to be an issue with the retrieved information from the crafted URL.
Trying different versions as declared in: https://pypi.org/project/ipython/#history
$ http https://pypi.org/pypi/ipython/7.26.0/json | jq -r .vulnerabilities
[
  {
    "aliases": [
      "CVE-2014-3429"
    ],
    "details": "IPython Notebook 0.12 through 1.x before 1.2 does not validate the origin of websocket requests, which allows remote attackers to execute arbitrary code by leveraging knowledge of the kernel id and a crafted page.",
    "fixed_in": [
      "1.2.0"
    ],
    "id": "PYSEC-2014-21",
    "link": "https://osv.dev/vulnerability/PYSEC-2014-21",
    "source": "osv"
  }
]

$ http https://pypi.org/pypi/ipython/7.27.0/json | jq -r .vulnerabilities
[
  {
    "aliases": [
      "CVE-2014-3429"
    ],
    "details": "IPython Notebook 0.12 through 1.x before 1.2 does not validate the origin of websocket requests, which allows remote attackers to execute arbitrary code by leveraging knowledge of the kernel id and a crafted page.",
    "fixed_in": [
      "1.2.0"
    ],
    "id": "PYSEC-2014-21",
    "link": "https://osv.dev/vulnerability/PYSEC-2014-21",
    "source": "osv"
  }
]

$ http https://pypi.org/pypi/ipython/7.28.0/json | jq -r .vulnerabilities
[]

$ http https://pypi.org/pypi/ipython/7.29.0/json | jq -r .vulnerabilities
[]

Thanks for the information @c00kiemon5ter!
From looking at the data source in OSV (which is where PyPI is getting the vulnerability data), it looks like the affected versions data is incorrect as it doesn't match with the introduced/fixed data.
CC: @di @oliverchang

Looks like this should be raised as an issue over at https://github.com/pypa/advisory-db instead.
As a side note, we should probably add an issue template here that directs people there for these types of issues.

Closing in favor of https://github.com/pypa/advisory-db/issues/36#issuecomment-965101008, thanks @c00kiemon5ter and @tetsuo-cpp!

As a side note, we should probably add an issue template here that directs people there for these types of issues.

Yep, I was just thinking that yesterday. I'll work on adding some issue templates today.


Rfsoc4x2

create function update, related to rfsoc new driver

I assume this is not yet ready, since the files contained are not changing substantially what it is in main.
In case, can you make it draft?
Otherwise, if I'm wrong, please ask for a review :)

sorry, I forgot about this PR... it was ready (it's merely an update to reflects the new driver).
However now the qubits will need a re-characterization.


Use BSD locks on macOS and OFD locks on Linux

Standard POSIX locks operate on an (inode, pid) pair and are released when any file descriptor for a file is closed by a process. A lock therefore risks being unexpectedly released if any operation within a process closes a file descriptor for which the process currently holds a lock.
While this is nicely solved by OFD locks in Linux, I've had to fall back to BSD locks on macOS as Darwin has no equivalent to OFD locks.

Node.js has tier 1 support for Linux >= 3.10 as of version 16, the current LTS. It changes to >= 4.18 in version 18 which will become the active LTS in October.


Python 3.11 not supported

Trying to run python with Azure Functions fails when using 3.11 (documentation says its supported)
func start
Found Python version 3.11.9 (py).
Python 3.6.x to 3.10.x is required for this operation. Please install Python 3.6, 3.7, 3.8, 3.9, or 3.10 and use a virtual environment to switch to Python 3.6, 3.7, 3.8, 3.9, or 3.10.

Close and Ignore
Core Tools needed update to 4.0.5348


CFFL

CFFL

Linter check found the following problems:
The following problems have been found:
ERROR: /tmp/abs_5fxxhq2y3c/clone/recipe/meta.yaml:29: missing_wheel: For pypi packages, wheel should be present in the host section
WARNING: /tmp/abs_5fxxhq2y3c/clone/recipe/meta.yaml:32: python_build_tool_in_run: The python build tool setuptools is in run depends
ERROR: /tmp/abs_5fxxhq2y3c/clone/recipe/meta.yaml:40: missing_pip_check: For pypi packages, pip check should be present in the test commands
ERROR: /tmp/abs_5fxxhq2y3c/clone/recipe/meta.yaml:47: incorrect_license: The recipe's about/license key is not an SPDX compliant license or license exception, closest match: NGPL
ERROR: /tmp/abs_5fxxhq2y3c/clone/recipe/meta.yaml:49: missing_documentation: The recipe is missing a doc_url or doc_source_url
WARNING: /tmp/abs_5fxxhq2y3c/clone/recipe/meta.yaml:49: missing_description: The recipe is missing a description
Errors were found


Add documentation about Linking.canOpenURL on iOS and promise rejection

The official Apple documentation about UIApplication::canOpenURL warns about making too many calls to this method under certain conditions.
I added this warning and a link to the page on the relevant React-Native doc page.
Moreover, I saw on the source code for iOS and Android that the promise can be rejected. Even though we could see it in the example source code, there was no clear documentation about it. I added explanations.

So should I target the 0.59 branch with this PR? Or open another PR?

In this PR you can copy the whole Linking.md file you updated over to website/versioned_docs/version-0.59/Linking.md, that will update Linking.md in 0.59

Okay thanks! Will add when the last comment is resolved 😄

@rickhanlonii just added the page for the 0.59 docs. Thanks for the review 😉

Looks good!

Thanks @thib92!


Use GH Action to login

based on PR feedback: https://github.com/Azure/reliable-web-app-pattern-dotnet/pull/180#pullrequestreview-1260782933
Explore:
https://github.com/marketplace/actions/azure-login#sample-workflow-that-uses-azure-login-action-to-run-az-cli

migrated to 1852557


Status Reason Transitions

[Enter feedback here]
Microsoft Docs says "This feature was introduced in CRM Online 2016 Update" but it is already available in CRM 2013.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 92c38601-a56d-411c-2f0f-332af2948a82
Version Independent ID: dfabdad6-11fc-ea0d-509c-ad8d48e1f844
Content: Define status reason transitions for case management (Dynamics 365 for Customer Service)
Content Source: ce/customer-service/define-status-reason-transitions-case-management.md
Service: dynamics-365-customerservice
GitHub Login: @anjgupta
Microsoft Alias: anjgup

GitHub user anjgupta has been removed from the MicrosoftDocs organization, so they were automatically removed as an assignee.

Hello @suri1547, the reference to "This feature was introduced in CRM Online 2016 Update" is no longer mentioned in the topic Define status reason transitions for case management. Please let us know if this addresses your issue.
Thank you.

Closing the issue after waiting for user response. There is no action item on the content.


Swift 4 version

I have created a Swift 4 version, based on the Scala implementation, and would like to submit a pull request.

Thanks, see https://github.com/delight-im/ShortURL/pull/27.


Text changes and additions in JSON files (EN and DE)

Hi there,
made some small text changes and additions.
Best regards,
Tobi

Hi @HelTob! Merged. Best wishes, DS


Deleting Digital Ocean cluster does not remove all droplets

What kind of request is this (question/bug/enhancement/feature request):
Bug
Steps to reproduce (least amount of steps as possible):

Create a Digital Ocean cluster
Create 1 node pool for etcd/controlplane - 1 node - 8GB, 2 CPU, SFO 2, ubuntu 18.04.3
Create 1 node pool for workers - 19 nodes - 1GB, 1 CPU, SFO 2, ubuntu 18.04.3
Leave other options default, click Create.
After cluster is created, delete the cluster.

Result:
10 of the 20 droplets were not removed in Digital Ocean after I removed the cluster.
Other details that may be helpful:
Logs -
rancher-logs.txt
Leftover droplets that didn't get deleted:

Tested on a 3 nodes cluster earlier and all nodes were removed. It's possible chances of reproducing this are higher when the cluster node size is larger.
Environment information

Rancher version (rancher/rancher/rancher/server image tag or shown bottom left in the UI):
v2.4.3
Installation option (single install/HA):
HA on k3s

Cluster information

Cluster type (Hosted/Infrastructure Provider/Custom/Imported):
Digital Ocean

Machine type (cloud/VM/metal) and specifications (CPU/memory):
see screen capture above

Kubernetes version (use kubectl version):
1.17.4

Docker version (use docker version):
19.03

Please prioritize this issue as it leads to cloud resource leakage!!!

Able to reproduce this issue when testing with rancher server version - v2.4.3 .

Create a Digital Ocean cluster
Create 1 node pool for etcd/controlplane/worker
Create 1 node pool for workers - 20 nodes
After cluster is created, delete the cluster.

10 nodes were delete .11 of the nodes were left behind in DO.

This is due to the high number of api calls we initiated from docker machine driver, which hits the rate limiting of their api and cause cascading failures. Can easily be reproduce with launching a large number of host at once. To fix the issue we will ned to increase the interval we call DO api and add clean up logic in the driver.

Available to test on 2.4-head and master.

The bug is reproduced with Rancher server rancher\rancher:v2.4-head version 8e20687a4
Steps:
Provision a 25 node cluster (1 etcd/control, 24 worker)
Wait for cluster to come up.
Delete cluster.
Result:
Saw nodes being recreated during cluster provisioning.
When deleting, these orphaned nodes do not delete.
Saw 1 etcd/control node and 2 worker nodes left over.

@aaronRancher Can you share the rancher server logs when you reproduced it? You should be able to see some ratelimiting logs. The original issue is caused by the rate limit we hit in our digitalocean api calls. Once we hit the limit there is no way to delete instances since Delete request will also fail due to the rate limiting. There are no good way to fix this other than increasing the interval of api calls in docker-machine(which is what I did). But it will eventually fail if we are increasing the number of droplets we provision at the same time since digitalocean only allow 250 requests/minute.
cc @maggieliu Let me know if this should be qualified as a known issue. The limit of droplets we can provision at the same time should be (250 / the number of request we hit when provisioning one droplets). Once rate limiting has been reached, there will be cascading failure in docker machine which cause the droplets failed to clean up.

Is it possible to retry the droplet delete if it fails due to rate limiting?

@dnoland1 I am hesitated to put a back-off retry logic into our machine controller, it requires a quite big change in our machine provisioning controller and I am not comfortable putting into a small patch release(2.4.x) to only address the rate limiting issue which is an edge case for only DO provider. I feel like we should have a recommended size for user to provision their node group using DO. My patch already mitigated the number of calls we need and possibly increase the limit to 20. If we can recommend user to only create node group with a specific range, I feel it should be sufficient.

Error logs seen while provisioning:
2020/05/20 22:06:23 [ERROR] NodeController c-gwgh2/m-zw65v [node-controller] failed with : Error creating machine: Error running provisioning: GET https://api.digitalocean.com/v2/droplets/193052721: 429 Too many requests

[ERROR] NodeController c-gwgh2/m-gcdw2 [node-controller] failed with : nodes.management.cattle.io "m-gcdw2" not found

Error from server (Forbidden): error when retrieving current configuration of:
Resource: "rbac.authorization.k8s.io/v1, Resource=clusterroles", GroupVersionKind: "rbac.authorization.k8s.io/v1, Kind=ClusterRole"
Name: "cattle-admin", Namespace: ""
Object: &{map["apiVersion":"rbac.authorization.k8s.io/v1" "kind":"ClusterRole" "metadata":map["annotations":map["kubectl.kubernetes.io/last-applied-configuration":""] "labels":map["cattle.io/creator":"norman"] "name":"cattle-admin"] "rules":[map["apiGroups":["*"] "resources":["*"] "verbs":["*"]] map["nonResourceURLs":["*"] "verbs":["*"]]]]}
from server for: "management-state/tmp/yaml-839299256": clusterroles.rbac.authorization.k8s.io "cattle-admin" is forbidden: User "u-5qr4rrquph" cannot get resource "clusterroles" in API group "rbac.authorization.k8s.io" at the cluster scope

Since this is specific to the DO API rate limit and based on @StrongMonkey comment of refactoring the rancher machine code heavily to handle this edge case, we can revisit this for one of our minor releases.


rework long-training example

Turns out --detaching is incompatible with the try/catch style the previous example used. With that pattern, the local environment was providing the durability, so the local process terminating would lead to the training "job" terminating.
Following a suggestion from @aksh-at, I reworked the example to use modal.Retries instead. This gives you up to 10 days of execution without manual interruption, which ought to be enough for anybody.
I also made some changes to improve the flow.
I now define the train function right at the top -- it roughly resembles the kind of function someone might bring to Modal, so it makes a great starting point. That means we can't use the @decorator style we normally use for Functions, but it's a small price to pay. I think we might want to use this alternative style more in our examples to make it more obvious that code can be brought in from elsewhere, without the Modal integration being defined "in-line".
I dropped the nvidia/cuda image. The -base image doesn't bring in anything we either don't have already or that PyTorch doesn't install on its own. We only need it for things like host-managed JIT kernel compilation with nvrtc or libraries that expect CUDA to be installed system-wide.
I split the definition of the resources used in the app.function call out from the call itself. This gives us more room to explain them, which is nice in cases like this one where we need to explain several (timeout, retries, and volumes).
I moved all of the Lightning code into the bottom of the file, after the local_entrypoint -- out-of-sight without requiring a separate file.
Finally, I added experiment IDs so that our re-execution of the example in synmon would actually exercise most of the logic (not all: the data on the volume is persistent).

🚀 The docs preview is ready! Check it out here:     https://modal-labs-examples--frontend-preview-6a2354c.modal.run

🚀 The docs preview is ready! Check it out here:     https://modal-labs-examples--frontend-preview-b707869.modal.run

Thanks for updating!

That means we can't use the @decorator style we normally use for Functions, but it's a small price to pay. I think we might want to use this alternative style more in our examples to make it more obvious that code can be brought in from elsewhere, without the Modal integration being defined "in-line".

My personal preference here is to still use a thin, decorated function that calls the train function defined on top. Although decorators are just higher-order functions, IMO we should be consistent with mostly using them as decorators so it doesn't confuse users who don't know much Python (which, sadly, is a big group).


Get Node importance from any model

From now on, we recommend using our discussion forum (https://github.com/rusty1s/pytorch_geometric/discussions) for general questions.
❓ Questions & Help
Hello!
I am trying to find a method that can give me back node importance. GNNExplainer explains the importance of the features for each node, but is there an analogous way that i could get back an importance for each node?
Please let me know if further information is required!
Thank you for your time.

I think you can modify the GNNExplainer class in order to do that. In particular, you may want to introduce a learnable node mask (instead of learning feature importance).

Got it thank you! So i have to change the source code of the GNNExplainer correct? Specifically i would have to change the following part of the __set_masks__ to the following:
From this:
`def set_masks(self, x, edge_index, init="normal"):
(N, F), E = x.size(), edge_index.size(1)
    std = 0.1
    self.node_feat_mask = torch.nn.Parameter(torch.randn(F) * 0.1)

    std = torch.nn.init.calculate_gain('relu') * sqrt(2.0 / (2 * N))
    self.edge_mask = torch.nn.Parameter(torch.randn(E) * std)

    for module in self.model.modules():
        if isinstance(module, MessagePassing):
            module.__explain__ = True
            module.__edge_mask__ = self.edge_mask`

To this:
'def set_masks(self, x, edge_index, init="normal"):
(N, F), E = x.size(), edge_index.size(1)
    std = 0.1
    self.node_feat_mask = torch.nn.Parameter(torch.randn(N) * 0.1)

    std = torch.nn.init.calculate_gain('relu') * sqrt(2.0 / (2 * F))
    self.edge_mask = torch.nn.Parameter(torch.randn(E) * std)

    for module in self.model.modules():
        if isinstance(module, MessagePassing):
            module.__explain__ = True
            module.__edge_mask__ = self.edge_mask'

Also would i use the explain_graph method or the the explain_node method? I would assume the former?
If it is the former, at least for me it is not working currently - please see the following traceback take from the gnn_explainer.py example:
`device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = Net().to(device)
data = data.to(device)
optimizer = torch.optim.Adam(model.parameters(), lr=0.01, weight_decay=5e-4)
x, edge_index = data.x, data.edge_index
for epoch in range(1, 11):
model.train()
optimizer.zero_grad()
log_logits = model(x, edge_index)
loss = F.nll_loss(log_logits[data.train_mask], data.y[data.train_mask])
print('Epoch {:4d} | Loss: {:.4f}'.format(epoch, loss))
loss.backward()
optimizer.step()
explainer = GNNExplainer(model, epochs=10, return_type='raw')
node_idx = 11
node_feat_mask, edge_mask = explainer.explain_graph(x, edge_index)
ax, G = explainer.visualize_subgraph(node_idx, edge_index, edge_mask, y=data.y)
plt.show()`
This gives the following error:
`---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
 in
3
4 node_idx = 11
----> 5 node_feat_mask, edge_mask = explainer.explain_graph(x, edge_index)
6 ax, G = explainer.visualize_subgraph(node_idx, edge_index, edge_mask, y=data.y)
7 plt.show()
~/anaconda3/envs/gcn_env/lib/python3.8/site-packages/torch/nn/modules/module.py in getattr(self, name)
945             if name in modules:
946                 return modules[name]
--> 947         raise AttributeError("'{}' object has no attribute '{}'".format(
948             type(self).name, name))
949
AttributeError: 'GNNExplainer' object has no attribute 'explain_graph'`
Please let me know if you nee more information.
Thank you!

This looks correct to me. I think the cleanest way to achieve that is to simply inherit from GNNExplainer and apply the necessary changes there. If you want to explain node-level predictions, you have to use explain_node. If you want to explain graph-level predictions, you have to use explain_graph. If the explain_graph method does not exist for you, I suggest you to upgrade PyG to version 1.7.2.

Hello! thank you for your comments -  i have implemented them and here is the code below for explaining node importance on the graph by using the explain_graph method. This piece of code worked, but i am still attaching it if you want to go over it really quick, or for other people to have access to.
from copy import copy
from math import sqrt
from typing import Optional

import torch
from tqdm import tqdm
import networkx as nx
from torch_geometric.nn import MessagePassing
from torch_geometric.data import Data
from torch_geometric.utils import k_hop_subgraph, to_networkx

class MyExplainer(GNNExplainer):

    def __init__(self,model, epochs: int = 100, lr: float = 0.01,
                 num_hops: int = None, return_type: str = 'log_prob',
                 log: bool = True):
        super(GNNExplainer, self).__init__()

        assert return_type in ['log_prob', 'prob', 'raw']
        self.model = model
        self.epochs = epochs
        self.lr = lr
        self.__num_hops__ = num_hops
        self.return_type = return_type
        self.log = log

    def __set_masks__(self, x, edge_index, init="normal"):
        (N, F), E = x.size(), edge_index.size(1)

        std = 0.1
        self.node_feat_mask = torch.nn.Parameter(torch.randn(N) * 0.1)

        std = torch.nn.init.calculate_gain('relu') * sqrt(2.0 / (2 * F))
        self.edge_mask = torch.nn.Parameter(torch.randn(E) * std)

        for module in self.model.modules():
            if isinstance(module, MessagePassing):
                module.__explain__ = True
                module.__edge_mask__ = self.edge_mask

    def explain_graph(self, x, edge_index, **kwargs):
        r"""Learns and returns a node feature mask and an edge mask that play a
        crucial role to explain the prediction made by the GNN for a graph.

        Args:
            x (Tensor): The node feature matrix.
            edge_index (LongTensor): The edge indices.
            **kwargs (optional): Additional arguments passed to the GNN module.

        :rtype: (:class:`Tensor`, :class:`Tensor`)
        """

        self.model.eval()
        self.__clear_masks__()

        # all nodes belong to same graph
        batch = torch.zeros(x.shape[0], dtype=int, device=x.device)

        # Get the initial prediction.
        with torch.no_grad():
            out = self.model(x=x, edge_index=edge_index, batch=batch, **kwargs)
            log_logits = self.__to_log_prob__(out)
            pred_label = log_logits.argmax(dim=-1)

        self.__set_masks__(x, edge_index)
        self.to(x.device)

        optimizer = torch.optim.Adam([self.node_feat_mask, self.edge_mask],
                                     lr=self.lr)

        if self.log:  # pragma: no cover
            pbar = tqdm(total=self.epochs)
            pbar.set_description('Explain graph')

        for epoch in range(1, self.epochs + 1):
            optimizer.zero_grad()

            h = x * self.node_feat_mask.view(-1,1).sigmoid()
            print(h.shape)
            out = self.model(x=h, edge_index=edge_index, batch=batch, **kwargs)
            log_logits = self.__to_log_prob__(out)
            loss = self.__loss__(-1, log_logits, pred_label)
            loss.backward()
            optimizer.step()

            if self.log:  # pragma: no cover
                pbar.update(1)

        if self.log:  # pragma: no cover
            pbar.close()

        node_feat_mask = self.node_feat_mask.detach().sigmoid()
        edge_mask = self.edge_mask.detach().sigmoid()

        self.__clear_masks__()
        return node_feat_mask, edge_mask

explainer = MyExplainer(model, epochs=10, return_type='raw')

node_feat_mask, edge_mask = explainer.explain_graph(x, edge_index)

This returns a node mask (importances for each node) of size 2708 ( equal to the number of nodes in the graph).
Please let me know if you have any comments! Thanks again for your time

Also, could you please explain why when i am running the explain_graph method multiple times, the top most important node feature ( or node in my case) changes every time?
Seems like even in the example gnn_explainer.py the method outputs a different node feature as the most important every time i run it.
Thank you!

Regarding the unstable performances of GNNExplainer, this thread might be of interest to you.

Thank you for pointing me to the thread, however lowering the lr did not help in my case. I tried with lower lr and higher number of epochs. I am posting the loss achieved at each epoch below:
2 3.496821403503418
3 3.3645520210266113
4 3.1787679195404053
5 3.413111686706543
6 3.1267714500427246
7 3.1029510498046875
8 3.6045148372650146
9 2.735372304916382
10 3.201169490814209
11 3.5895602703094482
12 2.9845454692840576
13 3.443255662918091
14 3.0134196281433105
15 3.0687482357025146
16 2.8410656452178955
17 3.2408909797668457
18 3.412515163421631
19 3.6745805740356445
20 3.0907177925109863
21 3.1836471557617188
22 3.3268399238586426
23 3.356376886367798
24 2.931065082550049
25 3.316051721572876
26 3.0394697189331055
27 3.263899564743042
28 3.088510513305664
29 3.073406219482422
30 3.2552621364593506
31 3.2704055309295654
32 3.5216448307037354
33 3.35966157913208
34 2.9769442081451416
35 3.6151528358459473
36 2.9984025955200195
37 3.1369500160217285
38 2.5288407802581787
39 3.3873307704925537
40 3.114293098449707
41 3.1227338314056396
42 3.0890815258026123
43 2.7845048904418945
44 3.258423089981079
45 2.510782241821289
46 3.0890111923217773
47 3.640535354614258
48 3.1954450607299805
49 3.132293701171875
50 3.7218129634857178
51 3.0036375522613525
52 2.980241537094116
53 2.957766056060791
54 2.9930639266967773
55 3.3926398754119873
56 3.380021810531616
57 3.180299997329712
58 3.0834662914276123
59 3.351193428039551
60 2.9332754611968994
61 2.9379701614379883
62 3.3295295238494873
63 3.3983876705169678
64 3.043132781982422
65 3.0385308265686035
66 3.442775011062622
67 3.0498578548431396
68 3.1381309032440186
69 3.099196195602417
70 3.474531888961792
71 3.5652389526367188
72 3.278151512145996
73 3.3231992721557617
74 3.1291697025299072
75 3.050398111343384
76 3.3383052349090576
77 3.2084426879882812
78 3.2853777408599854
79 2.8490824699401855
80 3.1916651725769043
81 3.57133412361145
82 3.1943612098693848
83 2.915182113647461
84 3.647850275039673
85 3.427914619445801
86 2.8212649822235107
87 3.1519296169281006
88 3.3894546031951904
89 2.772606611251831
90 3.212118148803711
91 3.0083513259887695
92 3.4693596363067627
93 3.2660067081451416
94 3.563992738723755
95 3.38681697845459
96 2.973496198654175
97 3.5036866664886475
98 3.5181024074554443
99 3.3292760848999023
100 3.434509515762329```

Is there an explanation for the `GNNExplainer` not converging? Is it because its trying to optimize the mask, and not improve the prediction of the model?

It's hard to say why the GNNExplainer is not converging. In the end, GNNExplainer tries to push the soft mask values close 0 and 1 so that the model predictions do not change. You might also try to change the hyperparameters in GNNExplainer.coeffs, which might not be optimal for your task.


Code cleanup and version parsing modification

I've made a couple of changes based on our discussion of #3. The biggest one is to move the version info into a separate file, which maintains the version info in a self contained manner, and can be imported by both top level __init__.py and in setup.py. This is less error prone (in my opinion) than trying to parse python code with regex in setup.py.
I also added tags to my fork of the repo (https://github.com/madphysicist/easy-pil). I can't push the tags to you directly, but here are the commands I used to create them:
$ git tag -a v0.0.1 -m 'Version 0.0.1 Stable' 9dca57fa2ed1f6f29884f2b529859341d630f2a0
$ git tag -a v0.0.3 -m 'Version 0.0.3 Stable' 7c229810640d424f2fad0e837330bd8630d8b819
$ git tag -a v0.0.4 -m 'Version 0.0.4 Stable' b435c7996d0eadef355c000ab489369dcb48edf0
$ git tag -a v0.0.5 -m 'Version 0.0.5 Stable' ef226d13f4b4d8074f4545f9cb31b046431d9332
$ git tag -a v0.0.6 -m 'Version 0.0.6 Stable' 39af809d89906de4c5766a6698cd54c774903c16
$ git tag -a v0.0.7 -m 'Version 0.0.7 Stable' 69958d066725b2c0242e6c8e6a564f3e786a1469
$ git tag -a v0.0.8 -m 'Version 0.0.8 Stable'<PHONE_NUMBER>e8bcb972ce21c3839d38bb7659b6e0
$ git tag -a v0.1.0 -m 'Version 0.1.0 Stable' cf259c0f9d370506d8d0bc2ef521f040467499a3
$ git tag -a v0.1.1 -m 'Version 0.1.1 Stable' 2624d3d5b2575438554f3ef5bdeb06d3781a05c4
$ git push --tags

I place the tag immediately before you change version numbers, so someone checking out the tag gets the latest and greatest stable code with that version number, and not the initial switchover. If you use feature/development branches, which you squash when merging to master, each commit in master will roughly correspond to a micro version increment.
Please let me know your thoughts. I'd be happy to change anything you don't like or would like to see added to this PR.

There is a problem tho, str.removesffix is a py3.9+ only method


transactionList is loading

HI:
Today, I deployed pinpoint。 When i visit "http://x.x.x.x/#/transactionList/Pay-fintech-receipt@TOMCAT/20m/2020-02-26-16-10-41"，it is always loading。How can i resolve it ?

hi @xiaoxinxin85
There will be an request that has error on that page.
If you refer to following link, the you can check all request on that page.
Please post request that has error in xhr tab and error message.
https://developers.google.com/web/tools/chrome-devtools/network
thanks :)

HI，koo-taejin：
Below are screenshots of all requests：

It  might be related with this issue (#6324)
Please retry with 2.0.0-RC4 version.


Refactored CSS in pages after the login

Description
Refactored CSS in pages after the login
Fixes #234
Status
READY
Type of change

New feature (non-breaking change which adds functionality)

Checklist:

[ ] I have made corresponding changes to the documentation (if applicable)
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] New and existing unit tests pass locally with my changes

Aguardando revisão.


CIF-1018 - The demo store generated from the archetype with custom parameters is missing styling

fixed the policy path in the templates to honor the appsFolderName property

Description
The default styling is not present for the demo store pages generated from the archetype with custom parameters, particularly when the appsFolderName property is not set to "venia".
Related Issue
CIF-1018
Motivation and Context

How Has This Been Tested?
Manually.
Screenshots (if appropriate):
Types of changes

[X] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Checklist:

[ ] I have signed the Adobe Open Source CLA.
[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[X] I have read the CONTRIBUTING document.
[ ] I have added tests to cover my changes and the overall coverage did not decrease.
[X] All unit tests pass on CircleCi.
[X] I ran all tests locally and they pass.

Verified using locally generated project of this branch.


feat: native systemd support wip

Turbo draft.
TODO:

[ ] figure out user sessions
[ ] add better logging to shim
[ ] rename shim
[ ] make sure nothing else explodes

Workaround for user sessions: sudo loginctl enable-linger $USER

See also: https://github.com/microsoft/WSL/issues/8842

For logging, you could use something like
.../activate |& logger --socket-errors=off -st activate 2>/dev/kmsg

to make the log output appear in dmesg
Systemd can be started with --log-target=kmsg to achieve that as well (though I haven't tested that)


Per-guild locale system

This was a request by だれも#4003 on Discord. The idea is to take every message in Gameboi and translate it into various different languages. This would have to be primarily outsourced to native speakers of other languages for the actual translation, but it would be relatively simple, just time-consuming.
Possible starter languages:

French ( だれも#4003)
Russian (?)
UK English (ThatTonybo#0001, colour not color :P)
German (I Al Istannen#1564?)
Turkish (icomewitheightkilogramsofsadness#0340)

If you wanted localization to be a big thing, you could also look into a software like (Weblate)[https://weblate.org/en/hosting/] and self-host it, this would make it easy to translate and would allow for many languages, but you could also just do it through files ;)

If you write a locale system, I could translate it to german. Or try to :P

Hello, I can translate it to Czech... Or try it :D


misleading exception when node name starts with number

Just a minor thing, the reason is clear:
n = Node(name='1node1')

AssertionError: Illegal characters in name 1node1. You can only use letters and numbers, and _

"You can only use letters and numbers" for "1node1" is misleading, it should say something like "must be valid python identifier" maybe?


TypeError: cannot read property 'HTTP' of undefined

The error message here is not very important. As we have raised in other issues, there still seems to be a way of writing modules that require does not work on LLRT.
const a = require('@aws-sdk/client-rds-data')

% llrt ./src/index.js
TypeError: cannot read property 'HTTP' of undefined
  at <anonymous> (/Users/shinya/Workspaces/hono-test/node_modules/@smithy/util-endpoints/dist-cjs/index.js:200:36)
      at <anonymous> (/Users/shinya/Workspaces/hono-test/node_modules/@aws-sdk/util-endpoints/dist-cjs/index.js:62:29)
      at <anonymous> (/Users/shinya/Workspaces/hono-test/node_modules/@aws-sdk/middleware-user-agent/dist-cjs/index.js:41:29)
      at <anonymous> (/Users/shinya/Workspaces/hono-test/node_modules/@aws-sdk/client-rds-data/dist-cjs/index.js:63:36)
      at <anonymous> (/Users/shinya/Workspaces/hono-test/src/index.js:6:11)
      at <anonymous> (eval_script:1:5)

By the way, if you load @smithy/util-endpoints, you can see the difference in behavior from Node.js as follows.
@smithy/util-endpoint (with llrt-dawrin-arm64-no-sdk):
const a = require('@smithy/util-endpoints')
console.log(a)

% llrt ./src/reproduction.js
{}

% node ./src/reproduction.js
{
  EndpointCache: [Getter],
  EndpointError: [Getter],
  customEndpointFunctions: [Getter],
  isIpAddress: [Getter],
  isValidHostLabel: [Getter],
  resolveEndpoint: [Getter]
}

What is even stranger is that when I run the reproduced program with the part that was in error extracted, it works.
var import_types3 = require("@smithy/types");
var DEFAULT_PORTS = {
  [import_types3.EndpointURLScheme.HTTP]: 80,              // -> @smithy/util-endpoints/dist-cjs/index.js:200:36
  [import_types3.EndpointURLScheme.HTTPS]: 443
};
console.log(DEFAULT_PORTS);  // debug

% llrt ./src/reproduction.js
{
  http: 80,
  https: 443
}

% node ./src/reproduction.js
{ http: 80, https: 443 }

Even stranger behavior included the following.

When modules that have no dependencies on each other are loaded.

var a = require("tinybench");
//const a = require('@smithy/types')
const b = require('@smithy/util-endpoints')
console.log(b)

% llrt ./src/reproduction.js
{}

% node ./src/reproduction.js
{
  EndpointCache: [Getter],
  EndpointError: [Getter],
  customEndpointFunctions: [Getter],
  isIpAddress: [Getter],
  isValidHostLabel: [Getter],
  resolveEndpoint: [Getter]
}

If a module with prior dependencies is loaded (but the variable to be assigned is irrelevant)

//var a = require("tinybench");
const a = require('@smithy/types')
const b = require('@smithy/util-endpoints')
console.log(b)

% llrt ./src/reproduction.js
TypeError: cannot read property 'HTTP' of undefined
  at <anonymous> (/Users/shinya/Workspaces/hono-test/node_modules/@smithy/util-endpoints/dist-cjs/index.js:200:36)
      at <anonymous> (/Users/shinya/Workspaces/hono-test/src/reproduction.js:3:11)
      at <anonymous> (eval_script:1:5)

% node ./src/reproduction.js
{
  EndpointCache: [Getter],
  EndpointError: [Getter],
  customEndpointFunctions: [Getter],
  isIpAddress: [Getter],
  isValidHostLabel: [Getter],
  resolveEndpoint: [Getter]
}

Apparently there are two issues.

It is not possible to load a module like @smithy/types.
If the same module has been pre-required, it has some effect on the second and subsequent requirments.

The reason why it differs from node is because we're bundling the SDK with a "browser" platform

I may have mentioned this issue too soon and may have confused you. The following are prerequisites.

Binaries are built with no-sdk. In other words, @smithy does not bundle anything.
I am now using a require that can read node_modules that are being tested in another PR.

Incidentally, the bytecode cache contained in the binary being tested has the following status.

I thought it was a strange condition since it reproduces in this situation.

Hi @richarddavison , The situation was slightly improved by the excellent response of #611.
// reproduction.js
const a = require('@smithy/util-endpoints')
console.log(a)

Execution results by llrt-dawrin-arm64-no-sdk:
% llrt ./src/reproduction.js
{
  EndpointCache: [class: EndpointCache],
  EndpointError: [class: EndpointError],
  customEndpointFunctions: {},
  isIpAddress: [function: isIpAddress],
  isValidHostLabel: [function: isValidHostLabel],
  resolveEndpoint: [function: resolveEndpoint]
}

% node ./src/reproduction.js
{
  EndpointCache: [Getter],
  EndpointError: [Getter],
  customEndpointFunctions: [Getter],
  isIpAddress: [Getter],
  isValidHostLabel: [Getter],
  resolveEndpoint: [Getter]
}

However, the following events do not seem to have been resolved yet.
// reproduction.js
//const a = require("tinybench")
const a = require('@smithy/types')
const b = require('@smithy/util-endpoints')
console.log(b)

Execution results by llrt-dawrin-arm64-no-sdk:
% llrt ./src/reproduction.js
TypeError: cannot read property 'HTTP' of undefined
  at <anonymous> (/Users/shinya/Workspaces/hono-test/node_modules/@smithy/util-endpoints/dist-cjs/index.js:200:36)
      at <anonymous> (/Users/shinya/Workspaces/hono-test/src/reproduction.js:3:11)
      at <anonymous> (eval_script:1:5)

% node ./src/reproduction.js
{
  EndpointCache: [Getter],
  EndpointError: [Getter],
  customEndpointFunctions: [Getter],
  isIpAddress: [Getter],
  isValidHostLabel: [Getter],
  resolveEndpoint: [Getter]
}

@richarddavison , I have created a slightly longer but reproducible code. The Node.js package contains code that was transpiled from TS to CJS, and it seems likely that those boilerplate codes are affected.
//require7.js
// Boilerplate when generating CJS from TS
var __defProp = Object.defineProperty;
var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
var __getOwnPropNames = Object.getOwnPropertyNames;
var __hasOwnProp = Object.prototype.hasOwnProperty;
var __export = (target, all) => {
  for (var name in all)
    __defProp(target, name, { get: all[name], enumerable: true });
};
var __copyProps = (to, from, except, desc) => {
  if (from && typeof from === "object" || typeof from === "function") {
    for (let key of __getOwnPropNames(from))
      if (!__hasOwnProp.call(to, key) && key !== except)
        __defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });
  }
  return to;
};
var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);

// Transpiled code based on logic written in actual TS
var src_exports = {};
__export(src_exports, {
  prop: () => prop
});
module.exports = __toCommonJS(src_exports);

var prop = {
  name: "require7",
};

0 && (module.exports = {
  prop,
});

Imagine that require7 is a module used universally in a variety of packages. If the object is accessed after the require has been executed only once, the information can be obtained correctly.
// index7.js
var mod = require("./require7.js");
console.log(mod.prop.name);

% llrt index7.js
require7

% node index7.js
require7

However, accessing an object after requiring the same package more than once will result in an error.
// index7.js
var dmy = require("./require7.js");
var mod = require("./require7.js");
console.log(mod.prop.name);

% llrt index7.js
TypeError: cannot read property 'name' of undefined
  at <anonymous> (index7.js:3:22)
      at <anonymous> (eval_script:1:5)

% node index7.js
require7

Is this still present after last commit?

Yes, I am verifying the source for the latest Commit (#1ae01a2) by building it on my laptop.


https://pump.fun/api/ipfs returning 500

The createAndBuy function uses https://pump.fun/api/ipfs to create token Metadata, and the endpoint returns 500 code. Is there another way to create tokens on Pumpfun? Or to manually generate the token Metadata?
https://github.com/rckprtr/pumpdotfun-sdk/blob/3f38ca32609ccc4d2a78a7ecfcb357648dee387b/src/pumpfun.ts#L405

I just checked, it should be working, is it possible the upload failed or your values are incorrect?

I just checked, it should be working, is it possible the upload failed or your values are incorrect?

Thanks! I was able to solve my issue by manually creating the Blob file. Here is the code snippet:
  private async deployAndSnipe() {
    try {
      const mint = this.getOrCreateKeypair('./pumpfunKeys', 'mint');
      const filePath = 'random.png';
      const fileBlob = await this.createBlobFromFile(filePath);
      const tokenMetadata: CreateTokenMetadata = {
        name: 'TST-7',
        symbol: 'TST-7',
        description: 'TST-7: token',
        file: fileBlob,
      };

      const createResult = await this.pumpfunSDK.createAndBuy(
        this.keypair,
        mint,
        tokenMetadata,
        BigInt(0.0001 * LAMPORTS_PER_SOL),
        SLIPPAGE_BASIS_POINTS,
        {
          unitLimit: 250000,
          unitPrice: 250000,
        },
      );
    } catch (error) {
      console.error(`Pumpfun Sniper Error in deployAndSnipe(): ${error}`);
    }
  }

  private async createBlobFromFile(filePath: string): Promise<Blob> {
    return new Promise((resolve, reject) => {
      fs.readFile(filePath, (err, data) => {
        if (err) {
          return reject(err);
        }
        const blob = new Blob([data]);
        resolve(blob);
      });
    });
  }

Previously, I used
const tokenMetadata = {
    name: 'TST-7',
    symbol: 'TST-7',
    description: 'TST-7: token',
    file: 'path/to/file',
  };

as in the example.
My previous code was failing here. I may be missing something, but I did not find where the tokenMetadata is converted to CreateTokenMetadata.

It should be passed in as the Type, but yes the file path needs to be correct.  I could have better error handling here.


hot-upgrade: update crossbeam-utils to 0.8.x.

Motivation
Upgrade the crossbeam-utils crate to fix the vulnerable warning crossbeam-utils Race Condition vulnerability

Solution

/merge


Support formatting of entire documents

Since swift-syntax no longer depends on the C++ parser library and thus swift-format also doesn’t, we can use swift-format to format an entire document.
Fixes https://github.com/apple/sourcekit-lsp/issues/576
rdar://96159694

CC @allevato, I’d appreciate your review of how I’m calling swift-format’s API.

@swift-ci Please test Windows

@swift-ci test

Putting on hold until we can build swift-format on Windows.

Is there already an issue for this in swift-format? Doing a cursory search there I only found https://github.com/apple/swift-format/issues?q=is%3Aissue+is%3Aopen+windows

I changed the implementation to invoke swift-format as an executable instead of having SourceKit-LSP link against SwiftFormat.

@swift-ci Please test

https://github.com/apple/swift/pull/71003
@swift-ci Please test

https://github.com/apple/swift/pull/71003
@swift-ci Please test

@swift-ci Please test

@swift-ci Please test Windows


[Bug] overflow in the add doctor form

Is there an existing issue for this?

[X] I have searched the existing issues

Bug Description?
the form to add doctor overflows above and is not visible
Add Screenshots

What browsers are you seeing the problem on?
No response
Record

[X] I agree to follow this project's Code of Conduct
[ ] I'm a GSSOC contributor
[ ] I want to work on this issue (Optional)
[ ] I'm willing to provide further clarification or assistance if needed.

Hi,I would like to contribute to this issue

@thaya-rk okay


thread 'main' panicked at 'misaligned pointer dereference: address must be a multiple of 0x2 but is 0x7fbe4fedc8cb'

System information
EndeavourOS 6.4.7-arch1-1
Describe the bug
In the middle of developing https://github.com/planetoryd/netns-proxy , lapce-stable 0.2.8 crashed.
And when I tried to restart v0.2.8. (of lapce-stabe, and then lapce-debug compiled by cargo, both are 0.2.8)
$ lapce /space/netns-proxy
(totally nothing was printed. it crashed)
(happens consistently)

the one that crashed in the middle, which is the first occurrence. lapce.log
strace -o ./strace.log -f ./target/debug/lapce /space/netns-proxy, strace.log
./target/debug/lapce /space/netns-proxy lapce-debug.log

This is: #2463
As my comment says there,

This is due to a bug in Swash
However, we've fixed this in latest master - but of course latest master is missing various pieces of functionality due to the UI rewrite.

I believe the answer, since we've changed the UI backend and so we aren't doing new releases with the druid backend, is that you should build that old commit using 1.69/1.68.


BUG: javascript returns incorrect file download URL

See: https://github.com/mslw/tabby-utils/issues/6

Duplicate of #326

Thanks, I completely forgot about the previous issue!


Mscolab tutorial, TTS feature for audios

Created mscolab tutorial
Created audio.py file which when run in cd tutorials/ python audio.py produces mp3 files for all texts in the textfile folders.
We can choose our preffered language in which we want to translate the text file and thus creating the subsequent mp3 file for that text.
Fixed small bugs
Updated tutorials.txt requirements file

Made the suggested changes!

@ReimarBauer
Added all the changes you suggested. Updated the tutorials.txt requirements file.


Treatment of OSC bundles does not match OSC 1.0 spec

Been working on some interoperability stuff between Rust and SuperCollider, and the treatment of OSC bundles here does not match SC.
https://github.com/Wallacoloo/serde_osc/blob/master/src/de/pkt_deserializer.rs#L15-L19
The "OSC Bundles" heading on the spec page is pretty clear about emitting #bundle.

Hm...I might be wrong, sorry, I see that you do actually allow for reading incoming bundles tagged with #bundle. Try this readme out when you get a chance, if you have supercollider.
https://github.com/andrewcsmith/osc_server_example
I can't get it to work with python either. I see that there's a general example of deserializing packets in the docs, but nothing for bundles.

@andrewcsmith Take a look at the tests in this serde_osc repository if you haven't already. For example, this one shows the wire format that serde_osc will output for a bundle. It looks to be a 4-byte length (little endian), followed by "#bundle\0", 8-byte timetag, and then each message concatenated to that.
This looks to be what the spec claims, however it is worth noting that I never tried connecting serde_osc to an application that wasn't built using serde_osc.
Unfortunately I don't have the resources to really dig into this. If you can pinpoint exactly how (or if) serde_osc is serializing the bundle incorrectly (i.e. expected output of serialize vs actual output), I might be able to troubleshoot & fix that over some weekend. Otherwise, there's not much I can do here.

Upon re-reading that, I guess this issue is in using serde_osc to deserialize a packet that comes from supercollider. If that's the case, just dump the bytes of the bundle & post them here I can check how they differ from what serde_osc is expecting.
The expected format is here.


Ensure all data plane components in the path of requests output stack traces for 500 errors

WHAT:
Ensure all data plane components in the path of requests (authorino, limitador, wasm-shim) output stack traces for 500 errors when there is a server error originating from them

Authorino uses zap for structured logging. More details about how it's configured in https://docs.kuadrant.io/authorino/docs/user-guides/observability/#log-levels-and-log-modes
example log output
{"level":"info","ts":"2024-03-22T15:34:57Z","logger":"authorino","msg":"setting instance base logger","min level":"info","mode":"production"}
{"level":"info","ts":"2024-03-22T15:34:57Z","logger":"authorino","msg":"booting up authorino","version":"991b6ebc2b3b415d2e5b12f54c8fe8959b868212","cmd":"server"}
{"level":"info","ts":"2024-03-22T15:34:57Z","logger":"authorino","msg":"starting http auth service","port":5001,"tls":false}
{"level":"info","ts":"2024-03-22T15:34:57Z","logger":"authorino","msg":"starting grpc auth service","port":50051,"tls":false}

Limitador uses https://docs.rs/tracing-log/latest/tracing_log/ ("Adapters for connecting unstructured log records from the log crate into the tracing ecosystem")
The log crate is a logging facade.
Log levels can be set in limitador via the RUST_LOG env var.
Logging is not structured at this time.
As limitador compiles to a binary, stacktraces will not be 'proper' as symbols are not included in production images.
Example log output from limitador when something fails:
2024-03-22T16:16:44.334295Z ERROR should_rate_limit: limitador_server::envoy_rls::server: Error: Storage("Reconnecting failed: Connection refused (os error 61)")

Limitador recently switched to tokio-tracing for logging in https://github.com/Kuadrant/limitador/pull/250. It is a framework to collect structured info, so it should not be hard to structure log in any format you want.

wasm-shim is loaded as a container image inside envoy, so any logs from the wasm-shim are output in the envoy logs.
In the case of istio, this would be the istio gateway pod that runs envoy e.g.
kubectl get po -A | grep -i istio
...
kuadrant-system      api-gateway-istio-8748c5947-sxk8f

Example of log output in envoy
2024-03-26T12:33:04.818862Z	info	wasm	fetching image kuadrant/wasm-shim from registry quay.io with tag v0.3.0
2024-03-26T12:33:06.392767Z	info	Readiness succeeded in 1.695333064s
2024-03-26T12:33:06.392961Z	info	Envoy proxy is ready

log messages from wasm modules are proxied as strings, so you wouldn't get any structured logging in enovys log output


Allow for builds without WKT format

If an application doesn't make use of the geometry string methods, it should be possible to build the library without OpenLayers.Format.WKT.
With these changes, tests pass on Chrome 15 and IE 6.

This is good to merge.
I'm curious to know why you no longer want to rely on arguments.callee. Is this unsafe?

@elemoine: arguments.callee is deprecated.

A minor point: in the penultimate line of release notes, you have 'the the' (tried to edit this myself but short of forking your fork couldn't work out how to do it).

@ahocevar thanks, that's good to know.

And, while not important for this bit of code, js engines can't optimize functions that rely on in.  There is really no reason to use it.


chore: setup the workflows to cache

Added caching of node_modules which will skip npm ci when nothing has changed in any package.json
also using the setup-node built-in cache of ~/.npm which will speed up npm ci when it has to run.
Converted npm install to npm ci there are deterministic advantages, node_modules gets blown away when it runs, when lockfile exists it will be quicker and adhere to the lockfile completely (no unintended upgrades in CI)

I tried re-running the jobs to check the caching. It looks like the Windows jobs failed.
I think this is because the sub-package node_modules folders are not being cached properly?

Windows jobs are failing on second run (checking the cache)

@petebacondarwin Made an addition and reran it a couple times. Thanks for the initial rerun!

Something here is breaking my PR on windows 🙃 https://github.com/cloudflare/wrangler2/runs/6447784315?check_suite_focus=true

npm install sets up workspace symbolic links, does npm ci do that as well?

Yep.


Not working with Next.js 13 on Vercel

Attempting to deploy a Next.js 13 project that uses the Notion client is failing when deploying to Vercel. It works locally.
Error:

I think Next.js 13 overrides the native fetch, so maybe that's related to the issue?
To Reproduce
Node version: Tested 16.x and 18.x
Notion JS library version: 2.2.2

I see the same thing but able to deploy (with nextjs v13.1.6) it just prints the warning:

Module not found: Can't resolve 'encoding' in '.../node_modules/node-fetch/lib'

Related issue in supabase repo mentions:

It's related to an old version of node-fetch being used in cross-fetch: https://github.com/node-fetch/node-fetch/issues/412 https://github.com/lquixada/cross-fetch/issues/146
It should be safe to ignore as it's an optional dependency in node-fetch...

Wondering if upgrading node-fetch here will get rid of this warning.

When I try to use the Notion SDK with Next.js 13, like @luciovilla, I only see a warning printed but the build completes successfully.
I tried with the default Next.js installation, only changing src/app/page.tsx to use the Notion API and print a value to the screen.
import { Client } from "@notionhq/client";

async function getData() {
  // Initializing a client
  const notion = new Client({
    auth: process.env.SECRET,
  });
  const data = await notion.users.list({});
  return data
}

export default async function Page() {
  const data = await getData();

  return (
    <main>
      <pre>{JSON.stringify(data, null, 2)}</pre>
    </main>
  );
}

Since this works, I'm going to close this issue but please let me know if this base example still doesn't work for folks.

This problem still seems to occur with "next": "13.3.4":
const Page = async () => {
  const notion = new Notion.Client({ auth: process.env.NOTION_TOKEN })
  const result = await notion.databases.query({ database_id: 'xxx', })
  console.log(result)

 // ...

Just install encoding, it's an optional package in node-fetch to use textConverted() function
# node-fetch/lib/index.js
let convert;
try {
	convert = require('encoding').convert;
} catch (e) {}

// ...
function convertBody(buffer, headers) {
	if (typeof convert !== 'function') {
		throw new Error('The package `encoding` must be installed to use the textConverted() function');
	}
       // ...
}


Outsource common NSTEPS code to function

i think this was the purpose of https://github.com/JuliaReach/ReachabilityAnalysis.jl/issues/734

i think this was the purpose of #734

Does that mean there should be a separate module?

i focuse too much on the "Refactor init constants" and less on the "to their own module" :)


Advance cleanup of Dotty server warnings

Dotty doesn't like this, and Dotty is right.

Does not look good to scalafmt!