Cannot build GHC ('@WhatGccIsCalled@')

I've just tried to build GHC with ./shake-build/build.stack.sh but I'm getting the following error. Any hints/docs on how to debug this? Thanks!
Error when running Shake build system:
* OracleQ (PackageDataKey (".build/stage1/rts/package-data.mk",".build_stage1_rts_COMPONENT_ID"))
* .build/stage1/rts/package-data.mk
* includes/dist-derivedconstants/header/GHCConstantsHaskellWrappers.hs
* OracleQ (LookupInPath "@WhatGccIsCalled@")
GHC build system error: Cannot find executable '@WhatGccIsCalled@'.

Output of configure:
----------------------------------------------------------------------
Configure completed successfully.

   Building GHC version  : 8.1.20160417
          Git commit id  : 97f2b16483aae28dc8fd60b6d2e1e283618f2390

   Build platform        : x86_64-unknown-linux
   Host platform         : x86_64-unknown-linux
   Target platform       : x86_64-unknown-linux

   Bootstrapping using   : /home/michal/.stack/programs/x86_64-linux/ghc-7.10.3/bin/ghc
      which is version   : 7.10.3

   Using (for bootstrapping) : /usr/bin/gcc
   Using gcc                 : gcc
      which is version       : 5.3.1
   Building a cross compiler : NO
   hs-cpp       : gcc
   hs-cpp-flags : -E -undef -traditional
   ld           : /usr/bin/ld
   nm           : /usr/bin/nm
   objdump      : /usr/bin/objdump
   Happy        : /home/michal/.stack/snapshots/x86_64-linux/lts-5.12/7.10.3/bin/happy (1.19.5)
   Alex         : /home/michal/.stack/snapshots/x86_64-linux/lts-5.12/7.10.3/bin/alex (3.1.7)
   Perl         : /usr/bin/perl
   sphinx-build :
   xelatex      :

   Using LLVM tools
      llc   : /usr/bin/llc
      opt   : /usr/bin/opt

   HsColour was not found; documentation will not contain source links

   Tools to build Sphinx HTML documentation available: NO
   Tools to build Sphinx PDF documentation available: NO
----------------------------------------------------------------------

Michal Terepeta<EMAIL_ADDRESS>writes:

I've just tried to build GHC with ./shake-build/build.stack.sh but I'm getting the following error. Any hints/docs on how to debug this? Thanks!

This is due to a recent GHC
change.
Pinging @hvr.

See #225

Cool, thanks! With #225 everything works as expected :-)

Many thanks for reporting (@michalt) and fixing (@hvr) :-)


NOMERGE: 62 freeze

[ ] desktop
[ ] ios
[ ] android
[ ] https://github.com/keybase/react-native-v8/releases/tag/rn_v0.62.0-v8_v8.80.1 (wrong v8 dep?)

@chrisnojima there's a new tag here: https://github.com/keybase/react-native-v8/releases/tag/rn_v0.62.0-v8_v8.80.1-2


[release-v1.14]: fix: prober cache returns StatusUnknown by default (#4017)

Backport of https://github.com/knative-extensions/eventing-kafka-broker/pull/4017 to fix the default status reported by a prober when it starts probing.

/test 415-test-reconciler-keda-aws-415

/lgtm

/approve


no middleware support

is there any middle support before you get the req  ?

thank you for answering

thank you for answering


Updated to account for new source format

Content is now distributed as a .app within a .zip (no longer pre-packaged)

Removed the unpacking steps

Create package with the extracted app

@tbridge Just wanted to follow up on the PR and see if it could be merged?  Thanks!

@tbridge Just bumping and tagging for visibility.

Sorry @MLBZ521 ! All set.

No worries, thank you!


fix(resource-response-consistency): avoid destructuring property of undefined values

Addresses a bug reported in which a property is attempted to be deconstructed from an object type. When the getCanonicalSchema function was converted to return an object, a return statement was left unconverted and was still returning undefined. This caused the bug upon attempted deconstruction of the return value.
Also, I updated the project copyright string for the new year.

:tada: This PR is included in version 1.15.2 :tada:
The release is available on npm package (@latest dist-tag)
Your semantic-release bot :package::rocket:

:tada: This PR is included in version 1.16.2 :tada:
The release is available on npm package (@latest dist-tag)
Your semantic-release bot :package::rocket:

:tada: This PR is included in version 1.3.1 :tada:
The release is available on npm package (@latest dist-tag)
Your semantic-release bot :package::rocket:


Fix table tree drawer duplicate entry

Create branch from main
issue-115-fix-table-tree-drawer-duplicate-entry


Move junit_upload jobs to k8s runners

What does this PR do?
Change junit_upload jobs to run on k8s runners

Motivation
Migrate our jobs running on legacy runners to new k8s runners

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

Reviewer's Checklist

[ ] If known, an appropriate milestone has been selected; otherwise the Triage milestone is set.
[ ] Use the major_change label if your change either has a major impact on the code base, is impacting multiple teams or is changing important well-established internals of the Agent. This label will be use during QA to make sure each team pay extra attention to the changed behavior. For any customer facing change use a releasenote.
[ ] A release note has been added or the changelog/no-changelog label has been applied.
[ ] Changed code has automated tests for its functionality.
[ ] Adequate QA/testing plan information is provided if the qa/skip-qa label is not applied.
[ ] At least one team/.. label has been applied, indicating the team(s) that should QA this change.
[ ] If applicable, docs team has been notified or an issue has been opened on the documentation repo.
[ ] If applicable, the need-change/operator and need-change/helm labels have been applied.
[ ] If applicable, the k8s/<min-version> label, indicating the lowest Kubernetes version compatible with this feature.
[ ] If applicable, the config template has been updated.

Don't you need to add source /root/.bashrc?

I was wondering if I had to, but we use another image for these jobs datadog-ci-uploader. And I think we do not need this here. Because this image do not use ENTRYPOINT instruction in Dockerfile.

I thought it was because we don't use (or can't, in the case of k8s runners) entrypoints that we had to use source /root/.bashrc: https://github.com/DataDog/datadog-agent-buildimages/pull/370
But given that the CI passed I suppose I understood it wrong :sweat_smile:


Bugs

Add precompiler directive for .NET Framework 4.5 or below.

The generic GetDelegateForFunctionPointer<TDelegate> method was introduced in .NET Framework 4.5.1.
Projects targeting .NET Framework 4.5 or below need to add the BEFORE_NET451 symbol to their project in order for it to compile.

Fix manifest resource name search

Doing the search in a case-insensitive manner was incorrect.

Looks good to me.
I assume the case of names is not needed for matching?

Correct. I was integrating this in our internal project and I didn't want to fat-finger the manifest resource name, so I put a breakpoint in EmbeddedNativeLibrary.cs and copied the lower-case name to clipboard. Then I pasted it in the constructor of DllInfo and it failed to load the resource. Only when I put the correct case-sensitive name in, did it work.

Looks good.


adding missing radiuss repos and running data update

This will add missing repos reported in #34 and also add a "Sort by Name" to "undo" the other sort types, feedback from Matt!
Signed-off-by: vsoch<EMAIL_ADDRESS>

@hauten here you go! https://output.circle-artifacts.com/output/job/280be6e6-8bff-49da-a427-258ddfea1e95/artifacts/0/radiuss/projects/index.html. This adds the repos discussed in #34 and also I added a "Sort by name" to undo the others (feedback from my supervisor that I showed it to).

Looks good! The "sort by"s are fast.

That's the power of JavaScript and my poor skills at writing it! lol! Let's get this merged in so we have all our repos!


 However, the same query on a collection with more than 100k documents takes more than 10-20s.
I think this is a cloud_firestore plugin issue because this query running on Python on the same large collection is also "instantaneous".

Is there any update on this? This still occurs on IOS

@AllNamesRTakn if you are having this issue still, please file a new issue with information for us to reproduce.


Cmake error，other 2 compile methods succeeded

Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed.
Compiler: /usr/local/cuda/bin/nvcc
Build flags:
Id flags:  -v
The output was:
No such file or directory
Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed.
Compiler: /usr/local/cuda/bin/nvcc
Build flags:
Id flags:  -v
The output was:
No such file or directory
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed.
Compiler: /usr/local/cuda/bin/nvcc
Build flags:
Id flags:  -v
The output was:
No such file or directory
Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed.
Compiler: /usr/local/cuda/bin/nvcc
Build flags:
Id flags:  -v
The output was:
No such file or directory
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed.
Compiler: /usr/local/cuda/bin/nvcc
Build flags:
Id flags:  -v
The output was:
No such file or directory
Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed.
Compiler: /usr/local/cuda/bin/nvcc
Build flags:
Id flags:  -v
The output was:
No such file or directory
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed.
Compiler: /usr/local/cuda/bin/nvcc
Build flags:
Id flags:  -v
The output was:
No such file or directory
Compiling the CUDA compiler identification source file "CMakeCUDACompilerId.cu" failed.
Compiler: /usr/local/cuda/bin/nvcc
Build flags:
Id flags:  -v
The output was:
No such file or directory
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Checking whether the CUDA compiler is NVIDIA using "" did not match "nvcc: NVIDIA (R) Cuda compiler driver":
Checking whether the CUDA compiler is Clang using "" did not match "(clang version)":
Performing C++ SOURCE FILE Test CMAKE_HAVE_LIBC_PTHREAD failed with the following output:
Change Dir: /data/jupyter/cuda_learn/NN-CUDA-Example/build/CMakeFiles/CMakeTmp
Run Build Command(s):/usr/bin/make -f Makefile cmTC_6d839/fast && /usr/bin/make  -f CMakeFiles/cmTC_6d839.dir/build.make CMakeFiles/cmTC_6d839.dir/build
make[1]: Entering directory '/data/jupyter/cuda_learn/NN-CUDA-Example/build/CMakeFiles/CMakeTmp'
Building CXX object CMakeFiles/cmTC_6d839.dir/src.cxx.o
/usr/bin/c++ -DCMAKE_HAVE_LIBC_PTHREAD   -o CMakeFiles/cmTC_6d839.dir/src.cxx.o -c /data/jupyter/cuda_learn/NN-CUDA-Example/build/CMakeFiles/CMakeTmp/src.cxx
Linking CXX executable cmTC_6d839
/home/huyang02/anaconda3/lib/python3.6/site-packages/cmake/data/bin/cmake -E cmake_link_script CMakeFiles/cmTC_6d839.dir/link.txt --verbose=1
/usr/bin/c++ -rdynamic CMakeFiles/cmTC_6d839.dir/src.cxx.o -o cmTC_6d839
CMakeFiles/cmTC_6d839.dir/src.cxx.o: In function main': src.cxx:(.text+0x3e): undefined reference to pthread_create'
src.cxx:(.text+0x4a): undefined reference to pthread_detach' src.cxx:(.text+0x56): undefined reference to pthread_cancel'
src.cxx:(.text+0x67): undefined reference to pthread_join' src.cxx:(.text+0x7b): undefined reference to pthread_atfork'
collect2: error: ld returned 1 exit status
CMakeFiles/cmTC_6d839.dir/build.make:98: recipe for target 'cmTC_6d839' failed
make[1]: *** [cmTC_6d839] Error 1
make[1]: Leaving directory '/data/jupyter/cuda_learn/NN-CUDA-Example/build/CMakeFiles/CMakeTmp'
Makefile:127: recipe for target 'cmTC_6d839/fast' failed
make: *** [cmTC_6d839/fast] Error 2
Source file was:
#include <pthread.h>
static void* test_func(void* data)
{
return data;
}
int main(void)
{
pthread_t thread;
pthread_create(&thread, NULL, test_func, NULL);
pthread_detach(thread);
pthread_cancel(thread);
pthread_join(thread, NULL);
pthread_atfork(NULL, NULL, NULL);
pthread_exit(NULL);
return 0;
}
Determining if the function pthread_create exists in the pthreads failed with the following output:
Change Dir: /data/jupyter/cuda_learn/NN-CUDA-Example/build/CMakeFiles/CMakeTmp
Run Build Command(s):/usr/bin/make -f Makefile cmTC_308c5/fast && /usr/bin/make  -f CMakeFiles/cmTC_308c5.dir/build.make CMakeFiles/cmTC_308c5.dir/build
make[1]: Entering directory '/data/jupyter/cuda_learn/NN-CUDA-Example/build/CMakeFiles/CMakeTmp'
Building CXX object CMakeFiles/cmTC_308c5.dir/CheckFunctionExists.cxx.o
/usr/bin/c++   -DCHECK_FUNCTION_EXISTS=pthread_create -o CMakeFiles/cmTC_308c5.dir/CheckFunctionExists.cxx.o -c /data/jupyter/cuda_learn/NN-CUDA-Example/build/CMakeFiles/CheckLibraryExists/CheckFunctionExists.cxx
Linking CXX executable cmTC_308c5
/home/huyang02/anaconda3/lib/python3.6/site-packages/cmake/data/bin/cmake -E cmake_link_script CMakeFiles/cmTC_308c5.dir/link.txt --verbose=1
/usr/bin/c++  -DCHECK_FUNCTION_EXISTS=pthread_create -rdynamic CMakeFiles/cmTC_308c5.dir/CheckFunctionExists.cxx.o -o cmTC_308c5  -lpthreads
/usr/bin/ld: cannot find -lpthreads
collect2: error: ld returned 1 exit status
CMakeFiles/cmTC_308c5.dir/build.make:98: recipe for target 'cmTC_308c5' failed
make[1]: *** [cmTC_308c5] Error 1
make[1]: Leaving directory '/data/jupyter/cuda_learn/NN-CUDA-Example/build/CMakeFiles/CMakeTmp'
Makefile:127: recipe for target 'cmTC_308c5/fast' failed
make: *** [cmTC_308c5/fast] Error 2

You need to specify cuda compiler as nvcc


Use mysql

How to use mysql database with DesktopMap?

exactly same way you use postgres with DesktopMap

@eritropp  how? there is no options to change database!

...\resources\app\map\config - add a config.ini file with DB params based on the .example file in the directory.


rectangle spatial index

A great project, is there any plan to increase the rectangle spatial index, such as NewGeoRectField for geo query of lines or polygons.
:)

So, this is partially related to this issue: https://github.com/blugelabs/bluge/issues/13
Our first goal is simply to improve our ability to index multi-dimensional values.  But we know there is also interest in indexing/query shapes as well.


[cloud_functions] Integration test on iOS should turn build red on failure

Ensures that iOS test failures are caught by our CI.
Related issue: https://github.com/FirebaseExtended/flutterfire/issues/1866

Fixed on master, thanks!


Milestone 1 README

Milestone 1 deadline is 8 days away (30 May 2022). It's time to start working on this. Until this PR is merged, the README can be read at https://test.joulev.dev/orbital/readme-ms1.
Still the planning dates are not yet specified.
We can simply print the page to PDF when we are ready. We will use Markdown for all README from now.
cc. @VietAnh1010

Ping @VietAnh1010

Look good to go now.


Support pre-kepler GPUs without __shfl_down instruction

https://discuss.gluon.ai/t/topic/4444

It appears that pytorch and TF don;t support Fermi GPUs. Do we wish to continue support?

https://github.com/apache/incubator-mxnet/pull/10375

@piiswrong can this be closed ?

Pre-Kepler GPUs have been disabled by the PR referenced here.
@sandeep-krishnamurthy Please close this issue.
@piiswrong Please reopen this issue if it has been closed in error.


Always run e2e-vcluster with latest master changes

The e2e-vcluster test suite needs to run with the latest version of the server. For this reason, when we run that test suite we will use a private image from the dockerhub repo with the lag lastest-master. We also skip this test suite on forks because it requires secrets that are only accessible through the vertica-kubernetes repo.
We still build the v2 image to make sure nothing is broken. But since it uses an RPM from version 12.0.3 of the server, it doesn't have all of the functionality that the e2e-vcluster test suite needs. So, no e2e tests will run with it.

I have attached the link to the previous old PR here:  https://github.com/vertica/vertica-kubernetes/pull/438

I think we are close with this. Were you able to verify that the e2e-vcluster test suite is skipped on forks? Maybe if we can the same change in your original PR (#438)

@spilchen I just update the github.reprository, the e2e-vcluster test suite is skipped on my fork https://github.com/vertica/vertica-kubernetes/actions/runs/5429395092.

@spilchen If we use github.reprository == "vertica/vertica-kurbenetes", the e2e-vcluster test suite is not skipped on my fork https://github.com/vertica/vertica-kubernetes/actions/runs/5429344275
I just update the github.event.pull_request.head.repo.full_name == github.repository, the e2e-vcluster test suite is skipped on my fork https://github.com/vertica/vertica-kubernetes/actions/runs/5429640136 and worked on main vertica-kubernetes repo https://github.com/vertica/vertica-kubernetes/actions/runs/5429598998


kd_tree kNN metrics fix

Changes:

Use sklearn.neighbors.VALID_METRICS['kd_tree'] instead of sklearn.neighbors.KDTree.valid_metrics for better compatibility and fix metrics on sklearn 1.4
Remove imports for older unsupported sklearn versions

/intelci: run


我用iframe渲染展示pdf的，我如何在h5 移动端中手势放大缩小查看pdf

Attach (recommended) or Link to PDF file here:
Configuration:

Web browser and its version:
Operating system and its version:
PDF.js version:
Is a browser extension:

Steps to reproduce the problem:
1.
2.
What is the expected behavior? (add screenshot)
What went wrong? (add screenshot)
Link to a viewer (if hosted on a site other than mozilla.github.io/pdf.js or as Firefox/Chrome extension):

We can only assist in English.


Method to add questionnaire answers for each candidate

Similar to the way notes are added, need a method on the backend to enter the answered questionnaire for each candidate. Should be markdown or HTML capable.
See Election Time Layout mockup for how this will be surfaced.

We can just use an existing SQLite web interface like http://mywebsql.net or https://www.phpliteadmin.org

Must do #34 first.

See if I can solve https://bitbucket.org/phpliteadmin/public/issues/267/override-config-using-environment


FailedCreatePodSandBox during ContainerCreating

I've deployed netchecker to my cluster running docker 18.9.2 and neither the server nor agent containers are able to start successfully.  They both fail, stuck in ContainerCreating with the following error:
  Warning  FailedCreatePodSandBox  2m53s (x100 over 7m52s)  kubelet, k8s-03-usqas3-master37-ad1-65zzbf  Failed create pod sandbox: rpc error: code = Unknown desc = failed to start sandbox container for pod "netchecker-agent-2nmcd": Error response from daemon: OCI runtime create failed: container_linux.go:345: starting container process caused "process_linux.go:297: getting the final child's pid from pipe caused \"read init-p: connection reset by peer\"": unknown

Nevermind -- the suggested resource limits in the example files are too low though -- they are seemingly what caused this issue.


PluginVerifier fails to download IDE

This is a followup issue to #606 and issue #585.
The release download of e.g. IU 2020.2.4 fails with the following log message: Cannot download IDE 'IU-2020.2.4' from release channel. Trying another channel....
As far as I can see this messages comes from RunPluginVerifierTask.groovy:622.

Would it be possible to include the IOException in the debug log to get more details to find the root cause?

@mvilliger Thanks for reporting.
I've extended exceptions logging with: 8ca6e91
Do you run your test on GitHub Actions?

@hsz Thank you very much. Then hopefully I know more as soon as a new snapshot is available :)

@mvilliger THe latest snapshot should be already available (also as 0.8.0).

@hsz I think I found the root cause of the problem:
The RunPluginVerifierTask uses the gradle-download-task with the option tempAndMove(true).
This might fail for gradle-download-task versions older than 4.0.4 because of issue 146. The gradle-intellij-plugin declares the fixed version 4.0.4 in its build.gradle.kts.
Next to the gradle-intellij-plugin the affected project also includes the Kotlin JVM plugin in version 1.4.31. This plugin also has a dependency to gradle-download-task but in the older version 4.0.2.
When calculating the 'RequiredBy' build dependencies on the affected project for 'gradle-download-task' it shows the following:
de.undercouch:gradle-download-task:4.0.2
    org.jetbrains.kotlin:kotlin-gradle-plugin:1.4.31
        org.jetbrains.kotlin.jvm:org.jetbrains.kotlin.jvm.gradle.plugin:1.4.31
            build.gradle.kts

So in the affected build gradle-download-task version 4.0.2 is used as required by kotlin-gradle-plugin. Unfortunately on the system where the build is executed (a company internal Kubernetes cluster) the directories are on different partitions and that's why the move from the temp dir to the user home dir fails (because of issue 146).
To force the build to use gradle-download-task version 4.0.4 I added the following to the build.gradle.kts:
buildscript {
    dependencies {
        classpath("de.undercouch:gradle-download-task:4.0.4")
    }
}

This fixes the issue for us.
As far as I can see the dependency to gradle-download-task version 4.0.4 of the gradle-intellij-plugin has no effect during the build because this dependency is not declared in the pom of the deployed artifact.
Therefore the gradle build cannot know that the gradle-intellij-plugin actually requires version 4.0.4 and therefore chooses version 4.0.2 from the Kotlin plugin?
Maybe the runtime dependencies of the gradle-intellij-plugin should also be reflected in the created pom? What do you think?

@mvilliger, thanks for a detailed investigation!
In general, snapshot channels have that issue with dependencies (see https://github.com/JetBrains/gradle-intellij-plugin#snapshot-version), and exact dependencies have to be specified manually.
We'll take care of it!

@hsz Yes I am aware of that and I have included the dependencies as documented. Then there might be some dependencies missing in the readme?

@mvilliger No, even otherwise – we shouldn't require adding such dependencies if you'd like to use snapshot release. And that's something that should be fixed on our side.

should be fixed on the latest 0.8-SNAPSHOT. @mvilliger could you confirm please?

@zolotov Sorry for the delay. I tested with 0.8.0-SNAPSHOT without any buildscript dependencies and the build was successful.
So I can confirm the issue is fixed. Thank you all for your efforts and your help!

@mvilliger thank you very much for the investigation and checking the results!


[TEVA-1666] Add text to subscription new and edit form

Jira ticket URL

Just add the ticket number to the end:

https://dfedigital.atlassian.net/browse/TEVA-1666
Changes in this PR:

Wasn't sure what to call the translation so went with 'description', even though it's not really a description... Suggestions for names welcome. That's also why it's called 'text' in the PR title and commit. Suggestions for better css class names also welcome.

Screenshots of UI changes:
Before
Create a job alert

Manage a job alert

After
Create a job alert

Manage a job alert

I think 'description' is a fine description of the description.
It's also consistent with how we label copy for other pages.

Review app deployed to https://teaching-vacancies-review-pr-2550.london.cloudapps.digital


Wrong spatial  location calculator output when rgb alignment is enabled.

I just found a potential bug that spatial location calculator output when rgb alignment is enabled is wrong as shown in the picture below:

Setup
Ubuntu 18.04
depthai-core develop branch with commit 7b60935b67299fae7fbf79c5bd3854d5cc74b8b6

Reproduce

Build depthai-core with commit 7b60935b67299fae7fbf79c5bd3854d5cc74b8b6 using command below:

cmake -S. -Bbuild -D'DEPTHAI_BUILD_EXAMPLES=ON'
cmake --build build

Run spatial_mobilnet example:

./build/examples/spatial_mobilenet

Expect result
The correct spatial location of detected object is generated and the roi region in depth frame is correct.

Actual output
Wrong roi regions of detected objects are generated from spatial detection network and visualized in the depth image.

My diagnose of this issue is that with rgb alignment enabled, the depth image was re-scaled to rgb ISP image size after alignment, however the bounding box (ROI) generated from the preview rgb image are just mapped directly to the aligned depth image without modifying the bounding box coordinates which causes the spatial calculator generating wrong result.

@developer-mayuan which board are you using? There's no such issue on OAK-D or OAK-D Lite.
Did you modify the example before running?

HI @szabi-luxonis I'm using OAK-D for running this test and I didn't modify the example, just checkout the commit and did a fresh build.

@developer-mayuan can you share your calibration info? Could be an older version that you are using.
Run the following example: https://github.com/luxonis/depthai-python/blob/main/examples/calibration/calibration_reader.py
and share the output .json file.

@szabi-luxonis It seems like this is indeed a calibration issue since I found one of my oak-d camera doesn't have this issue. But other boards come with the error out of box. Here is a sample calibration info I got from one of oak-d camera having this issue:
[18443010E1DF1AF500] [60.719] [system] [info] PRINT:LeonCss: bss_init took 40.417 ms
BootloaderConfig.options1 checksum doesn't match. Is: 0x10304418 should be: 0xEB4AFD53
BootloaderConfig.options2 checksum doesn't match. Is: 0x00000000 should be: 0x2380F205
GPIO boot mode 0x16, interface USBD
Setting aons(0..4) back to boot from flash (offset = 0)
====ENABLE WATCHDOG====1
--> brdInit ...
initial keepalive, countdown: 10
PLL0: 700000 AUX_IO0: 24000 AUX_IO1: 24000 MCFG: 24000 MECFG: 24000
Board init ret 3
brdInitAuxDevices: Error: SC = 27: io_initialize expander_cam_gpios_1 [OK]

spi_N25Q_init: Flash JEDEC ID: ff ff ff
eeprom_read_status 0!
Reading VERSION 6 --- ->
Failed to probe IR driver LM3644
Failed to probe IR driver LM3644
Failed to probe IR driver LM3644
Closing EEPROm!
Is booted from flash by bootloader: 0
Networking not available...
Called by: LOS, controller: LOS
Enumerating on socket: Cam_A / RGB / Center
Probe failed I2C1 0x1a reg 0016: expected 0214, read 0378
Probe failed I2C1 0x1a reg 0016: expected 0214, read 0378
  >> Registered camera A12N02A (imx378) as /dev/Camera_0
Enumerating on socket: Cam_B / Left
  >> Registered camera TG161B (ov9282) as /dev/Camera_1
Enumerating on socket: Cam_C / Right
  >> Registered camera TG161B (ov9282) as /dev/Camera_2
Enumerating on socket: CAM_D
initial keepalive, countdown: 9
Initializing XLink...
UsbPumpVscAppI_Event: 5 VSC2_EVENT_ATTACH
initial keepalive, countdown: 8
UsbPumpVscAppI_Event: 4 VSC2_EVENT_RESET
UsbPumpVscAppI_Event: 4 VSC2_EVENT_RESET
UsbPumpVscAppI_Event: 0 VSC2_EVENT_INTERFACE_UP
Done!
Usb connection speed: Super - USB 3.0
I: [Timesync] [   1905056] [main] startSync:116     Timesync | Callback not set
Temperature: Driver registered.
Temperature: Initialized driver.
Temperature: Sensor opened: CSS.
Temperature: Sensor opened: MSS.
Temperature: Sensor opened: UPA.
Temperature: Sensor opened: DSS.
[18443010E1DF1AF500] [60.719] [system] [info] PRINT:LeonMss: Called by: LRT, controller: LOS
RGB Camera Default intrinsics...
[[3110.83837890625, 0.0, 1921.591064453125], [0.0, 3110.83837890625, 1096.3291015625], [0.0, 0.0, 1.0]]
3840
2160
LEFT Camera resized intrinsics...
[[802.74401855   0.<PHONE_NUMBER>6]
 [  0.<PHONE_NUMBER>5<PHONE_NUMBER>9]
 [  0.           0.           1.        ]]
LEFT Distortion Coefficients...
k1: -11.881447792053223
k2:<PHONE_NUMBER>663086
p1: 0.0002003137196879834
p2: -0.0004118149518035352
k3: -70.5708236694336
k4: -11.907358169555664
k5:<PHONE_NUMBER>165039
k6: -68.99750518798828
s1: 0.0
s2: 0.0
s3: 0.0
s4: 0.0
τx: 0.0
τy: 0.0
RIGHT Camera resized intrinsics...
[[805.98931885   0.<PHONE_NUMBER>1]
 [  0.<PHONE_NUMBER>5<PHONE_NUMBER>7]
 [  0.           0.           1.        ]]
RIGHT Distortion Coefficients...
k1: -8.983304977416992
k2: 94.06720733642578
p1: 0.0005835810443386436
p2: 0.0006875866674818099
k3: -56.06025695800781
k4: -9.04328727722168
k5: 93.61856842041016
k6: -54.901123046875
s1: 0.0
s2: 0.0
s3: 0.0
s4: 0.0
τx: 0.0
τy: 0.0
RGB FOV 68.7938003540039, Mono FOV 71.86000061035156
LEFT Camera stereo rectification matrix...
[[ 1.00436654e+00  7.18781715e-03 -3.44817361e+01]
 [-6.62840836e-03  1.00422704e+00 -1.98676893e+01]
 [ 5.63491554e-07  5.82279554e-07  9.99416006e-01]]
RIGHT Camera stereo rectification matrix...
[[ 1.00032248e+00  7.15887554e-03 -3.11855436e+00]
 [-6.60171920e-03  1.00018354e+00  3.62704692e+00]
 [ 5.61222666e-07  5.79935016e-07  9.99447249e-01]]
Transformation matrix of where left Camera is W.R.T right Camera's optical center
[[ 9.99966621e-01  7.99766742e-03  1.66361686e-03 -7.52113533e+00]
 [-7.99612608e-03  9.99967575e-01 -9.30935843e-04  8.98113288e-03]
 [-1.67100830e-03  9.17602272e-04  9.99998212e-01  1.59466267e-02]
 [ 0.00000000e+00  0.00000000e+00  0.00000000e+00  1.00000000e+00]]
Transformation matrix of where left Camera is W.R.T RGB Camera's optical center
[[ 9.99976695e-01  5.96394110e-03 -3.31831700e-03 -3.76314974e+00]
 [-5.95916621e-03  9.99981165e-01  1.44668622e-03 -1.32785551e-02]
 [ 3.32688261e-03 -1.42687815e-03  9.99993443e-01 -2.45756328e-01]
 [ 0.00000000e+00  0.00000000e+00  0.00000000e+00  1.00000000e+00]]

@developer-mayuan

Can you share the calibration info from the one that doesn't have issue ?
Are all the devices were bought around the same time ?

I investigated this issues more and found cameras with calibration info with EEPROM data version 5 work fine, but cameras with EEPROM data version 6 have this issue.
Here is the calibration info without this issue:

@developer-mayuan check out 1ee7cedee3899ecc670ce94944ced8928474da8c it was an RGB alignment related issue when configured RGB resolution (1080p) was different from calibrated one (4k in your case)

Thanks for the quick fix! I can confirm that by checking out https://github.com/luxonis/depthai-core/commit/1ee7cedee3899ecc670ce94944ced8928474da8c and doing a fresh build, I cannot reproduce this issue anymore using my current oak-d cameras. Great work!


docs(checkbox group): Added vertical direction document

Checklist

[x] Fix linting errors
[x] Tests have been added / updated (or snapshots)

Change information

fix #1040

Codecov Report

Merging #1041 (7c2032c) into dev (d78b5cf) will not change coverage.
The diff coverage is n/a.

:exclamation: Your organization is not using the GitHub App Integration. As a result you may experience degraded service beginning May 15th. Please install the Github App Integration for your organization. Read more.
@@           Coverage Diff           @@
##              dev    #1041   +/-   ##
=======================================
  Coverage   95.94%   95.94%
=======================================
  Files         325      325
  Lines       21281    21281
  Branches     1428     1428
=======================================
  Hits        20419    20419
  Misses        816      816
  Partials       46       46


glom: refactor

Things done
Switch to python 3.11

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[x] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[x] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
24.11 Release Notes (or backporting 23.11 and 24.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

Add a :+1: reaction to pull requests you find important.

Thanks.
Could you please split the first commit into separate formatting and move so that Git can recognize the file as moved?
Also consider making yourself a maintainer if you use this software.
Though note that Glom is no longer maintained upstream so it might eventually break: https://gitlab.gnome.org/Archive/glom

@NixOS/gnome Please take a look

nixpkgs-review result
Generated using nixpkgs-review.
Command: nixpkgs-review pr 346684

x86_64-linux

:white_check_mark: 5 packages built:

glom
glom.dev
glom.devdoc
glom.doc
glom.lib

aarch64-linux

:white_check_mark: 5 packages built:

glom
glom.dev
glom.devdoc
glom.doc
glom.lib

x86_64-darwin

aarch64-darwin


Negative responses get cached even when setting cache-max-negative-ttl: 1

Describe the bug
Negative responses get cached even when setting cache-max-negative-ttl: 1
To reproduce
Steps to reproduce the behavior:

Verify unbound used by system in /etc/resolv.conf
Set cache-max-negative-ttl: 1
Restart unbound
Query non-existant domain (ex. dig www.john.doe)
See that query took some time (more than 10ms) and returned NXDOMAIN

...

Wait for 5 secunds for negative cache TTL to end
Query again, look at "Query time" to identify whether cache was used (can be also identified by watching logs for "using cached" message from unbound when running with log-queries and log-replies)

...

Expected behavior
As stated in unbound.conf(5):
cache-max-negative-ttl: <seconds>
    Time to live maximum for negative responses,
    these have a SOA in the authority section that is limited in time.
    Default is 3600.  This applies to nxdomain and nodata answers.

I expect for the cache to end after <seconds>
System:

Unbound version: 1.13.1
OS: Gentoo (happens to me also on Arch)
unbound -V output:

Version 1.13.1

Configure line: --prefix=/usr --build=x86_64-pc-linux-gnu --host=x86_64-pc-linux-gnu --mandir=/usr/share/man --infodir=/usr/share/info --datadir=/usr/share --sysconfdir=/etc --localstatedir=/var/lib --docdir=/usr/share/doc/unbound-1.13.1-r2 --htmldir=/usr/share/doc/unbound-1.13.1-r2/html --with-sysroot=/ --libdir=/usr/lib64 --disable-debug --disable-gost --enable-dnscrypt --disable-dnstap --enable-ecdsa --disable-subnet --disable-cachedb --disable-static --enable-systemd --without-pythonmodule --without-pyunbound --without-pthreads --with-libnghttp2 --disable-flto --disable-rpath --enable-event-api --enable-ipsecmod --enable-tfo-client --enable-tfo-server --with-libevent=/usr --without-libhiredis --with-pidfile=/run/unbound.pid --with-rootkey-file=/etc/dnssec/root-anchors.txt --with-ssl=/usr --with-libexpat=/usr
Linked libs: libevent 2.1.11-stable (it uses epoll), OpenSSL 1.1.1k  25 Mar 2021
Linked modules: dns64 ipsecmod respip validator iterator
DNSCrypt feature available
TCP Fastopen feature available

Additional information
It is happening to me for a while now (from previous versions) and I just finally decided to write an issue about it

If I perform these actions, everything works. The first printout shows a 1 second TTL (at step 5), for me.
Is unbound somehow not configured with the option even though you think you set it? Eg. you edited /etc/unbound.conf but unbound is using /usr/local/etc/unbound.conf or somewhere in /var a chroot with the file?

Thanks for the quick reply!

Is unbound somehow not configured with the option even though you think you set it? Eg. you edited /etc/unbound.conf but unbound is using /usr/local/etc/unbound.conf or somewhere in /var a chroot with the file?

I've checked, no other config than /etc/unbound/unbound.conf exists.

If I perform these actions, everything works. The first printout shows a 1 second TTL (at step 5), for me.

Might it be a misunderstading on my side?
As far as i understand the first dig shows:

;; Query time: 463 msec

Because the user sends a request to unbound and the unbound service dont have the domain cached so it is forwarding the request to the global DNS - thus creating a 463ms delay.
Afterwards on the 2nd dig we have:

;; Query time: 0 msec

Because the request was served from unbound's cache (on localhost).
What i wanted to achieve is for Unbound to not cache the NXDOMAIN response after the 1st dig, so that 2nd time i request the domain from unbound it will forward the query to the global DNS once again.

Yes it should then not cache it. That does not seem to happen, but if I try the option just plainly, it works for me. Something else must be wrong for you? Perhaps you do not query unbound, but another resolver like systemd, or I guessed you could be editing a different config file, because that happened to others.


Radzen Grid Filter floating outside screen not adjusting according to screen or radzen grid boundary

The search filter pop up of Grid is floating out of Screen The filter popup should adjust it's position according to screen and available space currently its going out of screen and causing extra scroll if filter is extreme right end of page it should adjust open in slight left from right end of page same as downwar if there is no space in downward it should popup in upward same as radzen select controls.

Thanks.

We are doing already what's possible to prevent this:
https://github.com/radzenhq/radzen-blazor/blob/master/Radzen.Blazor/wwwroot/Radzen.Blazor.js#L1099-L1128
still there are cases when it cannot be avoided since there is not enough space. Feel free to propose better code via pull request.


Homebrew install failing in Travis CI Xcode10.1 (10.13) build with git protocol.version 2 error

From the failed build:
TASK [ansible-role-homebrew : Ensure Homebrew is installed.] *******************
919fatal: [localhost]: FAILED! => {"changed": false, "cmd": "/usr/bin/git ls-remote https://github.com/Homebrew/brew -h refs/heads/master", "msg": "fatal: unknown value for config 'protocol.version': 2", "rc": 128, "stderr": "fatal: unknown value for config 'protocol.version': 2\n", "stderr_lines": ["fatal: unknown value for config 'protocol.version': 2"], "stdout": "", "stdout_lines": []}

See failed build log: https://travis-ci.org/geerlingguy/ansible-role-homebrew/jobs/619641497#L918
It looks like this is the associated issue: https://travis-ci.community/t/got-to-fail-carthage-outdated-command-because-of-git-protocol-version/2359/7 — and it links to: https://github.com/travis-ci/travis-build/pull/1659
More about protocol.version=2: https://opensource.googleblog.com/2018/05/introducing-git-protocol-version-2.html
I think I might just disable it by running git config --global --unset protocol.version

Finally fixed via commit https://github.com/geerlingguy/ansible-role-homebrew/commit/aa7f8d34fac5c105956bd504053a0f897a732c9d


acquireTokenByCode does not return a refresh token

tried working with msal-node for oauth code flow,
getAuthCodeUrl works perfectly fine
and helps to construct the url and returns the code.
when trying to use the acquireTokenByCode method even when defining a "offline_access" within the scope,
it does not return a refresh token.
it is important to mention that when using the same code and firing a post request to:
https://login.microsoftonline.com/common/oauth2/v2.0/token
it does return a refresh token.

RefreshToken is not returned to the users for MSAL libraries by design. A user would need idToken and accessToken to access the resources, and we provide them in authenticationResult. The RefreshToken is cached, and refreshed as needed depending on the expiry and renewal needs. Since the user never accesses RefreshToken directly and would need to swap it for a token that can be played against a resource, we would like to keep it in the cache rather than return it in the response.
Can you please confirm the cache has RefreshToken stored in your case to ensure this is working correctly?
Hope this clarifies!

RefreshToken is not returned to the users for MSAL libraries by design. A user would need idToken and accessToken to access the resources, and we provide them in authenticationResult. The RefreshToken is cached, and refreshed as needed depending on the expiry and renewal needs. Since the user never accesses RefreshToken directly and would need to swap it for a token that can be played against a resource, we would like to keep it in the cache rather than return it in the response.
Can you please confirm the cache has RefreshToken stored in your case to ensure this is working correctly?
Hope this clarifies!

Microsoft is worse in developer experience.
there has been several ask, at least you could have given option to return refresh token for greedy code. I don't need to depend on you to rotate refresh token. You are unnecessarily forcing people to move away from your lib.
for scalable apps it is app's responsibility to make sure how their flow is. complex architecture, hindrance in using what is in the protocol (dosen't OAuth protocol return refresh token) wasted my 2 day figuring out how to use this lib and get refresh token.  no wonder why Microsoft sdk and libs are incompetent and requires several partner libs and components. I can go on and on for several instances of arrogance or blunders in name of open source by MS

Microsoft is worse in developer experience.
there has been several ask, at least you could have given option to return refresh token for greedy code. I don't need to depend on you to rotate refresh token. You are unnecessarily forcing people to move away from your lib.
for scalable apps it is app's responsibility to make sure how their flow is. complex architecture, hindrance in using what is in the protocol (dosen't OAuth protocol return refresh token) wasted my 2 day figuring out how to use this lib and get refresh token.  no wonder why Microsoft sdk and libs are incompetent and requires several partner libs and components. I can go on and on for several instances of arrogance or blunders in name of open source by MS

Hi @sameerag, thanks, I quite agree with @gautamsi, the sdk should allow the retrieval of a refresh token.
we are working in a architecture that would not support the use of cached refresh token that is not exposed to the developer.
if it's ok, it could be extremely helpful to request a new feature for this specific use case,
at the moment it means that we are not using the sdk and we sure want to.
Thanks,
Amit

Hi @sameerag, thanks, I quite agree with @gautamsi, the sdk should allow the retrieval of a refresh token.
we are working in a architecture that would not support the use of cached refresh token that is not exposed to the developer.
if it's ok, it could be extremely helpful to request a new feature for this specific use case,
at the moment it means that we are not using the sdk and we sure want to.
Thanks,
Amit

I agree that requesting a user token through the SDK is needed, I have spent around 3 days trying to read through microsoft docs and hours of youtube videos trying to figure out how and still havent figured it out. I dont need the library to manage the refresh for me... I can handle that... I just need the ability to get the refresh token which I can then use to refresh on my own. Im literally about to download wireshark just to see what traffic the SDK is generating so I can implement on my own...

I agree that requesting a user token through the SDK is needed, I have spent around 3 days trying to read through microsoft docs and hours of youtube videos trying to figure out how and still havent figured it out. I dont need the library to manage the refresh for me... I can handle that... I just need the ability to get the refresh token which I can then use to refresh on my own. Im literally about to download wireshark just to see what traffic the SDK is generating so I can implement on my own...

Any news on this issue?
Thanks,
Amit

Any news on this issue?
Thanks,
Amit

Hi all. Apologies for the delay in answering.
@gautamsi This is your first warning: by participating in this repository, you agree to follow Microsoft's Code of Conduct: https://opensource.microsoft.com/codeofconduct/
Further violations may result permanent banishment. Happy to have a constructive conversation about why refresh tokens should be returned.

I agree that requesting a refresh token through the SDK is a fundamental need

we are working in a architecture that would not support the use of cached refresh token that is not exposed to the developer.

This is something that is not unique to MSAL.js, we have had these discussions in other MSAL libraries as well. I recommend reviewing this discussion.
We are happy to consider adding this feature as an opt-in configuration for advanced users, but after reading the above comments, it is still not clear on what use cases require the developer to use a refresh token. There are a few reasons we do not return the refresh token to developers:

Refresh tokens need to be persisted, and it adds another security consideration if they are persisted in a location other than where you have designated the MSAL library to store them.
Reducing the number of refresh token requests to the authentication service by ensuring refresh token is ONLY used when a new access token is required.
We recommend developers to retrieve access tokens using the acquireTokenSilent method, which will ensure you always have an access token that is not expired. This removes the need to track access token lifetime in the application.

I dont need the library to manage the refresh for me... I can handle that... I just need the ability to get the refresh token which I can then use to refresh and cache on my own.

@alilland I'm not sure this is a compelling reason to allow refresh tokens. The entire point of the MSAL libraries is to abstract away the token retrieval and renewal from the application. msal-node provides APIs to customize where the tokens and account objects are stored, so you could potentially put those tokens in a place that your app can access afterwards. As I said above, we are happy to consider adding refresh tokens to the result, but it seems like you are only taking advantage of a fraction of what the library is offering.
cc @jmprieur @bgavrilMS for further discussion.

@pkanher617 dont worry, I will not be jumping here again. Happy without it until the approach changes.

May be I'm not getting this. I have a Node background process that periodically sync OneDrive files for user. After I have access to user access_token and refresh_token I save them to database and my background process uses these tokens when needed. The process will request new tokens when old ones expire. Which flow an I supposed to use here? How will the msal-node library refresh the tokens of it's own if I can't persist them?

@gautamsi - ultimately AAD service is an OAuth2 certified service. You can use any OAuth2 library you like if you really want to or even make HTTP web requests on your own. By the way, OAuth protocol does not require IdP to issue refresh token, AAD does issue refresh tokens, but others do not.
MSAL libraries are higher level abstractions over OAuth2. MSAL aims to remove some of the complexity in combining authorization grant with refresh_token grant and handling expiration. By the way, MSAL.NET has 1000s of apps developed, including Visual Studio and Git Credentials Manager, and they never needed access to refresh tokens. I'm sure we can figure out a solution here. Calling AcquireTokenSilent and making sure MSAL can persist the token cache is all you need.
@amitava82 - MSAL will persist all tokens (access tokens, refresh tokens, id tokens) and some metadata about accounts to its cache. You only need to tell MSAL where to persist a blob. For public client apps (i.e. desktop apps, console apps)  on Windows you typically store it to a file and encrypt the file with Windows' Data Protection API, on Mac you'd use the KeyChain etc. For confidential client apps, i.e. web sites, web apis, you can store it in a distributed cache or in the session. Depending on your scenario, we can point you to some samples that do the heavy lifting. We currently do not provide a default persistence strategy, but we probably should for public clients.

@bgavrilMS Thanks for the explanation. We use serverless functions so a file storage like in the example won't work. I think what we need a storage api interface that we can implement. I just finished Box integration where their javascript api does it similar way and I just had to implement my own strategy for token store/retrieval logic. Can you please point me to the sample you're referring to (that isn't based on filesystem storage)?

@amitava82 - just to understand your scenario better. You have a front end where you ask the user to login and you collect the authorization code. You then send the authorization code to your backend (a serverless function) and redeem it for tokens using MSAL? Or does your front end also redeem the auth code ?
The MSAL mechanism that allows you to customize the token cache storage has a sample here - but it uses a file. Not sure if @sameerag and team have a sample showing other persistence mechanisms, but should be easy to adapt to your needs - you need to persist a blob and to give it back to MSAL when it asks for it.

@bgavrilMS Yes, the token exchange happens in backend using the code. From the look of the code it looks like it writes entire cache into the blob. I'd want to only update the one that changed in the given request context. Is there any document for the cache storage?

I'll let the JS team respond to the request for sample, I don't how far the token caching got for this confidential client scenario. @jmprieur may be able to help as well.

Thankyou @bgavrilMS. Appreciate the help.
@amitava82 Some points to note:

Currently msal-node cache is always written and read as a single blob, MSAL manages to merge the old data with new one to be in sync with the latest changes made by the application in run time. We are working on making this more flexible, the design to write and read single credentials to disk is not yet finalized.
We have a default implementation of file encryption as an additional library that can be opted in for a cross platform file storage here
I understand for your use case you do not want a file, and I believe it is possible to send any blob of data into msal-node as long as you implement ICachePlugin - referenced here and here.
Can you please check the msal-node-extensions documentation above and see if we can tailor that to your needs? We can work with you to develop a sample.

cc @sangonzal @samuelkubai

Thanks @sameerag for the pointers. I'll try to come up with a solution with ICachePlugin implementation. As long as I can pick the single credential that changed and msal-node can accept the blob then it should work.


import requests fails with Anaconda

The anaconda setup seems to have gone just fine. However, when I try to run the test, I ran into an issue. The bottom line is:
import requests  fails with this error:
ImportError: No module named 'requests'
Any help would be appreciated. Thanks.
Regards,
Amit

I fixed this issue. This is because of the bug in environment specification. package requests doesn't seem to be available for Udacity self driving car term1 environment. I installed this package specifically for that environment and now the test is passing.


Axios conversion

This issue is to add an axios  conversion. I saw PR 148 but didn't see why it was closed, or if those changes have just been lost.
I'd be happy to do the implementation and open a PR for it, just wanted to check if there's a reason the other PR was rejected.
Thanks!

Surprised no one has filed a ticket for axios

https://github.com/Kong/httpsnippet/issues/69#issuecomment-471342502 😂
@joshgrib the author closed that PR mysteriously so all targets are welcome for now. It is possible that we would extract out library implementations from the core into a plugin system in the future, but for now, it is welcome!

Opened a PR here: #176
Please give feedback if the output format can be changed/improved.


AI-Enhanced Testing Framework: New Features for Test Case Generation, Code Review and Documentationöst improvement

1. Summary:
This pull request brings in major improvements to the testing framework powered by Artificial Intelligence with an aim to automate and fine-tune the testing process. New functions are as follows: generate_test_cases to create test cases These updates are meant to increase testing efficiency, minimize the effort that goes into manual testing and to make the testing and development process more efficient.
2. Related Issues:
These improvements are concerned with aspects such as the amount of time and energy that was previously spent in developing test cases, reviewing codes, creating fake data, identifying faults, and documenting test suites. These changes focus on making these processes more efficient and to guarantee that every possible situation is covered in the testing.
3. Discussions:
The primary topic was the advantages of applying AI in the testing process, especially in those areas where manual work is required in large quantities, including test case creation, and code analysis. Another important aspect that was also highlighted was the use of AI to enhance code quality, adherence to the best practices and generation of realistic sample data. Also, the necessity of maintaining the documentation up to date and complete through the use of computer programs was also stressed.
4. QA Instructions:

Verify the efficiency of the generate_test_cases function in order to produce a large number of tests that can encompass a large number of possible scenarios.
Check if the ai_review_code function can detect code optimization opportunities, enforces the best practices and can identify any possible bugs.
Evaluate the ai_mock_data_generation function based on how well it generates relevant mock data.
Determine whether the ai_error_correction function is capable of identifying and correcting errors within the code.
Assess the ai_generate_docs function to check whether it produces precise, complete, and recent documentation as per the test suite.

5. Merge Plan:
Once the QA testing is done the branch will be merged into the main branch. Emphasis will be made to make sure that the AI features will not affect the current framework and when they are affecting the framework, their performance will be uniform across all scenarios. This will be done in a way that will not interfere with the day to day development processes that are taking place.
6. Motivation and Context:
This is because the motivation behind these updates is to use AI in a bid to improve the test framework so as to make it perform better. This way, we want to minimize the amount of work that has to be done in generating test cases, reviewing code, finding errors, and documenting the code and tests, enhance the overall testing by covering more code and increase the quality of the code by making sure it follows best practices. These are adding value to the use of Artificial Intelligence in software testing hence promoting faster, reliable, and quality software development results.
7. Types of Changes:

**New Feature:The following are the applications of AI in software development: Test case generation, Code review, Mock data generation, Error detection, and Documentation.
**Enhancement:There is an enhancement of the testing process through the automation of some of the processes involved.
Performance: Minimisation of the effort and time to be expended in the creation of test cases, reviews of code and documentation.
Maintenance: This helps in updating the documentation consistently and also, keeping an eye on the quality of code on a regular basis by the use of AI-based tools.

:warning: Please install the  to ensure uploads and comments are reliably processed by Codecov.
Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 62.59%. Comparing base (ab846f6) to head (76563fa).

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@           Coverage Diff           @@
##             main    #1473   +/-   ##
=======================================
  Coverage   62.59%   62.59%
=======================================
  Files         287      287
  Lines       17589    17589
=======================================
  Hits        11009    11009
  Misses       6580     6580

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

Hi, thank you for proposing this enhancement. I fully agree that improving the testing capabilities for LLM-based agents is critical. I suggest we focus on refining the implementation of specific actions, particularly in areas such as test case generation, code review validation, and debugging. For instance, we could develop specified prompts for generating test cases and debugging scenarios. Are you interested in working on this? Additionally, I believe it would be valuable to use a standard code dataset to test these features, ensuring the performance evaluation is comprehensive. What are your thoughts on this approach?


Static MAC for container

Hi,
when the CCU container is configured to receive its IP via DHCP, the assignment of a static IP via DHCP is not possible as the container currently regenerates a random MAC address each time the container / pivccu service is restarted.
As for many applications a static IP is necessary (XML-API, DNS in general, ...), a static MAC fixes this.
My change sets the container MAC address to a static value. The address is taken from a locally administered address range so it should not cause conflicts with existing devices.
For the future, it might be also worth considering to use a MAC that is once random-generated (e.g. at install / first boot) and then kept static, preventing issues with multiple piVCCU instances in the same network.

Declined: Using a complete static MAC will prevent using multiple piVCCU instances.
And there is already some logic available in piVCCU: The automatic MAC address is derived from the MAC address of the host and will be the same on every start of the container (as long as the MAC of the host does not change).
Additionally you can change the MAC in your local config like you did it in this PR. The file is marked as config file, so an update will not overwrite it without asking.


[GLUTEN-7387][CH] Allow parallel downloading in scan operator for hive text/json table when the whole compresse(not bzip2) file is a single file split

What changes were proposed in this pull request?
Allow parallel downloading in scan operator for hive text/json table. Currently it requires the whole file as file split(it only happens when file is compressed without bzip2). It is disabled by fault.
(Fixes: #7387)
How was this patch tested?
Test manually in production.

Test result in production result
Query: select count(1) from text_table where day = '2024-09-01'
Run it without parallel download (--conf spark.gluten.sql.columnar.backend.ch.runtime_settings.max_download_threads=1)

Run it with parallel download (--conf spark.gluten.sql.columnar.backend.ch.runtime_settings.max_download_threads=4)

为什么不支持 Biz2?
因为 bzip2 支持 file split，这个PR支持文件级别的并行下载


  Build frameworks is the single most tested part of AudioKit since every time we push a change or make a pull request on Github, that is what is run to compile everything and run the unit tests.  https://travis-ci.org/AudioKit/AudioKit

The scripts will use the current SDK in Xcode, however because we started using some features that are only available in Swift 4.2 / Xcode 10 this probably will not work unless you actually use Xcode 10. I suggest you install Xcode 10 separately and use xcode-select to switch the CLI between 9 and 10.


rename library v2

Description
renaming library, lightning and other stuff

List of changes:

mlcvs --> mlcolvar
pytorch_lightning --> lightning
import lightning as pl --> import lightning  (and pl. --> lightning.)
lightning.callbacks --> lightning.pytorch.callbacks

Both the mlcolvar/tests/test_cvs_multitask_multitask.py and DeepTDA notebook fail for tensors on different devices.

@EnricoTrizio I think the tests are failing on GPU when TDA loss is used:
# compute loss function contributes for class i
>           loss_centers[i] = alpha*(mu - target_centers[i]).pow(2)
E           RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!

@andrrizzi @EnricoTrizio I am merging this.
Note that you might have to reinstall the library
The last thing which needs to be changed is the repo name (and then also read the docs)


[WIP] Build Example Notebook to Walk Through mne-hfo usage

PR Description
Closes: #6
Closes: #9
This PR's goal is mostly to build a demo notebook to walk through mne-hfo usage. Some modifications and supporting functions needed to be added along the way.
Still in progress.
TODO (I will help w/ this):

[ ] API to take in two annotations dataframes and find overlapping HFO events
[x] API to convert from *events.tsv dataframe to *annotations.tsv dataframe
[ ] API to compute rate of HFOs per channel (per unit of time (e.g. minutes/hrs)).

Merge checklist
Maintainer, please confirm the following before merging:

[ ] All comments resolved
[ ] This is not your own PR
[ ] All CIs are happy
[ ] PR title starts with [MRG]
[ ] whats_new.rst is updated
[ ] PR description includes phrase "closes <#issue-number>"

Nice, it's not bad start. A few comments:

Limit the print statements. It renders as a huge file otw.
Include a GridSearchCV/RandomGridSearchCV using metric we converge on (see below). Might need to fenangle the Detector implementation though to improve the predict and score function.
Render the simulated part.

To compare HFO detections, what are you using as a metric? E.g. det1 gets HFO (time_x, time_y) and det2 gets HFO (time_a, time_b). What is the proposed overlap function?
In https://github.com/adam2392/mne-hfo/issues/9, I guess it is just overlap in endpoints counts as +1, no-overlap at all in endpoints counts as 0. Is that correct? Thus the metric in our case is simply a "custom" accuracy implementation.
Are there any weaknesses to this approach? What other metrics can alleviate that weakness?
Scoring Function to make SearchCV work
If that's the case, it seems that most of traditional metrics (e.g. accuracy), we have to define ourselves using for example, the overlap incidence defined above. Probably more things, such as roc_auc, etc. I can see the score function to simply operate with a kwarg input defining the metric (e.g. 'accuracy').
Then, we massage the data to go from these HFO events to our criterion. E.g. For overlap, events gets converted from (time_x, time_y) -> {+1, 0}. So for two running lists of HFO events, we get a list of y_true and y_pred. Then it becomes trivial to feed those to sklearn's API. That way, our responsibility is just implementing the logic to get to y_true and y_pred.

I've added an API to go from *events.tsv -> *annotations.tsv and corresponding tests for the public functions in io.py.
Let's get this closed out and refine the example as we develop the API further. Can you do the following:

Simplify the jupyter notebook (see comment above) and render the simulation cells as well.
Add unit tests for find_coincident_events
Update whats_new.rst document with a description of what was added here.

Re-ping me when that's done, and then let's meet to discuss how the algorithms performed on the validation dataset, and how we can start running it on the sickkids dataset.

Fixed circle CI for you.


How to get the "Change Dataset"

Hi,
I am wondering if your example "Change Dataset" in this repo was obtained by COnto-Diff first and then manually modified?
Is it possible to input the old ontology and new ontology and then automatically get the "Change Dataset" that can be used for input in this tool?
Thanks!

Hi @xuemduan, the change dataset was extracted from the release notes of ePO (e.g., see the last ones https://docs.ted.europa.eu/EPO/latest/release-notes.html). We parse them from the HTML to CSV and then use RML mappings to construct the Change Dataset KG.

Is it possible to input the old ontology and new ontology and then automatically get the "Change Dataset" that can be used for input in this tool?
Our tool needs the Change KG as input and it's out of our scope now to discover the changes. But it could be integrated with COnto-Diff or any other diff tool


Why there is no semver or release tags?

Hey guys,
I've been using this library for a while and it works pretty well.
Unfortunately the lack of versioning / releases is really a problem.
The workaround of using the tip of the repository as a dependency is obviously very fragile. A simple breaking change can go easily unnoticed into production build because of the absence of a version.
Of course we could simply lock the dependency to a specific commit, but it's going to be hard then to "upgrade" as there is no related changelog to look at.
So my question is: why there is no versioning / release tags? I can live with the library not being published to npm, bower, etc, but having versions and keeping track of them should be a must IMHO.
Thanks

There should be a 1.1 release soon. See https://github.com/LeaVerou/awesomplete/milestones/v1.1

Ok, so is it planned to start using semver?
Thanks for the quick reply.

@LeaVerou Speaking of server, should it be a 2.0 instead? There is a small known breaking change with suggestion item text API.

There is a small known breaking change with suggestion item text API.

That's the problem I discovered today :)

That's the problem I discovered today :)

Can you please share, maybe it's something we don't know about yet?

Well, it's related to the change in #16866.
The replace function used to return a string but now it returns a Suggestion which is an object with { label, value }.
Wasn't that the "breaking change" you were talking about?

Yes, did you had a problem with this or something else:

One known issue is that accessing suggestion's characters by index won't work with old API. It's easy to fix though. Instead of item[idx] use item.value[idx] or item.label[idx] directly.

The replace function used to return a string but now it returns a Suggestion which is an object with { label, value }.

Did this break any of your old code? Its toString function makes it coerce into the old string when needed, but of course, it's still not bulletproof.

The new version is 1.1 https://github.com/LeaVerou/awesomplete/issues/16850#issuecomment-197464182


Fix for Heading color in dark mode

Detailed description is available as a comment in the changed file.

Just noticed this is two commits. Can you squash them? Then I will merge.

Squashed two commits.

Sorry to be super annoying about the git hygiene, but could you also please use more descriptive commit message? Like the name of this PR. It should be possible to get a general idea of what the commit does from just scanning it in the log. The fixes keyword can go in the body of the commit message.

Yeah I understand. I just like the way Github links issues automatically from commit messages. It turned into a habit.

It will still do that, as well as close the related issue,￼ if the keyword an issue link are in the body of the commit.￼


Using --config=cuda_clang ignores compute capabilities and TensorRT values set by the configuration script

Issue type
Build/Install
Have you reproduced the bug with TensorFlow Nightly?
No
Source
source
TensorFlow version
2.17.0
Custom code
No
OS platform and distribution
No response
Mobile device
No response
Python version
No response
Bazel version
No response
GCC/compiler version
No response
CUDA/cuDNN version
No response
GPU model and memory
No response
Current behavior?
When running the configuration script, using Clang for CUDA (--config=cuda_clang) is an option. When this is enabled, however, the compute capability and TensorRT settings (which set TF_CUDA_COMPUTE_CAPABILITIES and TF_NEED_TENSORRT respectively) are ignored, as --config=cuda_clang sets these unconditionally.
Standalone code to reproduce the issue
$ TF_NEED_CUDA=1 TF_CUDA_CLANG=1 TF_CUDA_COMPUTE_CAPABILITIES=sm_87 TF_NEED_TENSORRT=0 ./configure

# The following does not respect the given compute capability and TensorRT options
$ bazel build //tensorflow/tools/pip_package:wheel --repo_env=WHEEL_NAME=tensorflow

# As a workaround, the variables can be set manually in the build command
$ bazel build //tensorflow/tools/pip_package:wheel --repo_env=WHEEL_NAME=tensorflow --repo_env=TF_CUDA_COMPUTE_CAPABILITIES=... --repo_env=TF_NEED_TENSORRT=...

Relevant log output
No response

Hi @hacker1024 ,
Apologies for the delay. Could you please tell what is the error you are facing exactly?
Thank you!

Hi @hacker1024 , Apologies for the delay. Could you please tell what is the error you are facing exactly? Thank you!

When enabling CUDA with Clang in the configuration script, and building like so, my settings (sm_87, no TensorRT) are ignored:
$ bazel build //tensorflow/tools/pip_package:wheel --repo_env=WHEEL_NAME=tensorflow
$ python -c 'from tensorflow.python.platform import build_info; print(build_info.build_info)'
OrderedDict([('cpu_compiler', '/usr/lib/llvm-17/bin/clang'), ('cuda_compute_capabilities', ['sm_60', 'sm_70', 'sm_80', 'sm_89', 'compute_90']), ('cuda_version', '12.2'), ('cudnn_version', '8'), ('is_cuda_build', True), ('is_rocm_build', False), ('is_tensorrt_build', True)])

In order to work around this, the variables need to be set again after .bazelrc runs:
$ bazel build //tensorflow/tools/pip_package:wheel --repo_env=WHEEL_NAME=tensorflow --repo_env=TF_CUDA_COMPUTE_CAPABILITIES=sm_87 --repo_env=TF_NEED_TENSORRT=0
$ python -c 'from tensorflow.python.platform import build_info; print(build_info.build_info)'
OrderedDict([('cpu_compiler', '/usr/lib/llvm-17/bin/clang'), ('cuda_compute_capabilities', ['sm_87']), ('cuda_version', '12.2'), ('cudnn_version', '8'), ('is_cuda_build', True), ('is_rocm_build', False), ('is_tensorrt_build', False)])

But this workaround depends on the implementation of the tensorrt Bazel configuration. tensorrt should never be enabled to begin with, and the selected CUDA capabilities should not be overwritten.


cmd/note-common.go: Fix context comments on diffs

@krobelus noticed that it wasnt possible to comment on the context portion
of a diff.  For example, when commenting on line 6 of
| newfile: Makefile oldfile: Makefile
|        @@ -5,6 +5,8 @@ SUBLEVEL = 0
|  5   5  EXTRAVERSION =
|  6   6  NAME = Merciless Moray
|  7   7
|      8 +# space
|      9 +
|  8  10  #
|  9  11  # DRM backport version
| 10  12  #
it was not possible to comment on line 6 and lab would output an error.
This is fixed by reworking the code to detect context diffs, however, this
only appears to work on code shown before the difflines.  There are
several open GitLab API issues that report errors when commenting on Merge
Request commits and it is likely that one of these is causing the error.
ex) https://gitlab.com/gitlab-org/gitlab-foss/-/issues/28599
Rework the code to allow for commenting on the context of diffs.
Signed-off-by: Prarit Bhargava<EMAIL_ADDRESS>

@krobelus @bmeneg @zampierilucas

Frustratingly I cannot get the code to work for context lines at the end of the diff :/  I've tried everything I could think of, including adding linePosition entries and forcing the line_code.  I still get the same error.

Hey @krobelus , I've uploaded a new version that takes all of your concerns into account and also fixes a bug where users should not be able to comment on the first line of the patch.

@bmeneg care to review?


Adding app.json

Description
This PR adds a app.json file to our project. This file will enable the use of review apps in Heroku. This will help us manually give a last check before merging into master for deployment.
Closes #145

This is still a WIP.

@jpadilla can you give this PR some 👀 ? Can we merge this or do you think it is no longer relevant?


Add ARCExpect.forall

signature:
// performs action (e.g. ARCExpect.isValid) for each CvParam with the given term
// on class ByTerm:
static member forall (
    term: CvTerm,
    action: CvParam -> unit,
    cvp: seq<CvParam>) = ...

reminder @omaus

Would be nice to also have an IParam overload. 😅


Difficult to use with Webpack.

First of all, Threlte is a very nice module.
That is why I would like to see it made available to various bundlers.
When importing a module, Threlte confuses specifying the file directly with specifying the folder where index.js resides.
This can work with Vite, but not with webpack unless a loader is provided. (I apologize if my knowledge is insufficient.)
Also, you need to specify "type": "module" because you don't add the ".js" extension when importing.
This is an option that you may not want to add depending on the project you are working on with webpack.
If you don't mind, could you please unify all imports with the extension as well...
Translated with DeepL.com (free version)

Simply adding jscofig.json to the module is fine.


Automate Text Summarization with OpenAI and PowerShell

Adding a new post relating to how to integrate openai gpt api and powershell
PR Summary
Automating tasks is the core of PowerShell scripting. Adding artificial intelligence into the mix takes automation to a whole new level. In this post, I am simplifying the process of connecting to OpenAI's powerful text summarization API from PowerShell.
PR Checklist

Do you want this post to be published on a specific date?: Y/N [Specify date]:
[X] I have read the contributors guide and followed the style and process guidelines
[X] PR has a meaningful title
[X] Includes content related an open issue

see Closing issues using keywords.

[X] This PR is ready to merge and is not Work in Progress

@microsoft-github-policy-service agree

closing this as it's a duplicate of #139 and in in the main branch


[Don't Create Medichanel from Cloudformation teamplate]

** Description of the error **
The error could not create a mediachannel with cloudformation tamplate.
** To reproduce **
Execute teamplate run
Enter name stack
Create stack
** Expected behavior **
Create a solution
** Please complete the following information about the solution: **

[] Version: Version 4.0.1
Last updated: 08/2022
Author: AWS
[] Region: US East (N. Virginia)
us-east-1

** Screenshots **
If possible, add a screenshot to help explain your issue (please do NOT include sensitive information).
** Additional context **
After I run the template there was an error lambda couldn't read the SSM paramter store, I fixed this by fixing the teamplate.

"ssm:GetParameters"
"ssm:GetParameter"
After running the template again, I have to wait more than 1 hour, but the mediachannel is still not created.

Thank you for opening this issue. We have added this to our backlog to look into.

Hi @NguyenDOanNhan,
Can you answer a few questions for us?

What values are you using for the parameters in the cloudformation stack?
What input type?
Does this repro consistently for you every single time? Did you ever successfully create a mediachannel?
Any other details to help us reproduce.

Thank you!


okhttp 4.10.0 change shrinkMode to strict and  Some of my image resources have been deleted

Question
I have a json configuration file that references the name of an image, but after I built the apk, the image was still removed and cannot be found，Look at the resource log. gradle deleted my picture,I don't know the specific reason.But if I roll back to version 4.9.3, it's normal,Here are the key messages:
Gradle environment:
Build time:   2022-08-05 21:17:56 UTC
Revision:     d1daa0cbf1a0103000b71484e1dbfe096e095918
Kotlin:       1.6.21
Groovy:       3.0.10
Ant:          Apache Ant(TM) version 1.10.11 compiled on July 10 2021
JVM:          11.0.12 (AdoptOpenJDK 11.0.12+1-202105061816)
OS:           Windows 10 10.0 amd64
Okhttp Version:
"okhttp"                            : "com.squareup.okhttp3:okhttp:4.10.0",
"okio"                              : "com.squareup.okio:okio:2.10.0",
1  json file content is (below assets):
{
"iconName": "uikit_selector_tab_task_checked",
"nameId": "R.string.commissioning_task_management",
}
2 icon is R.drawable.uikit_selector_tab_task_checked (a selector file)
3 How do I use it ?
Drawable drawable= ContextCompat.getDrawable(context,
context.getResources().getIdentifier("uikit_selector_tab_task_checked", "drawable", context.getPackageName()));
NotFoundException occurred：
NotFoundException Drawable ***:drawable/uikit_selector_tab_task_checked with resource ID #0x7f080ca5]
4 Why?
resource log : Skipped unused resource res ***drawable/uikit_selector_tab_task_checked replaced with small dummy file。
5 How to Solve this problem？
(1) roll back to version 4.9.3
(2) keep the resource in keep.xml
<resources     xmlns:tools="http://schemas.android.com/tools"     tools:keep="@drawable/uikit_*"> </resources>
But the second method is too difficult to maintain

This is not something we can help with.  Consider a site like stackoverflow, or report a bug for AGP?


Apply dart fixes to require_trailing_commas

Dart SDK Version Dart SDK version: 2.14.0 (stable) (Mon Sep 6 13:47:59 2021 +0200) on "macos_x64"
Reproduction
Add require_trailing_commas to analysis_options.yaml lints
TextStyle get hintTextFiesld => TextStyle(
      color: Colors.grey.shade500, debugLabel: 'lihjiolhoiukllinilobibib');
dart fix --dry-run

Result
Computing fixes in mobile (dry run)... 82.0s
Nothing to fix!

Expected
Offers to infer  the comma.
Display the fix on Fix, Fix.all on Vs code.

https://dart-review.googlesource.com/c/sdk/+/215403

I think this is happening again after I upgraded.
[✓] Flutter (Channel stable, 3.13.4, on macOS 13.4.1
    22F82 darwin-arm64, locale en-ID)
    • Flutter version 3.13.4 on channel stable at
      /Users/upbanx/dev/flutter
    • Upstream repository
      https://github.com/flutter/flutter.git
    • Framework revision 367f9ea16b (5 days ago),
      2023-09-12 23:27:53 -0500
    • Engine revision 9064459a8b
    • Dart version 3.1.2
    • DevTools version 2.25.0

[✓] VS Code (version 1.81.1)
    • VS Code at /Applications/Visual Studio
      Code.app/Contents
    • Flutter extension version 3.72.0

Somehow require_trailing_commas is detected again now. Could this be related to the package instead, such as  flutter_lints? Because my Flutter & Dart versions are still the same. Can't figure out what fixes the issue.
[✓] Flutter (Channel stable, 3.13.4, on macOS 13.4.1 22F82
    darwin-arm64, locale en-ID)
    • Flutter version 3.13.4 on channel stable at
      /Users/upbanx/dev/flutter
    • Upstream repository
      https://github.com/flutter/flutter.git
    • Framework revision 367f9ea16b (2 weeks ago), 2023-09-12
      23:27:53 -0500
    • Engine revision 9064459a8b
    • Dart version 3.1.2
    • DevTools version 2.25.0

[✓] VS Code (version 1.82.2)
    • VS Code at /Applications/Visual Studio Code.app/Contents
    • Flutter extension version 3.72.0

I'm facing the same issue

The require_trailing_commas lint does not appear to be included in flutter_lints. If you mean that the lint appears to be enabled now when it was disabled before, the only way I can think of that that could happen is if it's been added, directly or indirectly, to the analysis options file being used to analyze the code where it's being reported.

We will not be adding any work for the require_trailing_commas lint rule; instead leaning on the Dart formatter to provide commas, with the new Tall Style.


Adding device object in the resource object

Adding device object in the resources object, to account for device/host specific details of a resource.
Signed-off-by: Rajas<EMAIL_ADDRESS>

Why do you need the device in the resource object? What's the use case for it?

@rroupski
As mentioned in the PR description -> To account for device/host specific details of a resource. Think about a log record about launching/terminating an ec2 instance. The details of that instance/host/device will need to be stored, and device object is a perfect fit for it.

My concern is that the resource object is getting overloaded -- too many optional attributes and it is unclear when and which attributes should be used.
For the "launching/terminating an ec2 instance" use-case, where the device is a primary attribute or the "target" of the activity, adding the device object to the resource does not look like a right choice. The device should in the event itself, like the file or process objects in the filesystem/process activity events.
Also, why not use the existing Virtual Machine Activity class?

I don't think resource object is getting overcrowded. All the attributes in that object are clear and prescribe precise usage. Instance launch/terminate is only one such example of an "activity". Other usage of a resource(device) being a target is in a finding. "Which is the affected resource?" Device details being a part of a resource collection makes 100% sense to me.


ci: disable Bazel caching for msan build

This seems to break the build, cannot understand why, but disabling it
seems to fix it.
Part of the work for #5106

This change is

FWIW, I am not sure this is the right fix, it built on the PR, but did not build for the CI build:
https://source.cloud.google.com/results/invocations/124e5935-62bb-4fd3-a955-542ec3484b27

Note that the build did pass but took 97 minutes

Note that the build did pass but took 97 minutes

That was a build with a cold cache.  Builds with warm caches are taking more reasonable times, e.g. the latest took just under 10m.


cleaned up new warnings

In spite of the branch name this PR only contains warning fixes.
Fixes #721.

I accidently closed this the other day, but it is a good PR that should be merged when convenient.

I have merged these changes into my other PR #755, so I will take this PR down.


Harmonize return values of window_create() in rendering drivers

This is more than a cosmetic consistency change. I'd swear I've seen checks for -1 on return values of window_create() functions returning Error...

Thanks!


Misaligned breakpoint highlighting

I spoke to @NTaylorMullen about this. Even though there are certain situations where it's not possible to align the breakpoint highlighting, this apparently isn't one of them.
The following would look correct to me if the highlighting was shifted two columns to the right but I'm not sure if the
 tags are meant to be highlighted.

Is this the complete repro?

@rynowak Pretty much. I copied the first block of razor code from this razor pages tutorial into Pages/Contact.cshtml. Then I launched the site under the debugger and added a breakpoint to the
@message
 line and saw this.

@ajaybhargavb can you take a look at this and see if this a column alignment problem? Basically can we fix this with our current design approach? or does this require a new design for how we do alignment?

I looked at this and this is part of our design. Basically, we try to align the start of message with the generated code like below,

@message

  Write(message);
        ^     ^

Aligning this way makes us provide the correct line and character index for the purpose of debugging.

We looked at this, and this is a limitation baked into our current approach. We're going to keep this around and try to come up with a solution in the future, we'd like to fix this.


SAMZA-1787: Refactor TaskStorageManager to use SSPMetadataCache during init

Testing done:
Deployed test job with changelog with no existing file offset, verified through logging that oldest offset was registered with the changelog consumer in init stage for TaskStorageManager
Deployed test job with changelog with existing file offset, verified through logging that file offset was registered with the changelog consumer in init stage for TaskStorageManager

@rmatharu is taking this over through a separate PR


flutter_svg >=0.13.0 which requires Flutter SDK version >=1.5.9-pre.94 <2.0.0, version solving faile

flutter_svg >=0.13.0 which requires Flutter SDK version >=1.5.9-pre.94 <2.0.0, version solving faile
the package don't support this project

#1 问题与这个issue应该是一致的，解决方法请仔细阅读Readme的最后部分哦


Performance roadmap

We want to be able to create, combine, serialize, and use manifests that point to very large numbers of files. The largest Zarr stores we already see have O(1e6) chunks per array, and 10's or 100's of arrays (e.g. the National Water Model dataset).
To be able to virtualize this many references at once, there are multiple places that could become performance bottlenecks.

Reference generation
open_virtual_dataset should create ManifestArray objects from URLs with a minimum memory overhead. It is unlikely that the current implementation (i.e. kerchunk's SingleHdf5ToZarr to find generate references for a netCDF file) we are using is as efficient as possible because it first creates a python dict rather than a more efficient in-memory representation.

In-memory representation
It's crucial that our in-memory representation of the manifest be as memory-efficient as possible. What's the smallest that the in-memory representation of e.g. a single chunk manifest containing a million references could be? I think it's only ~100MB, if we use a numpy array (or 3 numpy arrays) and avoid object dtypes. We should be able to test this easily ourselves by creating a manifest with some dummy references data. See #33.

Combining
If we can fit all the ManifestArray objects we need into memory on one worker, this part is easy. Again using numpy arrays is good because np.concatenate/stack should be memory-efficient.
If the combined manifest is too big to fit into a single worker's memory then we might want to use dask to create a task graph, with the root tasks generating the references, concatenation via a tree of tasks (not technically a reduction because the output is as big as the input), then writing out chunkwise to some form of storage. Overall the result would be similar to how kerchunk uses auto_dask.

Serialization
Writing out the manifest to JSON as text would create an on-disk representation that is larger than necessary. Writing out to a compressed / chunked format such as parquet could ameliorate this. This could be kerchunk's parquet format or we could use a compressed format in the Zarr manifest storage transformer ZEP (see discussion in https://github.com/zarr-developers/zarr-specs/issues/287)

We should be trying to work out what the performance of each of these steps is, and they are separate so we can look at them individually.
cc @sharkinsspatial @norlandrhagen @keewis

To demonstrate my point about (2), it looks like storing a million references in-memory can be done using numpy taking up only 24MB.
In [1]: import numpy as np

# Using numpy 2.0 for the variable-length string dtype
In [2]: np.__version__
Out[2]: '2.0.0rc1'

In [3]: N_ENTRIES = 1000000

In [4]: SHAPE = (100, 100, 100)

# Taken from Julius' example in issue #93
# Notice these strings have slightly different lengths
In [5]: url_prefix = 's3://esgf-world/CMIP6/CMIP/CCCma/CanESM5/historical/r10i1p1f1/Omon/uo/gn/v20190429/uo_Omon_CanESM5_historical_r10i1p1f1_gn_185001-'

In [6]: paths = [f"{url_prefix}{i}.nc" for i in range(N_ENTRIES)]

In [7]: paths_arr = np.array(paths, dtype=np.dtypes.StringDType).reshape(SHAPE)

In [8]: paths_arr.shape
Out[8]: (100, 100, 100)

In [9]: paths_arr.nbytes
Out[9]: 16000000

In [10]: offsets_arr = np.arange(N_ENTRIES, dtype=np.dtype('int32')).reshape(SHAPE)

In [11]: offsets_arr.nbytes
Out[11]: 4000000

In [12]: lengths_arr = np.repeat(100, repeats=N_ENTRIES).astype('int32').reshape(SHAPE)

In [13]: lengths_arr.nbytes
Out[14]: 4000000

In [14]: (paths_arr.nbytes + offsets_arr.nbytes + lengths_arr.nbytes) / 1e6
Out[14]: 24.0

i.e. only 24MB to store a million references (for one ManifestArray) in memory.
This is all we need for (2) I think. It would be nice to put all 3 fields into one structured array instead of 3 separate numpy arrays, but apparently that isn't possible yet (see Jeremy's comment https://github.com/zarr-developers/zarr-specs/issues/287#issuecomment-2096636240). But that's just an implementation detail as this would all be hidden within the ManifestArray class anyway. So it looks like to complete (2) I just have to finish #39 but using 3 numpy arrays instead of one structured array.
24MB per array means that even a really big store with 100 variables, each with a million chunks, still only takes up 2.4GB in memory - i.e. your xarray "virtual" dataset would be 2.4GB to represent the entire store. This is smaller than worker memory, implying that I don't think we need dask to perform the concatenation (so we shouldn't need dask for (3)?).
Next thing we should look at is how much space these references would take up on-disk as JSON/parquet/special zarr arrays.

Next thing we should look at is how much space these references would take up on-disk as JSON/parquet/special zarr arrays.

See Ryan's comment (https://github.com/TomNicholas/VirtualiZarr/issues/33#issuecomment-1998639128) suggesting specific compressor codecs to use for storing references in zarr arrays.

even a really big store with 100 variables, each with a million chunks

I tried this out, see https://github.com/earth-mover/icechunk/issues/401#issue-2677032500


fix: add a primary key to an existing table

Description
Fixes: #8019
Checklist:

[x] Securely signed commits
[x] Component(s) with PHPDoc blocks, only if necessary or adds value
[x] Unit testing, with >80% coverage
[x] User guide updated
[x] Conforms to style guide

On develop it is surely fails the testProcessIndexesWithPrimaryKeyOnly.
$ vendor/bin/phpunit tests/system/Database/Live/ForgeTest.php
PHPUnit 9.6.13 by Sebastian Bergmann and contributors.

Runtime:       PHP 8.1.24
Configuration: /.../CodeIgniter4/phpunit.xml

............................................F.                                                                            46 / 46 (100%)

...

Time: 00:44.055, Memory: 18.00 MB

There was 1 failure:

1) CodeIgniter\Database\Live\ForgeTest::testProcessIndexesWithPrimaryKeyOnly
Failed asserting that actual size 0 matches expected size 1.

/.../CodeIgniter4/tests/system/Database/Live/ForgeTest.php:1705

FAILURES!
Tests: 46, Assertions: 112, Failures: 1.


Fix panic on adding worker node

https://github.com/rancher/rancher/issues/26792

We'd also need to update the cluster object, since this is only initializing the upgradeStrategy. Can close this in lieu of https://github.com/rancher/rancher/pull/26847

cool, thanks @kinarashah


oe_verify_report fails with OE_VERIFY_CRL_EXPIRED

CCF's quote verification started failing this morning (UK) with the following error:
10:26:26:751624 tid(0x7f48f5a6f740) (H)[ERROR]enforcing CRL (oe_result_t=(null))[OE_VERIFY_CRL_EXPIRED ../common/sgx/quote.c:5139712]

A similar behaviour is reproducible by running v0.5.0 OE's tests/report:
171: 10:27:34:359257 tid(0x7fcdeb9f90c0) (H)[ERROR]X509_verify_cert failed!
171:  error: (12) CRL has expired
171:  (oe_result_t=OE_VERIFY_CRL_EXPIRED)[../host/crypto/openssl/cert.c oe_cert_verify:721]
171: 10:27:34:359264 tid(0x7fcdeb9f90c0) (H)[ERROR]oe_cer_veTest failed: ../tests/report/common/tests.cpp(1055): test_remote_verify_report VerifyReport(report_buffer, report_size, NULL) == OE_OK

Note that the current date on the machine is Thu May 30 10:28:33 GMT 2019. However, when moving the time back to Thu May 30 10:22:00 GMT 2019, the tests (both CCF and OE) complete successfully. The threshold appears to be at 10:23:00 GMT.
There is nothing obvious from the quote certificate chain CRL (Next Update field for both PCK CRL and IntelSGXRootCA) that would make us think that this flag is set.
All of our CI and local builds are failing right now due to this. Feel free to let us know if you need additional detail on this.

In case it helps, this is the driver we run:
$ /sbin/modinfo intel_sgx
filename:       /lib/modules/4.18.0-1014-azure/updates/dkms/intel_sgx.ko
license:        Dual BSD/GPL
author:         Jarkko Sakkinen<EMAIL_ADDRESS>description:    Intel SGX Driver
srcversion:     18FB1A7E2798C015F3ABBAB
alias:          acpi*:INT0E0C:*
depends:
retpoline:      Y
name:           intel_sgx
vermagic:       4.18.0-1014-azure SMP mod_unload
signat:         PKCS#7
signer:
sig_key:
sig_hashalgo:   md4
And we believe the az-dcap-client is up to date:
$ sudo apt install az-dcap-client
Reading package lists... Done
Building dependency tree
Reading state information... Done
az-dcap-client is already the newest version (1.0).
0 upgraded, 0 newly installed, 0 to remove and 47 not upgraded.

This issue turned out to be a result of the fact that "sgx pck processor ca CRL" fetched from the caching service expired. We are working on a solution for it.

@soccerGB is there something that can/should be done to avoid that in the future? Like make the request with Cache-Control: no-cache?


[game] delegate randomly crash when calling "wallet_gia_create" from alice node

cucumber features/play_dice.feature
sometimes the delegate will crash at
https://github.com/bitsuperlab/cpp-play/blob/game/libraries/game/v8_game.cpp#L500

sometimes game script downloader will fail due to GFW , so the game create is not complete in this case.


Make it possible to extend the styles of the imported component

Not need fix.
Worked solutions
import { Button } from "@selfpub/selfpub-ui";

export const StyledElement = styled(Button)`
  border: 4px solid;
`;


link to release notes

https://trello.com/c/YobkwRo2/34

Codecov Report

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Request tracking configuration improvements

In some cases, injection and auto-config via AddApplicationInsights is not convenient: not all features are needed or some very specific config needs to be done.
It's complicated for request collection:

RequestTrackingTelemetryModule configures HostingDiagnosticListener and MvcDiagnosticsListener.

Hosting is responsible for

request tracking
appId injection into the response

Mvc listener is responsible for exception tracking.
In some cases I want to configure only requests, but not exceptions or vice versa (e.g. for functions I want to configure requests only, but exceptions are tracked in a different way), so I suggest:

configure them in a DI way: register list of IApplicationInsightDiagnosticListener in DI and pass the list as a parameter for RequestTrackingTelemetryModule
OR
split requests and exception tracking into 2 different modules.

OperationCorrelaitonTelemetryIntitializer extracts appId from the incoming request. It should be removed and done in hosting diagnostic listener.
Also, the initializer is internal so configuring it in the app explicitly via DI is not possible

fixed in #716


[9.0.x] ISPN-7991 Improve Compatibility between Rest and HotRod for text content

Created no-arg ctor to be used as compat mode marshaller
https://issues.jboss.org/browse/ISPN-7991

Some comments from https://github.com/infinispan/infinispan/pull/5278 should be applied here too.

Integrated in 9.0.x. Thanks @gustavonalle !