support for prometheus wrapped dbs

Support for prometheus wrapped dbs
Description
If someone uses django-prometheus in her project, she is going to use django_prometheus.db.backends.<...> as value in DATABASES as ENGINE key. Unfortunately it breaks dbbackup command:
Traceback (most recent call last):
  File "/home/ubuntu/reps/jitlearning/webpage_django/manage.py", line 22, in <module>
    main()
  File "/home/ubuntu/reps/jitlearning/webpage_django/manage.py", line 18, in main
    execute_from_command_line(sys.argv)
  File "/home/ubuntu/miniconda/envs/vocabuserver/lib/python3.10/site-packages/django/core/management/__init__.py", line 446, in execute_from_command_line
    utility.execute()
  File "/home/ubuntu/miniconda/envs/vocabuserver/lib/python3.10/site-packages/django/core/management/__init__.py", line 440, in execute
    self.fetch_command(subcommand).run_from_argv(self.argv)
  File "/home/ubuntu/miniconda/envs/vocabuserver/lib/python3.10/site-packages/django/core/management/base.py", line 414, in run_from_argv
    self.execute(*args, **cmd_options)
  File "/home/ubuntu/miniconda/envs/vocabuserver/lib/python3.10/site-packages/django/core/management/base.py", line 460, in execute
    output = self.handle(*args, **options)
  File "/home/ubuntu/miniconda/envs/vocabuserver/lib/python3.10/site-packages/dbbackup/utils.py", line 120, in wrapper
    func(*args, **kwargs)
  File "/home/ubuntu/miniconda/envs/vocabuserver/lib/python3.10/site-packages/dbbackup/management/commands/dbbackup.py", line 86, in handle
    self.connector = get_connector(database_key)
  File "/home/ubuntu/miniconda/envs/vocabuserver/lib/python3.10/site-packages/dbbackup/db/base.py", line 50, in get_connector
    connector_path = connector_settings.get("CONNECTOR", CONNECTOR_MAPPING[engine])
KeyError: 'django_prometheus.db.backends.postgresql'

All supported prometheus wrappers can be found in https://github.com/korfuri/django-prometheus/tree/master/django_prometheus/db/backends .
Easy solution is just to add all prometheus wrapper names in the dbbackup/db/base.py
Worked for my django_prometheus.db.backends.postgresql key. Didn't test the rest but looks straightforward.
This is my first contribution to open source, please tell me if I should've done something else.

There also needs to be some new documentation that mentions Prometheus support.

@Archmonger added lines in docs/databases.rst file.


✨ Record repo, actor and owner IDs

closes https://github.com/slsa-framework/slsa-github-generator/issues/140
closes https://github.com/slsa-framework/slsa-github-generator/issues/141
closes https://github.com/slsa-framework/slsa-github-generator/issues/130
closes https://github.com/slsa-framework/slsa-github-generator/issues/67

friendly ping for review

@ianlewis, I need your review. Thanks


the program throw exception "There is no active desktop required for moving mouse cursor" when run in window 7

the program throw exception "There is no active desktop required for moving mouse cursor" when run in window 7

使用vnc远程桌面可以解决这个问题，windows远程桌面必须保持窗口激活。


Performance regression with 1.1rc5?

Performance dropped from 1.851sec to 4.226sec for https://github.com/travis-ci/travis-core
https://gist.github.com/038f8f2103b656f38880
I've seen similar results with other travis-* repositories before.
If that's useful at all, this is Mac OS X 10.7.2, Ruby 1.9.2 (https://gist.github.com/2f4299b6a277878b972b), Gems: https://gist.github.com/046cf2f587bea5472971

I've noticed a rails boot time increase of 9s to 19s with 1.1rc5.
nick@nite:~$ uname -a
Linux nite 3.1.0-1-amd64 #1 SMP Mon Nov 14 08:02:25 UTC 2011 x86_64 GNU/Linux
nick@nite:~$ ruby -v
ruby 1.8.7 (2011-06-30 patchlevel 352) [x86_64-linux]

I think this is a performance regression from 1.1.pre.8 and 1.1.pre.9. Do you guys see performance changes b/t the rc's?

I only tried the difference between 1.1.rc.5 (which is what was install when I tried gem install bundler --pre) and 1.0.21 which is the current stable.

@hone yep, you're right:
bundler-1.1.pre.8
bundle install  1.86s user 0.17s system 99% cpu 2.044 total
bundler-1.1.pre.9
bundle install  3.79s user 0.16s system 99% cpu 3.958 total
... repeated this a couple of times with similar results each.

I did some digging today with @tenderlove and it looks like it might be related to https://github.com/carlhuda/bundler/commit/9d69030ffc7fd70cbe86edd64c7e0c1a228ba3a1 introducing a lot of calls to method_missing. I'll need to pair with @indirect and dig into this more. I'm not sure we're going to be able to speed this up for 1.1.0 :(

Butbut... The cache that that commit clears doesn't even exist in 1.0 :(
On Dec 15, 2011, at 6:26 PM, Terence<EMAIL_ADDRESS>wrote:

I did some digging today with @tenderlove and it looks like it might be related to https://github.com/carlhuda/bundler/commit/9d69030ffc7fd70cbe86edd64c7e0c1a228ba3a1 introducing a lot of calls to method_missing. I'll need to pair with @indirect and dig into this more. I'm not sure we're going to be able to speed this up for 1.1.0 :(

Reply to this email directly or view it on GitHub:
https://github.com/carlhuda/bundler/issues/1591#issuecomment-3172472

I noticed that too (#1508)

Okay, so Santiago (mostly or completely) fixed this in 9e1540c5d59b482869480ba138f4a4337ec78007. Please test rc6 and let us know how things look now. Thanks!

rc6 is not released, right? I've cloned master and built the gem locally. I'm still getting something like this:
$ gem list bundler

*** LOCAL GEMS ***

bundler (1.1.rc.5, 1.1.pre.8)
travis-ci $ time bundle check
The Gemfile's dependencies are satisfied
bundle check  4.13s user 0.10s system 100% cpu 4.225 total
$ gem list bundler

*** LOCAL GEMS ***

bundler (1.1.pre.8, 1.0.21)
$ time bundle check
The Gemfile's dependencies are satisfied
bundle check  1.49s user 0.11s system 99% cpu 1.601 total

Sorry for the confusion, I was looking at a CI failure and failed to release last night. RC6 is out now, please test against it. The master branch is not currently up to date, since we are finishing the 1.1 release out of the 1-1-stable branch.


Client Allocation Request for: Fei Yan - Kernelogic

Client Allocation Questions
Core Information

Name: Fei Yan - Kernelogic
Website / Social Media: @feiya200 slack
Region: North America
DataCap Requested: 5TiB
Addresses to be Notarized: f3srs3lcabsyqyxuz2o6vvsun7ri6bymyzi6hnzatq6pkaqqmuohnuhkj5eq5be2dluv7jd3vtfmnkandzkq2q
Notary Requested: ann-shin

This is to renew datacap granted here https://github.com/filecoin-project/filecoin-plus-client-onboarding/issues/134
Public record has been posted in the original issue.

Thanks for your request. Could you kindly add more information here？
1.Could you explain the source of gap between QualityAdjPower and RawBytePower of the miner id (f010617) that you provided in the supporting document.
2.Could you give a description of the cooperation mechanisms with miners you chose before.
3.Have you exhausted the allocated DataCap? Please add the timestamp for when the deal was transacted in the following format (YYYY-MM-dd HH:mm) and more information about stored data.
4.Is it convenient for users to retrieve and view data you stored? Can you provide detailed steps.
5.How did you perform in the past Slingshot Phase? Please enclose supporting document if any.
We hope to provide support for more participants with the limited amount of DataCap. We prefer to grant the application from which can produce valid and reliable data.

1.Could you explain the source of gap between QualityAdjPower and RawBytePower of the miner id (f010617) that you provided in the supporting document.

f010617 is my miner. I have received verified deals from other people before. Such as Charles Cao, askender and other unknown online deals. If you are asking if I have self-dealt using your approved datacap, the answer is no.
I'd like to know your policy about self-dealing, is it strictly prohibited or not? I'd like to store a copy on my own miner to guarantee retrievability but I will not start doing it before getting a definitive answer from you.

2.Could you give a description of the cooperation mechanisms with miners you chose before.

I ask the miners in slack whether they are free to accept deals, then I create sealing tasks in FILSWAN, a community project to collaborate offline deals.

3.Have you exhausted the allocated DataCap? Please add the timestamp for when the deal was transacted in the following format (YYYY-MM-dd HH:mm) and more information about stored data.

Yes it is exhausted. See my updated CSV for filename, minerID, date etc.
https://github.com/kernelogic/filecoin/blob/main/filplus/f3rfb7aarwmrulwc4rqy4526zvopnsnbsmcfokhbi743kq2shaybo46cbjqezvmhhjkejpk6xqbafixvplq5xa.csv

4.Is it convenient for users to retrieve and view data you stored? Can you provide detailed steps.

By using the posted CSV, users can easily retrieve the files using provided minerID and data CID. Using command like this:
lotus client retrieve --miner [minerId] [dataCid] [outputPath]

5.How did you perform in the past Slingshot Phase? Please enclose supporting document if any.

Slingshot 1:
Free Music Archive browser
Slingshot 2.1:
GHTorrent dataset
Free Music Archive browser
Slingshot 2.2:
Blackbird Dataset
Filecoin Trusted Setup
Public Domain Movies
GHTorrent dataset
Again, I'd like to know your policy about participating slingshot, is it prohibited or not? I will not start using your datacap for slingshot before getting a definitive answer from you.

We found that the allocated DataCap have not been used up. Please apply again after using up.
(./lotus-shed verifreg check-client  f3rfb7aarwmrulwc4rqy4526zvopnsnbsmcfokhbi743kq2shaybo46cbjqezvmhhjkejpk6xqbafixvplq5xa
68719476736)

It is used up now
lotus-shed verifreg check-client f3rfb7aarwmrulwc4rqy4526zvopnsnbsmcfokhbi743kq2shaybo46cbjqezvmhhjkejpk6xqbafixvplq5xa
2021-03-01T17:07:52.838Z	WARN	lotus-shed	lotus-shed/main.go:86	client %!s() is not a verified client:
main.glob..func62
/opt/lotus/cmd/lotus-shed/verifreg.go:262

Through considering synthetically with the situation, we’ll allocate 1TiB to you. Please confirm whether to accept it. The Foundation notary will stop processing datacap requests that aim to store Slingshot public datasets but instead focusing on those making an effort to store (1) data that can be tied to a specific use case built on Filecoin and (2) other type of open source data (in the scientific, systemically important realm). we keep the same attitude. We prefer to the client who store data legally generated or otherwise obtained during the ordinary course of business that have practical application scene.

OK I will take it.

Please confirm your address for the datacap allocation :
f3srs3lcabsyqyxuz2o6vvsun7ri6bymyzi6hnzatq6pkaqqmuohnuhkj5eq5be2dluv7jd3vtfmnkandzkq2q

Hi, please ensure whether the Filecoin address is correct.

Yes it is correct.

Request Approved
Your Datacap Allocation Request has been approved by the Notary
Message sent to Filecoin Network

bafy2bzacebkjax73ovacdyr5zd3cv2igs744m63wrdx6vduuquolqqxll36bo

Address

f3srs3lcabsyqyxuz2o6vvsun7ri6bymyzi6hnzatq6pkaqqmuohnuhkj5eq5be2dluv7jd3vtfmnkandzkq2q

Datacap Allocated

1TiB

You can check the status of the message here: https://filfox.info/en/message/bafy2bzacebkjax73ovacdyr5zd3cv2igs744m63wrdx6vduuquolqqxll36bo

Hi, @kernelogic
I have noticed that you haven't used up the 1TiB allocated before. Is there something wrong with it?
In addition, about 500GiB that has been used is stored on one node. Please pay attention to distributivity and select more nodes.

Hi, 1TB is tough to distribute broadly so I stopped after a while. Sorry about that.
I will try distribute to other nodes for the remaining of the allocation and post the result here.

Ok.


Follow the setup guide, but not work

the error is
curl: (35) OpenSSL SSL_connect: Connection reset by peer in connection to chatgpt-api.xxx.workers.dev:443

Is there a step I've missed?

It is my network problem


1_stdlib/VarArgs.swift

******************** TEST 'Swift :: 1_stdlib/VarArgs.swift' FAILED ********************
Script:
--
rm -rf /home/modocache/GitHub/apple/build/Ninja-ReleaseAssert/swift-linux-x86_64/test-android-armv7/1_stdlib/Output/VarArgs.swift.tmp && mkdir -p /home/modocache/GitHub/apple/build/Ninja-ReleaseAssert/swift-linux-x86_64/test-android-armv7/1_stdlib/Output/VarArgs.swift.tmp && /home/modocache/GitHub/apple/build/Ninja-ReleaseAssert/swift-linux-x86_64/bin/swiftc -target armv7-none-linux-androideabi -Xlinker --allow-shlib-undefined -Xlinker -pie  -module-cache-path '/tmp/swift-testsuite-clang-module-cache0D5zbw'   -module-cache-path '/tmp/swift-testsuite-clang-module-cache0D5zbw' /home/modocache/GitHub/apple/swift/test/1_stdlib/VarArgs.swift -o /home/modocache/GitHub/apple/build/Ninja-ReleaseAssert/swift-linux-x86_64/test-android-armv7/1_stdlib/Output/VarArgs.swift.tmp/a.out -module-name main -Xfrontend -disable-access-control && /home/modocache/GitHub/apple/swift/test/../../swift-android-extras/rundroid /home/modocache/GitHub/apple/build/Ninja-ReleaseAssert/swift-linux-x86_64/test-android-armv7/1_stdlib/Output/VarArgs.swift.tmp/a.out -parse-stdlib /home/modocache/GitHub/apple/swift/test/1_stdlib/VarArgs.swift | FileCheck /home/modocache/GitHub/apple/swift/test/1_stdlib/VarArgs.swift
--
Exit Code: 1

Command Output (stderr):
--
/home/modocache/GitHub/apple/swift/test/1_stdlib/VarArgs.swift:15:25: error: cannot convert value of type '(_) -> Int32' to expected argument type 'CVaListPointer -> _'
  withVaList(arguments) {
                        ^
/home/modocache/GitHub/apple/swift/test/1_stdlib/VarArgs.swift:39:20: error: cannot convert value of type '(_) -> Int32' to expected argument type 'CVaListPointer -> _'
  withVaList(args) {
                   ^
/home/modocache/GitHub/apple/swift/test/1_stdlib/VarArgs.swift:63:20: error: cannot convert value of type '(_) -> Int32' to expected argument type 'CVaListPointer -> _'
  withVaList(args) {
                   ^

test/1_stdlib/VarArgs.swift fails to compile when targeting android-armv7. @hpux735 tells me it also fails for Linux armv6/armv7.
I found the error message hard to understand. cannot convert value of type '(_) -> Int32' to expected argument type 'CVaListPointer -> _' -- huh? So I made the following change:
diff --git a/test/1_stdlib/VarArgs.swift b/test/1_stdlib/VarArgs.swift
index 2791711..6e537f0 100644
--- a/test/1_stdlib/VarArgs.swift
+++ b/test/1_stdlib/VarArgs.swift
@@ -12,8 +12,8 @@ typealias CGFloat = Double
 #endif

 func my_printf(format: String, _ arguments: CVarArgType...) {
-  withVaList(arguments) {
-    vprintf(format, $0)
+  withVaList(arguments) { (vaList: CVaListPointer) in
+    vprintf(format, vaList)
   }
 }

This results in the following error message, which is much easier to understand:
/home/modocache/GitHub/apple/swift/test/1_stdlib/VarArgs.swift:16:21: error: cannot convert value of type 'CVaListPointer' to expected argument type '__va_list'
    vprintf(format, vaList)
                    ^~~~~~

Aha! So vprintf expects a __va_list, but we're giving it a CVaListPointer.
As far as I understand, it's lib/ClangImporter's responsibility to convert certain raw C types like __va_list to CVaListPointer. Sure enough, there are a few commits related to va_list:

https://github.com/apple/swift/commit/2b6bee7fb8063161ecb3365abf31eb2d2d93a18b -- Imports C va_list as CVaListPointer. The author struggles with behavior on arm vs. x86_64--perhaps the same sort of problem we're seeing here?
https://github.com/apple/swift/commit/9d74d25e50290d3cdeff5b30ecb72aa77e627ddb -- "va_list on i386 and arm64 is a pointer. On armv7, it's a struct that /contains/ a pointer. But on x86_64, it's an array of one struct element, which means it decays to a pointer as an argument but not as a variable or
struct field." The patch cleans up the va_list import implementation.

It appears that on android-armv7 and linux-armv7, va_list is not being imported as CVaListPointer, and as a result our vprintf function takes a __va_list instead of a CVaListPointer.
Just for fun I tried adding the following mapping:
diff --git a/lib/ClangImporter/MappedTypes.def b/lib/ClangImporter/MappedTypes.def
index 474a78b..ccf4530 100644
--- a/lib/ClangImporter/MappedTypes.def
+++ b/lib/ClangImporter/MappedTypes.def
@@ -126,6 +126,7 @@ MAP_STDLIB_TYPE("u_int64_t", UnsignedInt, 64, "UInt64", false, DoNothing)
 // stdarg.h types.
 // FIXME: why does this not catch va_list on x86_64?
 MAP_STDLIB_TYPE("va_list", VaList, 0, "CVaListPointer", false, DoNothing)
+MAP_STDLIB_TYPE("__va_list", VaList, 0, "CVaListPointer", false, DoNothing)

 // libkern/OSTypes.h types.
 MAP_STDLIB_TYPE("UInt", UnsignedInt, 32, "CUnsignedInt", false, DoNothing)

This actually gets 1_stdlib/VarArgs.swift to compile, but it fails with the following error:
/home/modocache/GitHub/apple/swift/test/1_stdlib/VarArgs.swift:21:12: error: expected string not found in input
 // CHECK: The answer to life and everything is 42, 42, -42, 3.14
           ^
<stdin>:1:1: note: scanning from here
The answer to life and everything is 42, 42, -42, 0.000000
^

Anyway, something is wrong with va_list importing on android-armv7 and linux-armv7, but I'm not sure what yet.

va_list is part of an architecture's calling conventions, so it's important to do whatever's expected on that architecture. I'm a little surprised the existing mapping didn't work, but the one you're adding should be fine.
For the actual arguments being passed incorrectly, you'll need to make sure that the logic in stdlib/public/core/VarArgs.swift actually makes sense for your platform. In this case that's probably the AAPCS, although I'm surprised that either Apple or Linux diverged here.

Awesome, thanks @jrose-apple! I'll try adding the mapping and double-checking the logic in stdlib/public/core/VarArgs.swift. :bow:

The following gets this test passing for me:
diff --git a/lib/ClangImporter/MappedTypes.def b/lib/ClangImporter/MappedTypes.def
index 474a78b..77e4620 100644
--- a/lib/ClangImporter/MappedTypes.def
+++ b/lib/ClangImporter/MappedTypes.def
@@ -126,6 +126,7 @@ MAP_STDLIB_TYPE("u_int64_t", UnsignedInt, 64, "UInt64", false, DoNothing)
 // stdarg.h types.
 // FIXME: why does this not catch va_list on x86_64?
 MAP_STDLIB_TYPE("va_list", VaList, 0, "CVaListPointer", false, DoNothing)
+MAP_STDLIB_TYPE("__va_list", VaList, 0, "CVaListPointer", false, DoNothing)

 // libkern/OSTypes.h types.
 MAP_STDLIB_TYPE("UInt", UnsignedInt, 32, "CUnsignedInt", false, DoNothing)
diff --git a/stdlib/public/core/VarArgs.swift b/stdlib/public/core/VarArgs.swift
index ce4ee0e..83f5a7e 100644
--- a/stdlib/public/core/VarArgs.swift
+++ b/stdlib/public/core/VarArgs.swift
@@ -290,7 +290,7 @@ final public class VaListBuilder {
     // supported vararg type is greater than the alignment of Int.
     // FIXME: this implementation is not portable because
     // alignof differs from the ABI alignment on some architectures
-#if os(watchOS) && arch(arm)   // FIXME: rdar://21203036 should be arch(armv7k)
+#if (os(watchOS) || os(Android)) && arch(arm)   // FIXME: rdar://21203036 should be arch(armv7k)
     if let arg = arg as? _CVarArgAlignedType {
       let alignmentInWords = arg._cVarArgAlignment / sizeof(Int)
       let misalignmentInWords = count % alignmentInWords

android-armv7 is soft float, and I'm assuming that armv7k is as well--I think that's the real issue here. So instead of checking for #if os(watchOS) && arch(arm), we should probably check for something like #if arch(arm) && floattype(hard). Is something like floattype available? Should it be added? @jrose-apple
I think the work @hpux735 is doing on hard float, though... so I'm curious what sort of failure output you're seeing, @hpux735.

@modocache This is what I get from test/1_stdlib/VarArgs.swift  on a linux-armv7 with hard float (GNUEABIHF)
FAIL: Swift :: 1_stdlib/VarArgs.swift (111 of 2471)
******************** TEST 'Swift :: 1_stdlib/VarArgs.swift' FAILED ********************
Script:
--
rm -rf /mnt/temp/Ninja-ReleaseAssert/swift-linux-armv7/test-linux-armv7/1_stdlib/Output/VarArgs.swift.tmp && mkdir -p /mnt/temp/Ninja-ReleaseAssert/swift-linux-armv7/test-linux-armv7/1_stdlib/Output/VarArgs.swift.tmp && /home/wdillon/swift-build/build/Ninja-ReleaseAssert/swift-linux-armv7/bin/swiftc -target armv7-unknown-linux-gnueabihf  -module-cache-path '/tmp/swift-testsuite-clang-module-cacheZiExII'   -module-cache-path '/tmp/swift-testsuite-clang-module-cacheZiExII' /home/wdillon/swift-build/swift/test/1_stdlib/VarArgs.swift -o /mnt/temp/Ninja-ReleaseAssert/swift-linux-armv7/test-linux-armv7/1_stdlib/Output/VarArgs.swift.tmp/a.out -module-name main -Xfrontend -disable-access-control &&  /mnt/temp/Ninja-ReleaseAssert/swift-linux-armv7/test-linux-armv7/1_stdlib/Output/VarArgs.swift.tmp/a.out -parse-stdlib /home/wdillon/swift-build/swift/test/1_stdlib/VarArgs.swift | FileCheck /home/wdillon/swift-build/swift/test/1_stdlib/VarArgs.swift
--
Exit Code: 1

Command Output (stderr):
--
/home/wdillon/swift-build/swift/test/1_stdlib/VarArgs.swift:15:25: error: cannot convert value of type '(_) -> Int32' to expected argument type 'CVaListPointer -> _'
  withVaList(arguments) {
                        ^
/home/wdillon/swift-build/swift/test/1_stdlib/VarArgs.swift:39:20: error: cannot convert value of type '(_) -> Int32' to expected argument type 'CVaListPointer -> _'
  withVaList(args) {
                   ^
/home/wdillon/swift-build/swift/test/1_stdlib/VarArgs.swift:63:20: error: cannot convert value of type '(_) -> Int32' to expected argument type 'CVaListPointer -> _'
  withVaList(args) {
                   ^

--

********************

@hpux735 Awesome, thank you! And what if you apply the following patch?
```diff
diff --git a/lib/ClangImporter/MappedTypes.def b/lib/ClangImporter/MappedTypes.def
index 474a78b..77e4620 100644
--- a/lib/ClangImporter/MappedTypes.def
+++ b/lib/ClangImporter/MappedTypes.def
@@ -126,6 +126,7 @@ MAP_STDLIB_TYPE("u_int64_t", UnsignedInt, 64, "UInt64", false, DoNothing)
 // stdarg.h types.
 // FIXME: why does this not catch va_list on x86_64?
 MAP_STDLIB_TYPE("va_list", VaList, 0, "CVaListPointer", false, DoNothing)
+MAP_STDLIB_TYPE("__va_list", VaList, 0, "CVaListPointer", false, DoNothing)

 // libkern/OSTypes.h types.
 MAP_STDLIB_TYPE("UInt", UnsignedInt, 32, "CUnsignedInt", false, DoNothing)

My theory is that the above patch will get your test to compile and pass.

I'm not sure if floattype is something we want as a first-class predicate just yet, but maybe if we underscored it (_floattype) for now. That's a discussion for a separate PR on the main Swift repo, though.
(I think you also meant "watchOS uses hard float". At least, that's what I see from reading the LLVM target info; I can't find official documentation on developer.apple.com, and I don't actually know myself.)

After further investigation we're beginning to think this isn't a hard float vs. soft float issue. android-armv7 is soft float, whereas linux-armv7 is hard float, but both have the same problem.
We're thinking that actually iOS and tvOS don't conform to AAPCS, so those are the only ARM-based systems that won't need this check. Every other ARM-based system will.
The solution we're going with is going to be adding va_list mappings for each platform and adding os(Linux) || os(Android) to the watchOS os check. Alternatively, it might be a good idea to check !os(iOS) && !os(tvOS) -- but we can discuss in a pull request.

Oh, good catch! Indeed that is in Apple's docs and I just breezed over it.

The function calling conventions used in the ARMv6 environment are the same as those used in the Procedure Call Standard for the ARM Architecture (release 1.07), with the following exceptions:

Large data types (larger than 4 bytes) are 4-byte aligned.
…

There's no 32-bit tvOS, so we shouldn't need to worry about that. Feel free to submit a pull request upstream.

It looks like the arm64/aarch64 conventions are different too, if/when that becomes interesting.

@jrose-apple https://github.com/apple/swift/pull/1271 :+1:


Mono compatability

I tried building it in mac. Look's like the framework version 4.6 isn't available in Mono. Is there a specific feature of 4.6 that is being used.

Hi,
No there are no real reasons for 4.6, I'm planning to bring the version requirement down. (it should be 4.5.2 in the Master branch atm)


WebGL warnings in Firefox

There are new WebGL warnings in Aurora (Firefox 27)

Error: WebGL: A texture is going to be rendered as if it were black, as per the OpenGL ES 2.0.24 spec section 3.8.2, because it is a 2D texture, with a minification filter requiring a mipmap, and is not mipmap complete (as defined in section 3.7.10).

I believe this is a Firefox bug (issue) since we later set the texture filters before rendering.  We can workaround it if need be.

Since this is a longstanding Firefox issue, do we just want to close this?  There's noting we can do about it on our end and if anyone searches for the issue in our repository they'll still find it even if it's closed.

Sounds good.


Attach book name to output file

This is more of a QOL update but I believe adding the book's title to the output file might look better.

Looks cool, thanks for your contribute! Merged.


feat: added a 2 second delay in all the sample apps

Added a 2 second delay in all the sample apps to make them work in the docker mode with the latest Keploy.

The Lint is failing

@Sonichigo, the lint issues have been fixed. Let me know if any other change is needed.


error in forecasting code.

Hi,
when I run exe_forecasting.py it gives me type error.
The type error is :
TypeError: embedding(): argument 'indices' (position 2) must be Tensor, not NoneType
It is from this part of the code:
main_model.py", line 356, in get_side_info
feature_embed = self.embed_layer(feature_id).unsqueeze(1).expand(-1,L,-1,-1)
It would be great if you fix this.

Hi,
I have run the code with the sample electricity dataset and there is no problem.
If you use your original dataset, please set "target_dim" in exe_forecasting.py.

I am having the same problem, using the electricity dataset provided

Hi all,
Sorry for the inconvenience.
I have understood the issue and fixed the code.

@y-tashi I can confirm that it is working now.
However, I am getting weird results when predicting. I get inf and all the computed losses are nan. I looked a bit in the results and they seem to blow up more and more from sample to sample.
I am running the model on 'mps' device, which is the GPU provided by apple on their Macbook Ms and I am suspecting that is where the error is coming from.
If anyone has encounterd this problem and identified any possible solutions, that would be a life saver as I am trying to write my Masters thesis and I don't have a Nvidia GPU.
I am also obtaining this type of results when predicting using TimeGrad model as well.

OK, so I ran it on cpu and indeed I stop getting inf and nan values. Any idea what (maybe a particular pytorch module like LayerNorm or smth) is causing mps to blow up? I am thinking I could rewrite the module and maybe than it will work.


Design: figure out nightly testing plans

Problem Statement
To execute on Emblem's testing plans, we will need to create nightly tests of some kind. There are two key questions we need to answer:

What needs to be tested?
How should the tests be implemented?

Proposal: Design
What to test
We will need to figure out how to test the Website, Content API, and Delivery components.
How to test
We propose a three-step process for our nightly testing:

Build containers, and push them to Artifact Registry
Deploy a fresh version of the Emblem application (website and content API components) as a Delivery test.
Run the website's "end-to-end" (E2E) tests against the deployed application

Proposal: Implementation
We should implement this using three scheduled builds on three (separate) Cloud Pub/Sub topics:

nightly-builds will trigger container builds + pushes
nightly-deploys will trigger deployments to Cloud Run
nightly-tests will trigger end-to-end tests of the deployed Emblem application

Avoiding race conditions
To avoid race conditions (and ensure we always test the latest working version of Emblem), we should create a 1-hour delay between the topics being triggered:
flowchart LR
    A["Build"]-- 1 hour -->B["Deploy"]-- 1 hour -->C["Test"]

Deployments as tests
We plan to use the website/content API's deployment process as a (smoke) test of our delivery component.
✅ We'll run our deployment 'tests' automatically
✅ Testing our 'actual' deployment workflow (as opposed to one with mocked dependencies) gives us high-fidelity deployment tests
❌ Can be slow to return results
❌ May not always test the latest versions of dependencies. (For example, failures in docker push may result in the Website or Content API tests using an old container version.)
Other options
Testing components in isolation
One alternative would be to test each component in question (website, content API, and delivery) independently from each other.
Tradeoffs relative to our proposal:
✅ Reduces test flakiness
✅ Potentially faster test runs
❌ Doesn't test cross-component integration
Sequential testing ("one big test")
Another alternative would be to test each component sequentially (for example, as part of a single Cloud Build process).
Tradeoffs relative to our proposal:
✅ Faster overall build times
❌ Upstream failures would prevent us from testing downstream dependencies
Use unit tests only
Our existing unit tests currently run on a presubmit basis. Theoretically, we could run them on a nightly basis too.
Tradeoffs relative to our proposal:
✅ Faster test runs
✅ Reduces test flakiness
❌ Not very informative (vs. presubmit unit tests)
❌ Doesn't test cross-component integration
Next steps

Discuss these options as a team (in this thread!).
Decide on a testing option.
Record that decision as a decision record.
Implement the required changes.

We discussed this during a meeting today; @grayside seems in favor of the sequential testing approach.
I'm fine with that, so long as we're fine with the (major) tradeoff:

If a build failure occurs upstream, anything downstream of it won't be tested.

I'm curious as to @engelke's opinion too.

This is 🚨 semi-blocked 🚨 on #414 (to minimize churn / merge conflicts).


clustermesh: downtime/dropped packets due to network policy on upgrade

Is there an existing issue for this?

[X] I have searched the existing issues

What happened?
We are currently running Cilium on EKS in chaining mode with aws-cni. We are utilizing clustermesh across 6 clusters and the configuration and installation is managed by FluxCD. Our application has an auth service that lives in one of the six clusters and proxy service that lives in all clusters. The proxies connect to each other in a mesh as well as initiate a connection to the auth service. The proxies rely on a global service to connect to auth, they dial each other directly via a different discovery mechanism.
Single cluster upgrades don't appear to be an issue but if multiple clusters upgrade close enough together we observe connection issues between proxies in those clusters. Specifically we are looking at the metric hubble_drop_total{reason="Policy denied"} as well as metric on our application that indicates the number of other proxies a proxy is connected to. Looking at the logs of the cilium agent of the node where affected proxies were running it seems like it isn't uncommon to see a connection to etcd, disconnect, and reconnect. It is fairly reproducible by running kubectl rollout restart deployment clustermesh-apiserver in cluster1 and kubectl rollout restart ds cilium in cluster2.
I considered trying to split the cilium install and the clustermesh install into separate helm installs as that would give us control when they would restart and not happen at the same time. Unfortunately, the cilium-ca secret is expected to be created every time and would cause a conflict (there may be other but this was the first roadblock I hit, could potentially get around this by allowing users to specify this).
We are hoping to better understand the following:

Expectations of upgrades as the upgrade guide states Minimal to None affect on L3/L4 and if we are hitting that or if we are hitting something else.
Is it expected that Cilium upgrades in clustermesh happen one cluster at a time? Our FluxCD reconciles every 10 min and currently have no coordination that at the moment but are looking at options for this.
Would we be better off configuring our cilium install to be backed by etcd? That seems like it would remove the possibility of etcd connections being broken on cilium startup since there wouldn't be a clustermesh-apiserver pod being recreated. Is there documentation for this by chance?
Possibly separate the etcd container (and give it a PV) from the apiserver container so that clustermesh isn't rolled at the same time? Any gotchas with this approach?

Thanks for all the work on this awesome CNI!
Cilium Version
1.12.3
Kernel Version
Linux ip-10-16-112-106.us-west-2.compute.internal 5.4.242-155.348.amzn2.x86_64 #1 SMP Mon May 8 12:52:40 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux
Kubernetes Version
Server Version: v1.23.17-eks-0a21954
Sysdump
Sysdump file was too large to upload
Relevant log output
level=info msg="Established connection to remote etcd" clusterName=redact config=/var/lib/cilium/clustermesh/redact kvstoreErr="<nil>" kvstoreStatus="etcd: 1/1 connected, lease-ID=0, lock lease-ID=0, has-quorum=timeout while waiting for initial connection, consecutive-errors=1: https://redact:2379 - 3.5.4 (Leader)" subsys=clustermesh

Anything else?
No response
Code of Conduct

[X] I agree to follow this project's Code of Conduct

I did some additional testing here.
Observing the hubble UI during my testing I see my traffic generator app being classified as Unknown app and world until eventually it gets the correct identity and traffic starts being allowed once more.
v1.14.0-rc.0:
Using kvstoremesh I saw roughly 5 minutes dropped packets with POLICY_DENIED as the reason when cilium agents and the clustermesh-apiserver pod were restarted in the same cluster. Without kvstoremesh enabled and using the original test method of restarting cilium agents in one cluster and clustermesh-apiserver in another I saw between 60s and 120s of dropped packets due to policy enforcement.
v1.12.3->v1.12.11->v1.13.4->v1.14.0-rc.0 using etcd:
0 or near 0 increments in hubble_drop_total{reason="Policy denied"} so I am guessing this the best path forward for Cilium upgrades and avoiding packet drops due to policy enforcement.

Thanks @rcanderson23 for the detailed issue!
I've been able to consistently reproduce the connectivity issue scaling the clustermesh-apiserver to zero replicas in one cluster and restarting the cilium agents in the other. Essentially, the issue happens when, during the bootstrap phase, the agents regenerate all local endpoints, switching, among the others, to using the newly populated ipcache map. Yet, at that point, the ipcache map will correctly contain all local entries, while the ones referring to the remote clusters might still be missing, breaking the connectivity towards remote endpoints. Similarly, policy entries get also synchronized with the known state, possibly removing entries referring to remote endpoints if not yet discovered.
Please note that scaling the clustermesh-apiserver to zero replicas makes this issue easy to reproduce, but it would also happen restarting the agents only, if the endpoints get regenerated before synchronizing all ipcache entries from the remote etcd --- it would just be less likely (depending on the total number of remote endpoints.
It is not yet fully clear to me a possible solution to limit (or better fix) this issue. The tricky part about solving this issue is not introduce a hard dependency on remote clusters, as that could easily lead to chicken-and-egg issues preventing the entire cluster mesh from converging.

Looking at the logs of the cilium agent of the node where affected proxies were running it seems like it isn't uncommon to see a connection to etcd, disconnect, and reconnect.

There's one bug I'm aware of (and that has been recently fixed by https://github.com/cilium/cilium/pull/26363) which caused a valid connection to the remote kvstore to be restarted, typically happening when the clustermesh-apiserver and the agents get restarted at the same time. I guess that it is what you observed in this case.

Expectations of upgrades as the upgrade guide states Minimal to None affect on L3/L4 and if we are hitting that or if we are hitting something else.

My understanding is that the upgrade guide expectations currently apply to single cluster scenarios, while there are still a few rough edges that would benefit from improvements in the multi cluster case (a few known issues have also already been fixed in v1.14).

Using kvstoremesh I saw roughly 5 minutes dropped packets with POLICY_DENIED as the reason when cilium agents and the clustermesh-apiserver pod were restarted in the same cluster. Without kvstoremesh enabled and using the original test method of restarting cilium agents in one cluster and clustermesh-apiserver in another I saw between 60s and 120s of dropped packets due to policy enforcement.

It is expected that kvstoremesh introduces a bit of additional latency, but this difference seems pretty severe to me. Could you please share the logs of the cilium agents, clustermesh-apiserver and kvstoremesh containers from that run to double-check if anything wrong happened?

Sorry for the late reply and thanks for the detailed answer. This definitely helps us determine our best path forward.

It is expected that kvstoremesh introduces a bit of additional latency, but this difference seems pretty severe to me. Could you please share the logs of the cilium agents, clustermesh-apiserver and kvstoremesh containers from that run to double-check if anything wrong happened?

Unfortunately, it was with an ephemeral setup and don't have logs. I retested and my results this time seem to show similar results in a 3 node cluster with 50 "workload namespaces with global services" with kvstoremesh enabled and disabled so it is possible something abnormal happened that one time as I don't seem to be able to repeat it.

@rcanderson23 The fixes to prevent the connection drops mentioned in this issue have just been merged (and are being backported to v1.14). Please feel free to reopen this issue (or a new one) if you still encounter problems.


Add some missing ciphers in 'enc' document

The original issue is #7273 and this commit fixes part of that issue.

Checklist

[x] documentation is added or updated

I guess this should affect 1.1.1 as well.

Pushed to master (41a6fa7) and 1.1.1 (ea94f19), closing...


No module named qiskit.chemistry.components

What is the expected enhancement?
In the tutorial section 'Creating Your First Qiskit Chemistry Programming Experiment', the line:
from qiskit.chemistry.components.initial_states import HartreeFock
produces the error:
No module named qiskit.chemistry.components
I think the tutorial needs to be updated if the code has been deprecated. I apologise if this is an issue local to me.

The tutorials work, are tested and kept in sync with the current release in Pypi, not with the latest code in github.

The readme you are looking at has been updated to reflect the code as it exists in master. I imagine you have installed the stable release from PyPi. In which case look at this link which should give you what you need https://github.com/Qiskit/qiskit-aqua/tree/stable

That's perfect - thank you both.


pull request for e2e test at 02/06/2017 12:45:08

:white_check_mark: Validation status: passed
For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


Sparkle/Questions

Over the weekend I realized that we hadn't discussed what will be the scope of the Sparkel dev environment ... we've discussed bits and pieces, but I think that we need to start focusing on just what needs to be included ... so this issue is a starting point.
This list of items is somewhat independent of whether or not we got with plan A or plan B, but the underlying implementations will be dependent upon which plan we follow.

Session Console.
We need a way for users to manage there RSR connections (plan A) and GCI connetions (plan B). Having a GUI ala, the Gt4Gemstone session handler:

The session console should have me items so that user can:

Create and log into a gem, using one or more of the following approaches:

[ ] GCI/RSR
[ ] manual topaz
[ ] netldi
[ ] ???
In my opinion, I think this question needs to be determined by at least the end of the month, then we need to have a proof of concept (that can be just a set of doits) by the end of January -- this is just my opinion. As a secondary part of this we need to define the security model that we will be using ...

Emergency stop menu item and/or keyboard binding, basically the moral equivalent of hard break/soft break. I will be looking at the feasibility of doing a soft break for #15, but we will need to be able to unfreeze (hard break) or kill a session that is hung.
Open workspace menu item. Launch a workspace associated with the selected session.
Breakpoint browser. Without a separate code browser the developers will need a way to set breakpoints in the gem associated with the session, using one or more of the following possibilities:

[ ] text entry filed for method and step point number, where the step point number is determined by using topaz to list step points
[ ] method browser where the developer specifies the method (entry filed) and then can interactively define the step point (ala Jadeite)
[ ] ???
I expect to have a breakpoint API (based on Jadeite/Rowan services) as part of of my #15 work - haha and it was thinking bout the breakpoint api, that caused be to ask these questions :).

Process browser. This is more of a convenience than a requirement, but it is likely that I will create an listing and monkeying with processes as part of my #15 work, so it may only need GUI work to add this capability to the Sparkle dev environment ...

The main purpose of this issue is to start the conversation on what will and will not be in the dev environment delivered to our customer, so we should probably give them an opportunity to chime in with their take on priorities as part of the upcoming discussion with them

I believe all of the issues raised here have been solved or are covered by other open issues, so closing this one. Please file new issues for anything I missed.


Added handling for local to RSS route

When running locally RSS route will check the local folder for the file

Looks good


panic in second .Create() after setting a key with db.set()

GORM Playground Link

https://github.com/go-gorm/playground/pull/117
Description
When you do these things in following order:

Set key via db.Set()
Create a toy
Try to create a company

It panics while trying to do number 3. One workaround seems to be, to set the session attribute "WithConditions" to true in step 2. I am unsure though why this is the case.

https://gorm.io/docs/v2_release_note.html#Method-Chain-Safety-Goroutine-Safety


[HUDI-2053]  Insert Static Partition With DateType Return Incorrect P…

…artition Value
What is the purpose of the pull request
Fix the bug that insert static partition with DateType return incorrect partition value.
Brief change log

Add cast for the static partition value in InsertIntoHoodieTableCommand.

Verify this pull request
(Please pick either of the following options)
This pull request is a trivial rework / code cleanup without any test coverage.
(or)
This pull request is already covered by existing tests, such as (please describe tests).
(or)
This change added tests and can be verified as follows:
(example:)

Added integration tests for end-to-end.
Added HoodieClientWriteTest to verify the change.
Manually verified the change by running a job locally.

Committer checklist

[ ] Has a corresponding JIRA in PR title & commit

[ ] Commit message is descriptive of the change

[ ] CI is green

[ ] Necessary doc changes done or have another open PR

[ ] For large changes, please consider breaking it into sub-tasks under an umbrella JIRA.

Codecov Report

Merging #3133 (11f4d93) into master (5db37c2) will decrease coverage by 25.95%.
The diff coverage is n/a.

@@              Coverage Diff              @@
##             master    #3133       +/-   ##
=============================================
- Coverage     42.48%   16.53%   -25.96%
+ Complexity     4933      468     -4465
=============================================
  Files           914      274      -640
  Lines         39600    10650    -28950
  Branches       4269     1088     -3181
=============================================
- Hits          16825     1761    -15064
+ Misses        21041     8731    -12310
+ Partials       1734      158     -1576

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chore(tests): add more symbols to symbols.ts

Ref #51, #57
This PR adds more symbols to symbols.ts. Some symbols added do not have all of the data, will need to fix by changing interfaces in a later PR.
Changes

Add 6 new symbols to symbols.ts, this allows for testing against more symbols and prevents #42, #46, #57, etc.

Comments

The CI will fail. This will be fixed in a later PR.
The 10AM files are generated at 11AM, will need to fix that.

Thanks, @PythonCreator27, this is great!

:tada: This PR is included in version 1.7.2 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Testing of "helm lint" details.

Description:
Per @arkodg  comment
we needed the way to validate the helm chart is capable with AWS helm lint
After back and forth with AWS it's confirmed that the specific version `3.8.1' of Helm is required, ataching the screenshot here:

Relevant Links:
the desired version - https://github.com/helm/helm/releases/tag/v3.8.1
Reference of the existing Helm tags - https://github.com/helm/helm/tags

thanks for raising this @PetrMc, would be good to add helm lint into our existing lint target

/assign me


Omnisharp is not starting - [ERROR] Error: spawn vscode-csharp-omniSharp/extension/.omnisharp/1.37.0/run cmd ENONET

I am facing the following issue in linux x86*64 environment
Starting OmniSharp server at 9/2/2023, 1:20:26 AM
Target: vscode-csharp-omniSharp/extension/test/integrationTests/testAssets/slnFilterWithCsproj/SolutionFile.sln
[ERROR] Error: spawn vscode-csharp-omniSharp/extension/.omnisharp/1.37.0/run cmd ENONET

Sometimes, I do see this issue instead of the above one as well
Target: Starting OmniSharp server at 9/2/2023, 9:02:28 PM
    Target: /home/ccrushev/___dasd/c-sharp-code-examples/CSharp Code Samples/CSharp Code Samples.sln

[ERROR] TypeError: Cannot read properties of null (reading 'process')

Does someone help me on this?

@davidwengier ^ Any thoughts on this?

A lot has changed with O# and mono since this issue was opened. If you are still having problems, please open a new issue at https://github.com/omnisharp/omnisharp-roslyn/issues


Use DefaultImpl for calls of com.intellij.ui.dsl.builder.{Cell, Panel} methods that gained @JvmDefaultWithCompatibility in recent 2022.3 EAP

This should be merged to #1305, and then #1305 should pass

beautiful things here

b e a u t i f u l

should we wait with this one and do the release first? a lot of things in v3.2.0 already

yeah, 3.2.1 FTW


daily e2e tests- Log to File protected branch issue

See https://github.com/adobe/aio-e2e-tests/actions/runs/7734235829/job/21087863018
This might be a fix:
https://github.com/adobe/.github/issues/3#issuecomment-827931497

Re-opened. the PR didn't work: https://github.com/adobe/aio-e2e-tests/actions/runs/7749461909/job/21134052065

Removed "Require status checks to pass before merging". Waiting for next scheduled run.


Workflow to use Tailwind in Vue components?

Ah yes, the dreaded first issue! Fortunately more of a question/discussion point than anything.
Is there a best way to use Tailwind with Vue single file components? It would be really nice to keep those one-off styles or component styles inside Vue components themselves, but the tricky part is getting component CSS between the preflight and utilities lines.
The only thing I can think of is to have 2 files — The first file would just contain @tailwind preflight;, and the second would have @tailwind utilities; + any custom utilities users want. In Laravel Mix, if we use the extractVueStyles option, that should extract the Vue component styles at the top of the second file, which is what we want. We could then use Mix's combine() function to join 'em together.
Last I suppose we'd have to add Tailwind to vue-loader's PostCSS options.
Nevermind, all PostCSS plugins in Mix apply to Vue component styles as well, no need to do it manually. 👍
I haven't had a chance to actually test this approach but I figured I'd gather some thoughts in case there's a better way.
Edit Again: Ok! I tested the above approach and it seems to work great. My Vue styles get injected in the right spot, and I'm also able to successfully use Tailwind functions (config, @apply, etc) inside my Vue components. 🎉

Amazing! Thanks for testing this Collin. Very cool that it just works, but I guess that sort of makes sense. Are we good to close this issue then?

Yep! Closing.

Hi @syropian,
Can you show me your mix setup? I'm struggling with setting it up the way you suggested. My extracted Vue styles are just being inserted in between the output of preflight and utilities, but they're not being processed by PostCSS.

@syropian and @reinink, I'm hitting the same wall as @unxsist... Keep getting unable to find .bg-blue when trying to @apply in me Vue component... What's the mix config that could get me home here?

@unxsist @lperiodbose Unfortunately you have to include @tailwind utilities; in your style block. The very unfortunate side effect being this duplicates all of Tailwind into the output and your CSS file will row exponentially. More on this issue can be found here: https://github.com/tailwindcss/tailwindcss/issues/150

So I can think of a few ways that we could make it possible to @apply classes that aren't defined in the same scope:

Add some sort of @silent { ... } at-rule for generating the utilities so they are available when @apply runs but stripped by the time Tailwind is totally finished:
<style>
@silent {
    @tailwind utilities;
}

.whatever {
    @apply bg-red;
}
</style>

Make Tailwind always fallback to looking for a matching utility in the utilities it would generate, even if they haven't been generated into the current scope. So @apply .bg-red would work as long as Tailwind would generate that utility if you did add @tailwind utilities to that file.
The only thing I dislike about this approach is it doesn't let you use @apply for custom utilities that aren't generated by Tailwind like you can normally.

I'm somewhat hesitant to solve this problem because I really don't want to encourage people to start using Tailwind solely as a library for building component classes, but if it's really a big problem for people then maybe we can try something.

Is there a solution for this that Vue users not using Mix could implement? It looks like @silent is not implemented. I'm just setting up tailwind in a large Vue project, and I honestly don't know yet how I'll need/want to compose with @apply, but it's advertised in the documentation by virtue of the Extracting Components section. Usage in a single file component environment shouldn't preclude me from being able to compose things in that environment, right? Especially if I'm going to use tailwind as the primary source of truth for a color palette. Possibly confusing my setup is the fact that SCSS is already implemented, so style blocks in vue are using that lang attribute.

@alexsasharegan FYI you can use the config helper like this:
<style lang="postcss" scoped>
  html {
    background-color: config('colors.white');
  }
</style>

without including @tailwind utilities; in the Vue component. However, I have not been able to make @apply work  without including @tailwind utilities;.

Thanks @r0skar, I updated my comment when I figured out that the broken @apply was also breakingconfig(). That's working now that I've removed all my attempts at @apply.

@syropian
I'm not sure I follow your solution. I'm using Laravel Mix and Vue single file components.
I split my main SASS file into two: preflight with just @tailwind preflight in it and utilities with @tailwind utilities and an import for custom classes covering what Tailwind can't do.
In my webpack.mix.js file it looks like this:
mix.js('resources/assets/js/app.js', 'public/js')
  .sass('resources/assets/sass/preflight.sass', 'public/css/app.css')
  .sass('resources/assets/sass/utilities.sass', 'public/css/app.css')
  .options({
    processCssUrls: false,
    postCss: [tailwindcss('./tailwind.js')],
    extractVueStyles: true
  });

This isn't working. extractVueStyles and Mix's .combine() method are undocumented so I'm not sure how to get them to work.

Since Tailwind 0.6.2 you can use shadowLookup to apply classes that aren't defined but would exist if @tailwind utilities was included in the same CSS file. See the release notes.
However, this feature is disabled by default behind flags. It is also stated that this features may be changed or removed at any time without any regard for semantic versioning.
If you still wish to enable it, add this to your tailwind config file:
module.exports = {
  // ...
  experiments: {
    shadowLookup: true
  }
}

You can then use your stylesheet like you normally would:
// ./src/App.vue generated by Vue-CLI 3
// ...
<style lang="scss">
#app {
  background-color: config('colors.yellow'); // eww
  * {
    color: config('colors.white');
  }
  @apply bg-black; // ahh better!
}
</style>

@Wurielle Am I doing something wrong? What happens is styles @apply w-full; gets compiled as css (as a string).
webpack.mix.js
mix.js('resources/js/app.js', 'public/js')
    .sass('resources/sass/app.scss', 'public/css')
    .options({
        processCssUrls: false,
        postCss: [tailwindcss('./tailwind.js')],
        hmrOptions: {
            host: '<IP_ADDRESS>',
            port: 8080,
        },
    });

mix.webpackConfig({
    module: {
        rules: [
            {
                enforce: 'pre',
                test: /\.(js|vue)$/,
                loader: 'eslint-loader',
                exclude: /node_modules/,
            },
        ],
    },
});

tailwind.js
module.exports = {
    // ...
    options: {
        prefix: '',
        important: false,
        separator: ':',
        shadowLookup: true, // Should be official feature now
    },
    experiments: {
        shadowLookup: true, // Added just in case
    },
};

component.vue
<style lang="scss" scoped>
.cart-bg {
  @apply bg-black; // Just compiles into a string in css
}

.progress-bar {
  &::-webkit-progress-bar {
    @apply w-full; // Just compiles into a string in css
  }
}
</style>


Add the new BitDataGrid component

A new component named BitDataGrid should be added based on the QuickGrid of the AspLabs here:
https://github.com/aspnet/AspLabs/tree/main/src/QuickGrid

+1


Change of listening address to <IP_ADDRESS>

What if we use <IP_ADDRESS> as the listening IP address of JupyterLab and VSCode? Those two processes run correctly on the container, but the IP address is configured as the loopback address, <IP_ADDRESS>, and it's not receiving the requests. If it's not designed so in the first place, I can make a PR for you. Thanks.

Hi @JakeJungJoonYoon,
A PR is very welcome 🙏 - I think it will be easier to discuss once we have a fix suggestion 🙂

I made a PR #13 which can be accessed by below link, which is changing lookback address (<IP_ADDRESS>) to anywhere address (<IP_ADDRESS>).
https://github.com/allegroai/clearml-session/pull/13
I've read your documentation carefully, and found out that you meant to use ssh tunneling. However, in our on premise K8S server, there is no service attached to the agent pod, so ssh tunneling is keep failing like below.
SSH tunneling failed, retrying in 3 seconds
Starting SSH tunnel

SSH tunneling failed, retrying in 3 seconds
Starting SSH tunnel

SSH tunneling failed, retrying in 3 seconds
Starting SSH tunnel

SSH tunneling failed, retrying in 3 seconds
Starting SSH tunnel

So, I suggest this for those who have same problem with me.

Clone github clearml-session repository.
Change those <IP_ADDRESS> address to <IP_ADDRESS>, like I did in PR.
Attach service for the agent.
You can use NodePort or even, attach Ingress to service.

The K8S service yaml file is following.
kind: Service
apiVersion: v1
metadata:
  name: clearml-agent-ports
spec:
  ports:
  - name: clearml-agent-vscode
    port: 9000
    targetPort: 9000
    nodePort: 31100
  - name: clearml-agent-jupyterlab
    port: 8888
    targetPort: 8888
    nodePort: 31120
  - name: clearml-agent-ssh
    port: 10022
    targetPort: 10022
    nodePort: 31140
  type: NodePort
  selector:
    app.kubernetes.io/instance: clearml-agent

Thanks.


Add upper_bound_column to order by

resolves #659
This is a:

[ ] documentation update
[x] bug fix with no breaking changes
[ ] new functionality
[ ] a breaking change

All pull requests from community contributors should target the main branch (default).
Description & motivation

The order by clause(s) used in the window functions in the mutually_exclusive_ranges test give non-deterministic results when more than one range within a partition has the same lower_bound. If zero-length ranges are not allowed, the test will FAIL (as it should) if this occurs. But if zero length ranges are allowed and gaps are not required, it should be expected that one could have more than one range within a partition with the same lower_bound.
This PR changes the order by clause(s) to use {{ lower_bound_column }}, {{ upper_bound_column }} as the ordering criteria. This will ensure that when multiple ranges have the same lower_bound, they are sorted based on their upper_bound, which will place all zero-length ranges together, with any non-zero-length range with the same lower_bound appearing as the last record in this group, causing it's upper_bound to be compared to the next distinct lower_bound.
Since the test only considers the lower and upper bound columns, the fact that records with the same lower and upper bounds won't have a guaranteed order shouldn't be problematic, since these are effectively interchangeable as far as the test is concerned. So this should be enough to guarantee deterministic results (i.e., the test will always PASS or will always FAIL, unless changes are made to the dataset or to the test configuration).
Checklist

[ ] This code is associated with an Issue which has been triaged and accepted for development.
[ ] I have verified that these changes work locally on the following warehouses (Note: it's okay if you do not have access to all warehouses, this helps us understand what has been covered)

[ ] BigQuery
[ ] Postgres
[ ] Redshift
[x] Snowflake

[x] I followed guidelines to ensure that my changes will work on "non-core" adapters by:

[x] dispatching any new macro(s) so non-core adapters can also use them (e.g. the star() source)
[x] using the limit_zero() macro in place of the literal string: limit 0
[x] using dbt.type_* macros instead of explicit datatypes (e.g. dbt.type_timestamp() instead of TIMESTAMP

[x] I have updated the README.md (if applicable)
[x] I have added tests & descriptions to my models (and macros if applicable)
[x] I have added an entry to CHANGELOG.md

@sfc-gh-ancoleman I like this! Would you be able to add a test case just like your one from the initial issue which fails under the current setup (subject to the vagaries of non-deterministic sort algorithms at least) and passes under the new system?
There are sample tests in the integration_tests project in this repo - let me know if you need a hand digging into them

@joellabes Since I believe that I just identified an edge-case that the existing test data doesn't include, I modified the existing data_test_mutually_exclusive_ranges_with_gaps_zero_length.csv seed so that it includes a zero-length record for 2020-05-08 as well as a positive-length record that also begins on 2020-05-08. I placed the positive-length record above the zero-length record in a (possibly misguided) attempt to influence ordering.
I had initially also extended the final record for supscription_id 3 so that it overlaps with some records for subscription_id 4, so that if at some point in the future the macro is changed in a way that breaks the functioning of the partition_by argument, the test on the dataset I modified should fail. I have undone this change, since it's not really related to this issue, and there is probably a better place to incorporate such a test.

Works for me! Thanks @sfc-gh-ancoleman 🌟


Use build v0.9.0 with pyproject.toml instead of legacy setup.py

Modifying the setup.py to let pyproject.toml naturally cythonize the extension. Using pyproject.toml from here on.

See Issue #97 for details.


EventSeeker no longer works with SimTelArray files

source = event_source("events.simtel.gz")
seeker = EventSeeker(source)

throws an exception:
OSError: Reader is not compatible as input to the event_source is a stream
   (seeking not possible)

But I thought the whole point of the EventSeeker class was to provide a way to seek forward (or backward) in a file to a particular event, by event count or event_id?  Even if the file is not backward-seekable (a stream for example), forward seeking should still work, and backward seeking can be implemented by re-opening the stream (or throwing an exception as now).
In other words I think that forward-seeking should work fine for a SimTelArray file, but backward seeking should either fail or work in a non-optimal way. Is there a reason this changed?  It's quite useful for event-wise debugging, so having this functionality back is important.
A use case:

user identifies a reconstruction problem in the DL1 or DL2 data, and identifies a set of event_ids that exhibit the problem
to debug, the user wants to open a raw data file, seek to each of the identified events, and plot the raw camera data.

Of course one could write a loop manually to do this each time, but EventSeeker was supposed to be a common way.

It seems a change was made to SimtelEventSource in which passing back_seekable=True is required to go to earlier events in the file

But yes, some changes could be made to EventSeeker to allow streams + seeking forward

Is the user allowed  to set back_seekable?  I assumed that is not under the user's control, and should be set correctly by the EventSource depending on the file type (e.g. if it's a stream vs a tabular file)?

@kosack in case of the SimtelEventSource together with gzip files, the user can request to use the python gzip module instead of zcat which is a bit slower but allows back seeking


Cron Min Reschedule is 60s

adding 60 sec min time for schedules
https://jira.mesosphere.com/browse/MARATHON_EE-1717
JIRA: MARATHON_EE-1717

@alenkacz I'm not clear on your comment.   I believe it says 60 secs in all places.   perhaps I made a mistake and it was edited away.  sorry about that if that was the case.


Add kibana 3.1.2

As discussed here, please add the kibana 3.1.2 image.

As per https://www.elastic.co/support/eol, EOL for 3.1.x was 2015-11-15, so I'm going to close this, but it'll stick around as a reference for folks who need it to take the Dockerfile and have their own image. :+1:


[5.4] Included ability to pass extra variables to Blade @each

Fixed of #18955.
As it is not possible to pass extra variables to the @each, it's hard to avoid the @foreach sometimes.
with the inclusion of the $mergeData, it is simple to add new variables:
Passing the empty view:
@each ('blog.post', $posts, 'post', 'blog.empty', ['data' => 'This is a sample data'])
Or withouth the empty view:
@each ('blog.post', $posts, 'post', ['data' => 'This is a sample data'])
Note: It is still possible to pass a empty value as the empty view:
@each ('blog.post', $posts, 'post', false, ['data' => 'This is a sample data'])
This way it is not mandatory to pass a false empty view, but if the developer wants to, it will not break the code.

I really don't want to add this at this time.

Ok.


Fix broken emoji in web site

Motivation:
Emoji link is broken in https://armeria.dev/.

The emoji URL generated by Emoji is https://twemoji.maxcdn.com/2/svg//2728.svg,
but expected link is https://twemoji.maxcdn.com/2/svg/2728.svg.
Basically, this is a bug of library react-easy-emoji.
The library should remove / from baseUrl when option.size is empty string.
https://github.com/appfigures/react-easy-emoji/blob/v1.8.1/lib/makeTwemojiRenderer.js#L35
As a workaround, we can specify baseUrl as URL without ending with / and size as empty string.
Modifications:

Modify baseUrl parameter in site/src/components/emoji.tsx not to end with /.

Result:

Upstream issue:

https://github.com/appfigures/react-easy-emoji/issues/25

[FYI]
It seems the library bug is being fixed.
https://github.com/appfigures/react-easy-emoji/pull/26


FEATURE: Retrieve .idx files from cloud object storage, given a path and search pattern

Related

#1

This isn't relevant given the new design outlined in https://github.com/JackKelly/hypergrib/blob/91e688dbf456154792ecfaf1844ae92eaff28235/design.md


PSPs and SCCs not being deleted for workshop environment.

Describe the bug
The pod security polices (obsolete Kubernetes versions) and security context constraints (OpenShift) resources created for a workshop environment are not being set as being owned by the workshop namespace. This means these resources are not being deleted automatically when the workshop environment and workshop namespace were deleted.
Additional information
No response

I think we should probably remove support for PSPs, since they have been deprecated for long time and those cluster versions are no longer supported.


[EASY] Small patches to language tools

Material changes:

Remove seed-isort-config :/ . It adds new imports on the same line, which is a nightmare for merges/rebases
Reactive flake8 F401 (unused imports)
Add some known imports

Test plan
Travis? idk

The missing known_third_party imports were never added outside of git commit. isort is still checked in tox -e check and git commit. Order fixes happen in tox -e fix. Missing known_third_party imports aren't added anywhere now.


Request for Documentation: Docker bridge network can interfere with the Mattermost VPN and DNS resolution for  internal.mattermost.com (<IP_ADDRESS>/16)

Mattermost user jason.deland from https://community.mattermost.com has requested the following be documented:
Just an FYI - you can also use docker cli
jpd@pop-os:~/go/src/github.com/mattermost/mattermost-server$ docker network rm mattermost-server_mm-test
mattermost-server_mm-test

See the original post here.
This issue was generated from Mattermost using the Doc Up plugin.

The original post referenced cannot be found

@rohitjain13 First off - thank you for taking an interest in this issue and helping us get it resolved 😊!
It was a private conversation between myself and Daniel S. Basically, the docker-compose network that is created when you use our makefile defaults to <IP_ADDRESS>/16
Just an FYI - you can also use docker cli
jpd@pop-os:~/go/src/github.com/mattermost/mattermost-server$ docker network rm mattermost-server_mm-test
mattermost-server_mm-test
We can also setup the docker bridge to use a different ip
Here are details on how to change the default:
https://success.docker.com/article/how-do-i-configure-the-default-bridge-docker0-network-for-docker-engine-to-a-different-subnet

Should I enhance the documentation at https://docs.mattermost.com/install/prod-docker.html?highlight=compose to mention perhaps in step 3 that the network would default to <IP_ADDRESS>/16 and if you want to change the default, see the reference you mention above?
And I could suggest there that you could use the docker cli instead of docker-compose.  I assume that the cli method is not documented in the manual anywhere that I can just link to, and therefore we would need to provide the steps for the cli as an alternative to the steps documented in step 3 for docker-compose.  But it is not clear to me that just entering the command as you have written it above would do it.  It does have jpd@pop-os in it :-).  What would those steps look like with the docker cli as different from the steps for docker-compose?

Hey @RohitJain13 - sorry for the confusion, the command above was used to remove the docker-compose network after changing the default config so that on the next run it will be generated again with the new default cidr.

Okay, I understand now.  But could you spell out for me exactly what part of that is the command?  Is it just "docker network rm mattermost-server_mm-test"

Please review pull request: https://github.com/mattermost/docs/pull/3480
Documenting how to change the default docker-compose network #3480


Flux doesn't support array of component references passed as contructor arg

When specifying a component such as myComponent in the following config yaml:
- components
  - id: "referencedComponent"
    className: "com.test.Foo"
    ...
  - id: "myComponent"
    className: "com.test.MyClass"
    constructorArgs:
      - [ ref: "referencedComponent" ]
      - "bar"

The reference in the list passed as the first contructor arg isn't dereferenced. Then when an attempt is made to instantiate MyClass in org.apache.storm.flux.FluxBuilder.buildObject, the first parameter is passed as an ArrayList of LinkedHashMap and an exception is thrown.
I can look at fixing this and making a pull request. Should that be done over in the main Storm project now that Flux is an external?
Alternatively, would you consider Flux providing the option of using Spring as a way to load components? e.g.
components:
   - springDefinition: "/path/to/springDefinition.xml"

Hi @grantnd,
Yes, since this is incorporated into main Storm project, all modifications should take place there.
Also, could you provide the constructor signature of the class you are trying to use?

Sure thing, in the above example it would be:
public MyClass(List<Foo> foos, String someString) { ... }


Automated cherry pick of #5378: fix: Add 'scope=system' and 'system' for Caches when querying from Keystone.

Cherry pick of #5378 on release/3.0.
#5378: fix: Add 'scope=system' and 'system' for Caches when querying from Keystone.

Codecov Report

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The diff coverage is 0%.

@@              Coverage Diff              @@
##             release/3.0   #5384   +/-   ##
=============================================
  Coverage               ?   6.87%
=============================================
  Files                  ?     535
  Lines                  ?   91076
  Branches               ?       0
=============================================
  Hits                   ?    6260
  Misses                 ?   84294
  Partials               ?     522

Flag
Coverage Δ

#aFlag
6.87% <0%> (?)

Impacted Files
Coverage Δ

pkg/cloudcommon/db/tenantcache.go
1.31% <0%> (ø)

pkg/cloudcommon/db/usercache.go
4.25% <0%> (ø)

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/lgtm

/approve


Date or since time

Is there a way to config from which point should show date or since time.
In my case what i would like to set, Today i would like to have how much time has passed, but before today should Date be presented.

Hi @CrackerakiUA unfortunately that functionality does not exist yet. At the moment we don't have the time to add it but we do welcome PR's if you want to add it in.


Commit syntax has weird highlighting

I see weird violet highlight of first comment line when committing. It shows up when there is something written on first (empty) line and there is no line break between it and the comment.
See the image:

S3 b3161
git version 2.15.1 (Apple Git-101)
macOs 10.13
BTW. New S3 builds include syntax for commit messages and other git files. I wonder if it makes sense to use those instead.

I found use_syntax_for_commit_editmsg to switch to native syntax but it doesn't work exactly as expected. I'll file new bug for that.
Also, regardless of that setting, this bug should still be valid.

the highlight is related to git style guide https://github.com/divmain/GitSavvy/blob/b64a9fccc3e709e7d3b4ffe1c31e94422c8de3b4/GitSavvy.sublime-settings#L127

OK, but it's too overzealous in saying there is an problem.
When starting to type the subject there is no empty line added yet so it shouldn't indicate a problem at that point. It only should do that when there are at least two lines of text added at the start of the document, without line break in between.
That would also fix the case when there is only commit summary without any message in the body - I think that is equally valid and shouldn't indicate any problem.

When I wrote it I did think there will comment on the 2. line.

I've looked at the pull request and I'm not sure it addresses the problem the way I would humbly expect.
The comments themselves are from git and and are not included in the final commit message. So IMO they should be treated more like not being there at all instead of ignoring first comment line specifically. Basically handle the commit view as if the comment would not be there at all. Then we would have rules like:
a) if there is only one line of message (summary) - OK
b) if there is summary + empty line - WRONG - highlight second line
c) if there is one line of summary + empty line + line with commit message - OK

Seems to work OK.
Small, a bit contrived problem found - after removing all the commented out lines, highlighting no longer triggers when there are two lines with text without empty line in between.

Ok. That will be fixed in the next release :)
Thanks  for testing and reporting


[corechecks/kubelet] Enable kubelet core check by default

What does this PR do?

Sets the kubelet core check to be enabled by default
Motivation

We have tested the kubelet core check internally and have not noticed any issues yet. For 7.54.0 we would like to enable the core check by default (users will still be able to change this behavior if they would like).
Additional Notes

Once 7.53.0 is released, we will be enabling this by default in the helm chart, and monitor if there are any issues raised after that point.
Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

Deploy the agent
Check the output of agent config--kubelet_core_check should be set to true

$ agent config | grep kubelet_core_check_enabled

❯ kubelet_core_check_enabled: true

/merge


Thinning with different dataset input sizes leads to different accuracy

When doing filter removal (resnet18), different dataset input sizes give different P/Rs. I tried with dataset: 'imagenet' and my own dataset with input size (1,3,288,512) respectively, the thinned model with my dataset input gets higher P/R. It seems the dummy input does more than finding the data-dependencies #416. Could you explain more about it? Thanks.

Hi @yama514,
Can you explain what you mean by P/R?
Thanks
Neta

Sorry for the confusion. I am testing a resnet18 based detection network, P/R is the precision and recall.

Hi @yama514 ,
I might be missing more information, because it seems obvious to me that different datasets will produce different P/Rs, regardless of any sparsity and thinning.  The two datasets have different  number of objects, classes and examples distributions.  You know the datasets you've used:

when you don't perform any pruning (sparsification) and thinning - how do your two datasets perform?
If you only perform pruning (sparsification only - so you have channels with zeros, but you didn't delete physically them using thinning) - how do your two datasets perform?

Cheers,
Neta

Hey Neta, thanks for the reply. I did the training (pruning) and testing all on my own same dataset. Only in the thinning process when setting net_thinner in yaml, I set dataset field to be "imagenet" for one experiment, and manually set the input size to be my dataset image shape (1,3,288,512) in code for the second experiment. I thought the size of the dummy input is only used for checking data flow. However, the two thinning experiments show different precisions and recalls on the same testset. Hope this helps describe my question. Thanks!

That's interesting.  You can see in the code (search for dataset) that the dataset is used only for creating a SummaryGraph (code).
A SummaryGraph is documented in the code, and in this issue.
In short, the dummy_input is fed into a PyTorch model for tracing.  The Pytorch trace is a representation of the forward-graph generated by our dummy_input.   We then convert this graph into a distiller.SummaryGraph representation.  The thinning process uses this distiller.SummaryGraph representation to determine dependencies.
Your input - (1,3,288,512)- and ImageNet - (1,3,224,224)- have the same number of input channels (3) so the feature-extraction part of ResNet18 should not be affected (i.e. the Convolution layers don't require reconfiguration).  The average-pooling ( nn.AdaptiveAvgPool2d((1, 1))) also help maintain independence from input size.
Because the number of channels in all the layers are independent of the input size (see above), the thinning should behave the same.   You can create different summaries of the two models and compare their structural characteristics.  Maybe you'll see a difference that explains the different results, but I don't think.  And this leads me to suspect that the difference is in how you perform the pre-processing of each of these datasets.
Cheers,
Neta

Thank you for the detailed explanation, Neta. Since the thinning is independent of the input size in this case, I will check the data, retrain the models, and compare the summaries.


Have a "_no_ripple_effect" variable in MDApp that controls all widgets

Description of the Feature
Like when you do MDApp.theme_cls.primary_palette to change color of all widgets, I purpose having MDApp._no_ripple_effect that affects all widgets, instead of having to set this property to all of them individually, that could cause mismatches if you forget to deactivate some widgets.
Versions

OS: Windows 11
Python: 3.11.2
Kivy: 2.2.0.dev0
KivyMD: 1.1.1

You cannot disable the ripple effect for all widgets. Only for the selected widget.


DFK23U445, Hardware trigger supported also for Linux (Ubuntu 16.04)?

Hello Stefan,
I am thinking to buy DFK23U445 to create my own stereo cam. I bought before DFK23UM021 for the same purpose, but realized the hardware level synchronization was necessary. So, can you let me know if hardware trigger is supported for DFK23U445 also for linux??
Thank you,
Koichi

Hello Koichi
yes, hardware trigger is supported. You may need to install the UVC Extension for letting v4l2 know about the trigger properties.  https://github.com/TheImagingSource/tiscamera/wiki/UVC-Extension-Units


use io stream when proxying

as an end user of trickster, I would like for requests that are proxied to origin to use an iostream to serve the content to the downstream client in real time, rather than waiting for the entire object to download into trickster's memory before beginning to service it to the end user. one consideration for this is, if the object is cacheable, to be sure to tee the stream so it can be written to the cache as quickly as possible, while maintaining a buffer for the end user's service which will likely receive the payload more slowly than trickster's internal local write.

@LimitlessEarth be sure to consider that other clients may request the same object as the original requester nearly simultaneously, either before the first byte is returned from the origin, or while the bytes are still in flight from the origin (e.g., many dashboards refreshing at roughly the same time). These late joiners should be able to be served any already-downloaded bytes, and then pick up on receiving any additional that were still in flight when they started receiving data.


Cperon/payload gen

It looks like we need to change the cookie fixture tests, we are getting redirected (302) back from the ieee.org servers instead of the 200 specified in the test.

@csanders-git thoughts??


FAW support: run on very small screen

Full Android Watches span from Mediatek / MTK based Android 7.1.1 models to Android 8.1, Android 9, 10 and Android 11 (Z40) are the newest. DM100 and DM101 style rectangular giant wrist watches can have 2.65"-2.88" screens, but most circular big watches have ~1.6" IPS screens, usually around 400x400px resolution. Brand manufacturers such as LEMFO, Kospet, Lokmat have web sites and may offer warranties, while noname copycats go starting from $50 (for 1GB RAM 16GB ROM). Other common RAM / ROM configurations are 3GB RAM 32GB ROM, or 4GB RAM 64 GB ROM.
Got a used LEMFO LEM P 4GB / 64GB on eBay, that runs Android 9.1. We'd need to test how the app looks and functions on such a tiny screen and make adjustments accordingly.

FAW features will helps if ever we'll have a WearOS release


Automatic installation when creating a Knative Camel Source

The ideal scenario for Knative users (imo) should be:

A cluster admin enables Camel-based sources and related resources on a cluster
A user selects a Camel-based source from a catalog (e.g. operatorhub catalog)
A user creates an instance of the Camel-based source into her namespace of preference
The Camel-based source is started

Currently this does not work this way, because the user needs to install the Camel K operator in each namespace where he plans to use sources.
Can we improve this?
How good is the option of creating a master-controller in a camel-k namespace that instantiate the operator and related resources when a Camel-based source is added to a namespace?
@astefanutti , @lburgazzoli

Is it something managed by the operator lifecycle manager?

I think we should explore also the option to have an operator that handles multiples namespaces

Yes, our operator works oob if you specify "" as target namespace. The issue is that the operator is doing heavy work that cannot be shared, e.g. builds.
We can:

separate builds into their own controller, or
create a super controller that installs the current operator

Which one is best?

The described scenario is exactly what OLM with Operator Hub as config source configured is supposed to provide.
Besides, operator groups now provide tenancy support for operators installed via OLM:
https://github.com/operator-framework/operator-lifecycle-manager/blob/master/Documentation/design/operatorgroups.md#installmodes-and-supported-operatorgroups
An operator can have any combination of installation modes, so the Camel K operator could support both OwnNamespace and AllNamespaces.
Then from the developer catalog UI, user would browse the Camel-based sources and have the ability the instantiate any of them from the UI.
This relates to #523. I'm not 100% sure yet what that means in term of code change and operator execution model. Someone (no name ;)) told me that the AllNamespaces mode just instantiate the operator in each namespace. To be investigated.

I think we should support both, but I personally won't go to the path of having an additional controller written by us that does the installation & set-up so IMHO:

if one wants the operator to be installed in each namespace then OLM is the way to go
we should support handling mutiple namesapce
we should support separate builder

Sounds good to me.

This has been implemented. Additionally, platforms are auto-created on OpenShift by the platform trait.


fix #167348: add aria-live

Closes #167348. This also improves suggested code auto-announcement for screen readers.

@microsoft-github-policy-service agree

@microsoft-github-policy-service agree

Closing this as it looks like the branch has been deleted, but i'll test it out with the changes you made


[CI][Release] macOS job is failed because of mascos-latest change

Describe the bug, including details regarding any error messages, version, and platform.
macos-latest is macos-14 not macos-12.
See also: https://docs.github.com/en/actions/using-github-hosted-runners/about-github-hosted-runners/about-github-hosted-runners#standard-github-hosted-runners-for-public-repositories
Example:
https://github.com/apache/arrow/actions/runs/8819910983/job/24212269544?pr=41359#step:4:18
Error: The current runner (macos--arm64) was detected as self-hosted because the platform does not match a GitHub-hosted runner image (or that image is deprecated and no longer supported).
In such a case, you should install Ruby in the $RUNNER_TOOL_CACHE yourself, for example using https://github.com/rbenv/ruby-build
You can take inspiration from this workflow for more details: https://github.com/ruby/ruby-builder/blob/master/.github/workflows/build.yml
$ ruby-build 2.7.8 /Users/runner/hostedtoolcache/Ruby/2.7.8/arm64
Once that completes successfully, mark it as complete with:
$ touch /Users/runner/hostedtoolcache/Ruby/2.7.8/arm64.complete
It is your responsibility to ensure installing Ruby like that is not done in parallel.

Component(s)
Continuous Integration, Release

Issue resolved by pull request 41379
https://github.com/apache/arrow/pull/41379


Asset-Sync only ever retrieves a single tag at a time

EFFICIENCY

/azp run tools - test-proxy - tests

/azp run tools - test-proxy - tests


feature(agent,pkg): remove timed authentication

Authentication request is critical for the device presence on ShellHub, what makes its remotion difficult to do.
One of the main limitations is the addition of devices to a namespace. When it is initialized, it authenticates on the namespace, and starts to listen for connections. If the device, after being accepted, is removed, the Agent won't notice it until it loses the connection to the server, showing it as offline in the system.
To remove timed authentication, we should also be able to identify this deletion on the tunnel, or refactor core components for device to server communication. JWT invalidation is also a problem, as the connection could also remain open while the tunnel is established.