Error when try it run in parallel

Hi! Cool project!
I deployed project services and making attempts to configure my CI jobs but API returns error  like as:
StatusCodeError: 400 - "Must provide query string."

My command:
$(npm bin)/cypress run --record --parallel --ci-build-id "123" --key x

Cypress version: 3.6.0
API service: logs does not have an any errors
Director: logs does not have an any errors

What am I doing wrong?

Cypress 3.4.1 was also tested and it crashes with same error.

@roquie The problem is that you need to pass the --key after the --record, you have to use this command: $(npm bin)/cypress run --record --key x --parallel --ci-build-id "123".
It works for me on Cypress 3.6.0

Also remember to change the api_url from cypress root to use this API.

Replaced.

The problem is that you need to pass the --key after the --record

No :(

Following body request (POST) was be sent:
{
  "ci": {
    "params": null,
    "provider": null
  },
  "specs": [
    "cypress/integration/packages/0-enviroment/env.feature",
    "cypress/integration/packages/0-enviroment/exit.feature",
    "cypress/integration/packages/0-enviroment/lifecycle.feature",
    "cypress/integration/packages/1-authorized/auth.feature",
    "cypress/integration/packages/1-authorized/db.feature",
    "cypress/integration/packages/1-authorized/favorite.feature",
    "cypress/integration/packages/1-authorized/profile.feature",
    "cypress/integration/packages/1-authorized/sign-up.feature",
    "cypress/integration/packages/1-cases/home-filter.feature",
    "cypress/integration/packages/1-cases/shop-filter.feature"
  ],
  "commit": {
    "sha": "87eed9b791fcdeea8ae561ca16357d650b646433",
    "branch": "develop",
    "authorName": "Maks",
    "authorEmail"<EMAIL_ADDRESS>    "message": "Update .dockerignore",
    "remoteOrigin": "git@gitlab.example.io:example/web.git",
    "defaultBranch": null
  },
  "group": null,
  "platform": {
    "osCpus": [
      {
        "model": "Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz",
        "speed": 3100,
        "times": {
          "user": 73301780,
          "nice": 0,
          "sys": 53641710,
          "idle": 266876510,
          "irq": 0
        }
      },
      {
        "model": "Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz",
        "speed": 3100,
        "times": {
          "user": 12199180,
          "nice": 0,
          "sys": 11563330,
          "idle": 370013350,
          "irq": 0
        }
      },
      {
        "model": "Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz",
        "speed": 3100,
        "times": {
          "user": 66353680,
          "nice": 0,
          "sys": 41032890,
          "idle": 286389930,
          "irq": 0
        }
      },
      {
        "model": "Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz",
        "speed": 3100,
        "times": {
          "user": 11602330,
          "nice": 0,
          "sys": 10325850,
          "idle": 371846420,
          "irq": 0
        }
      },
      {
        "model": "Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz",
        "speed": 3100,
        "times": {
          "user": 60976940,
          "nice": 0,
          "sys": 35320640,
          "idle": 297478800,
          "irq": 0
        }
      },
      {
        "model": "Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz",
        "speed": 3100,
        "times": {
          "user": 11715020,
          "nice": 0,
          "sys": 9698920,
          "idle": 372360530,
          "irq": 0
        }
      },
      {
        "model": "Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz",
        "speed": 3100,
        "times": {
          "user": 55413400,
          "nice": 0,
          "sys": 30368950,
          "idle": 307993900,
          "irq": 0
        }
      },
      {
        "model": "Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz",
        "speed": 3100,
        "times": {
          "user": 11996770,
          "nice": 0,
          "sys": 9311740,
          "idle": 372465840,
          "irq": 0
        }
      }
    ],
    "osName": "darwin",
    "osMemory": {
      "free": 556597248,
      "total":<PHONE_NUMBER>4
    },
    "osVersion": "18.7.0",
    "browserName": "Electron",
    "browserVersion": "73.0.3683.121"
  },
  "parallel": true,
  "ciBuildId": "123",
  "projectId": "rwei8y",
  "recordKey": "x",
  "specPattern": null
}

to
{{API_URL}}/runs

Facepalm! For resolve this issue I should be to use director instead of api in config file. Thanks :))


Refactor function handler

Codecov Report
Attention: Patch coverage is 54.16667% with 22 lines in your changes are missing coverage. Please review.

Project coverage is 76.41%. Comparing base (6125897) to head (7531e03).
Report is 1 commits behind head on main.

Additional details and impacted files
@@             Coverage Diff             @@
##             main    #4463       +/-   ##
===========================================
+ Coverage   34.61%   76.41%   +41.79%
===========================================
  Files         109      109
  Lines       53276    53299       +23
===========================================
+ Hits        18440    40726    +22286
+ Misses      34836    12573    -22263

Since the line of codes
            if not settings.enable_error_handler:
                if settings.release_on_exception:
                    from pyaedt.generic.desktop_sessions import _desktop_sessions

                    for v in list(_desktop_sessions.values())[:]:
                        v.release_desktop(v.launched_by_pyaedt, v.launched_by_pyaedt)
                raise e
            else:
                return False

are used in every exception handling, could we have an inner function in wrapper to refactor that and call it every time it is needed ?

Implemented


When the ios app is launched after receiving a silent push notification png images are pink;

Is there an existing issue for this?

[X] I have searched the existing issues
[X] I have read the guide to filing a bug

Steps to reproduce

Integrate the ios version of the app to receive push notifications (turn on background modes etc.);
Prepare and install a release build;
Send a push notification with content-available: 1.
Wait while the app receives the push notification;
Open the app;

P.S  I realized that the problem is connected with push notification handling because I also sent badge : 100, and I have a sync with my server which response with 0 for now, so the app set the badge to 0 after the push comes;
Links to other similar issues:

https://github.com/flutter/flutter/issues/114594
https://github.com/flutter/flutter/issues/64558
https://github.com/flutter/flutter/issues/71074

Expected results
The app is launched and all the images are displayed correctly;
Actual results
The app is launched, but some images are pink;
After relaunching the app everything is ok;
No Code sample yet
I hope someone will be able to understand what is the problem, but anyway, I will try to post the reproducible repo a little bit later;
Code sample
[Paste your code here]

Screenshots or Video

Screenshots / Video demonstration
[I had to blur some parts of the app, but anyway you can see there are normal images and pink images]
https://github.com/flutter/flutter/assets/6989126/4a9c73ff-0e04-4ab2-8563-a0d2a98bf9fc

No Logs
Logs
[Paste your logs here]

Flutter Doctor output
Doctor output
Doctor summary (to see all details, run flutter doctor -v):
[✓] Flutter (Channel stable, 3.10.1, on macOS 13.3.1 22E772610a darwin-x64, locale en-GB)
[✓] Android toolchain - develop for Android devices (Android SDK version 33.0.2)
[✓] Xcode - develop for iOS and macOS (Xcode 14.3)
[✓] Chrome - develop for the web
[✓] Android Studio (version 2022.2)
[✓] VS Code (version 1.77.3)
[✓] Connected device (4 available)
[✓] Network resources

• No issues found!

As far as I understand the app launches after it receives a silent push, and the first piece of images that are trying to be rendered are getting pink, all other images after navigation to other parts of the app look ok.

Thanks for the report @befirst
Can you provide us a complete minimal reproducible code sample or a repo that we can clone and run locally to verify the behavior ? Also please provide the payload you are sending.
Are you using firebase_messaging plugin to trigger push notifications ? And if so, is it only occuring while using this plugin ?
If yes and it is only occuring with the said plugin, you might need to report this in https://github.com/firebase/flutterfire/issues
If not and is specific to framework itself, then we would need required code sample that we can use to verify the reported behavior.

Hi,
same bug here!
As @befirst mentioned, it seems it is a regression, and there is difficult to reproduce, or give you a sample code to test, because the pink image are displayed after many hours that app remains in the background.
In my case the silent notification of firebase_messaging doesn't exists, and the image are loaded from the assets using Image.asset or ImageProvider for DecorationImage.

This seems to be a duplicate of https://github.com/flutter/flutter/issues/126878, so please follow-up in that issue for further updates. Closing as such.


KBC-2276 fix description not null

Jira: KBC-2276
Before asking for review make sure that:

[x] New client method(s) has tests
[x] Apiary file is updated
[x] You declared if there is a BC break or not (will affect next release of a client)

@fejjo Tak to nejde phpstan mě to nedovolí.


Transparency

I'd like for the document to recommend maximal transparency in operation. We need to write this down, motivating it, and describing how that might look.

We're not really using these issues to track stuff any more.


Add a test suite for Color

PS: I get (intended) error messages when running tests:
❯ bin/godot.linuxbsd.tools.64.llvm --test
[doctest] doctest version is "2.4.0"
[doctest] run with "--help" for options
ERROR: Invalid color code: invalid.
   at: html (core/color.cpp:329)
ERROR: Invalid color name: doesn't exist.
   at: named (core/color.cpp:409)
===============================================================================
[doctest] test cases:     44 |     44 passed |      0 failed |      0 skipped
[doctest] assertions:    198 |    198 passed |      0 failed |
[doctest] Status: SUCCESS!

I'm testing failure paths to increase test coverage. Is there a way to hide them when not using --verbose?

CC @RevoluPowered @Xrayez

Yeah kinda looks ugly to have those errors there. If Godot had exception handling enabled this could be bypassed with try/catch blocks. In fact I've had to write some tests for SCons, testing the expected error messages themselves that way (I know some platforms require exceptions handling to be disabled, this is just as an example).
I think some magic can be done in error_macros.h, or implement some interface to optionally disable error messages caused by those assertions in OS::print_error (every time you have to make those expected failures assertions).
Perhaps it may be worth to put those kind of assertions to the bottom of a test case at least, but that's just semantics.
Parameterized tests as described in doctest could also make those test cases more compact perhaps, but that's just food for thought.

@Calinou I've found a way to mute error prints entirely for those expected errors coming from Godot itself. You can wrap either assert statements or method calls by switching _print_error_enabled boolean! This should be documented, for testing purposes that's really useful.

Alternatively, we could add OS::set_print_error_enabled() which could simply wrap this switching in a method and even expose this to scripting, some people may find this useful to test failure paths in various GDScript testing frameworks as well.

Will need rebase after #40883.

I added the ERR_PRINT_* macros. Thanks to @Xrayez for implementing them :slightly_smiling_face:

Thanks!


ODQA inference speed very very slow

Running the default configuration and model on a EC2 p2.xlarge instance (60~GB Ram and Nvidia K80 GPU) and inference for simple questions take 40 seconds to 5 minutes.
Sometimes, no result even after 10 minutes.

Hi, @shubhank008 !
The inference can speed up multiple times if you switch from CPU to GPU usage.
No result is expected behavior and means that the model didn't find an appropriate answer.
The inference process takes different time because Wiki articles have different size, so when they are chunked and passed to the reader, the number of chunks varies.

Hi, @shubhank008 !
The inference can speed up multiple times if you switch from CPU to GPU usage.
No result is expected behavior and means that the model didn't find an appropriate answer.
The inference process takes different time because Wiki articles have different size, so when they are chunked and passed to the reader, the number of chunks varies.

I believe I am already using GPU since p2.xlarge is AWS GPU instances with K80 GPU
Also, the no result thing was actually just a very very slow inference, it did return the result after like 10-15 minutes, though the result seems wrong (not exactly wrong but outdated). India's prime minister is Narendra Modi since 2014~ yet it returned answer as Manmohan Singh (who was PM pre 2014~)

When you install config requirements, by default tensorflow and not tensorflow-gpu is installed, as we cannot reliably check if CUDA is installed.
You can install tensorflow-gpu==1.10.0 in the same environment to make the model work with your GPU.

Actually, does deeppavlov uses CPU by default ?
Yes, I recommend uninstalling tensorflow and installing tensorflow-gpu==1.10.0 like @yoptar suggested. According to your tensorflow logs, you are using CPU version.

Outdated answers can appear because we are using the English Wikipedia dump from 2018-02-11.

@yoptar Wow damn me. I thought the P2 instance comes with TF GPU installed by default since it ships a deep learning AMI with all the tools, but it was not. I have now installed TF GPU and confirmed TF was using GPU for operations.
But here is the weird thing, even now, when running ODQA something is very wrong and it feels as if running the code in python hangs or gets stuck for minutes (I thought it was just results/inference but right now just initial steps took 3 minutes of time).

As you can see above, just the data check and download step took whole 3 minutes and now its stuck at that last line, even though resources should not be a problem on such a powerful instance.
@my-master Yes I understand that but thats the weird part, the result is outdated by 5-6 years, since that answer should have been in the 2013~ dump and after it the answer in all dumps should be Narendra Modi

@shubhank008 data and models files for ODQA are very huge, so it doesn't really matter how powerful the instance is, it still will take several minutes to upload 14 GB database, 17 GB ranker matrix, embedding vectors and neural network model from disk to RAM. The good part is that this time is taken only at the first inference. Since everything is uploaded, inference will take less time.
As for the model answer, it could simply be wrong, if two names of prime ministers occur in the same article in different contexts. The algorithm could just miss the part where it says that one of the prime ministers is the former one.

@yoptar so I made it work and leaving what was wrong and solutions for anyone who stumbles upon it.
@my-master Yes, thank you, it took me a while to realize that those steps were related to ram and not gpu and I was under the impression that my cpu/gpu usage is 0% yet they are taking so much time.
Also, using interact mode without -d (download) is way way faster, I will try using python code mode too without download (since I have them downloaded already) to see if its just the code mode which is slower or getting stuck
Furthermore, I am not sure if or how it can be a problem, but I have a vague doubt that keeping 2 terminals open (which I had, one to monitor resource usage top -c/nvidia-smi) was also somehow causing the stuckness/delay. Closing the other terminal window suddenly processed many lines of output at once.
Realized it once I ran free -m and it showed 32GB of Ram usage (while GPU usage was still 0MB).

First of all, the latest deeppavlov requires tensorflow-gpu==1.13.1 (or higher). I tried with 1.0.0 but there are errors related to CUDNNGRU which I believe was added in 1.12 or 1.13
AWS/EC2 does not ship with tensorflow-gpu installed so it needs to be installed. Thankfully they ship with nvidia drivers and a few CUDA versions installed, so just install a version of TF GPU you need and load/use the CUDA version compatible with it.
I ran into many errors due to CUDA version being wrong and had to use a .bashrc and EXPORT file to change in-use cuda versions between 8,9 and lastly 10 (for tf-gpu 1.13.1). You will probably also need to downgrade or upgrade your GPU drivers.
Most of the errors/problems were simply due to mismatch of drivers and installed version of packages (mainly TF, cuda, cudnn)
Use AWS GPU optimization article to disable autoboost and clock the GPU to 100% performance

I have found my success in having it work using TF-GPU 1.13.1, Nvidia Driver 418, CUDA 10.0 on Ubuntu 16.04 with 32GB of Ram. Yet to test on 16GB of lower Ram.
Also, its probably better to download all the models and data separately using the "download" command of deeppavlov so you don't have to use -d or "download = true" while inference. I have kind of fixed my getting stuck and delay issue by doing so.
My initial load time of loading all the data and connecting to the wiki database (loading data to Ram) is approx 2 minutes~
I will try the whole setup on my personal PC and laptop later this week to see how it affects the performance since pc/laptop will be physical dedicated hardware, compared to the virtual resources of cloud instances (I remember reading a report that the HDD/SDD and Ram performance of EC2 or cloud is a bit slower than same hardware in a dedicated/proper PC)

@yoptar @my-master  why does sometimes it fails to give any answers at all even though the question is quite focused and similar. Sometimes it gives answers and sometimes it does not.
Also, maybe its time to start updating the TF calls since lots of warnings about using older methods (maybe the reason why docs/articles suggest 1.0.0 even though you actual need 1.13.1 as even 1.12 did not work).
PS: I was using the en_odqa_pop_infer_enwiki20180211 model
Out of curiosity, I actually thought the difference between this and default model is that this one gives more details/excerpt of the answer (like how the DRQA does).
Is there a way to fetch the relevant excerpt or summary for that answer ?

Its me again, heh.
Finally everything is working although the answers are not accurate enough for real world use, sad. I was quite excited when I saw DrQA and this project and wanted to create a prototype talking bot for my dad's NGO school to showcase the technology and have kids interact and answer general questions to it, but so far the accuracy and relevancy seems quite bad to me.
Was this trained on the whole Wiki dump or partially ? And how long was it trained for ? Asking to know if anything can be done to make it better and more accurate (maybe train more ?).

Its me again, heh.
Finally everything is working although the answers are not accurate enough for real world use, sad. I was quite excited when I saw DrQA and this project and wanted to create a prototype talking bot for my dad's NGO school to showcase the technology and have kids interact and answer general questions to it, but so far the accuracy and relevancy seems quite bad to me.
Was this trained on the whole Wiki dump or partially ? And how long was it trained for ? Asking to know if anything can be done to make it better and more accurate (maybe train more ?).

@shubhank008 Exactly same question! Apparently the answer is not satisfying, I even can not reproduce the same answer as the demo shows. Any idea?

@IgnatovFedor Could you help here, which configuration file are we using on the demo page?

@yurakuratov, we are using en_odqa_pop_infer_enwiki20180211 and ru_odqa_infer_wiki_rubert_noans with 1080 Ti.


Provide x- and y-velocities in drawInternal() Confetto method

These are not calculated because you already use twice-integrated equations of motion based on the current time, acceleration, and initial conditions, but they could be similar fields to currentX and currentY. I'd be happy to submit a PR implementing the feature!
As a side note, the comments in the computeDistance function talk about linear acceleration, when you are clearly dealing with constant acceleration. It would be possible to implement linear acceleration, but I don't see any use cases for it.
As a side note to the side note, If you were to go down that path, you could use generalized mathematical functions from Apache Math to take derivatives, etc.

Sorry for the late reply! What would be the use case for knowing velocity inside drawInternal? The idea is that drawInternal will draw the confetto at that moment in time so velocity/acceleration values are not necessary there.

@jinatonic The use case that I had in mind was for implementing a motion-blur effect that depended on the velocity. I approximated it by remembering the previous x and y values and calculating a displacement, but having the true velocity would let me be one time-step ahead and more precise. Other uses could include a color-based speed indicator, but my main one was for stretching rain particles based on speed to improve the apparent smoothness of the animation.

I see your point. I personally think that it doesn't quite belong in the library as it's not very applicable to the general use-case. I would trade ease of use and understandability over customizability in this case as I don't want to pollute the arguments of drawInternal with these various states that might be confusing to others.
I think this is probably best done via a fork of the library so you can customize it to your needs. I appreciate the your work in the PR though!

@jinatonic Would you be open to me attempting this again in a cleaner and more performant fashion? I worked around it before, but a new downstream issue https://github.com/MatteoBattilana/WeatherView/issues/18 would be solved by having this information in a clean way.

Can you explain the issue a little bit more in detail? I'm not quite sure the problem you are describing with motion blur effect. Also what are your proposed changes at a high level before you dive into implementing it?

Well, in the downstream motion blur issue, the motion blur was dependent on the distance the particle had covered since the last draw call. This worked fine mostly, but had issues when the time between draw calls wasn't "typical", as could happen during lag or when manually calling the draw method.
My proposed change was just to store currentVelocityX alongside currentX in the base Confetto class, and then pass them into the draw methods. Since Java doesn't have the ability to return multiple values from a method simultaneously, I rewrote the computeDistance method to take in a reusable 2-element float array to store the results of x and velocityX.
The change in method signature would mean it wouldn't be backwards-compatible so the version number would have to be bumped, but existing users wouldn't need to change anything in their method body.

I see. I still maintain my stance from before in that this feels like a niche use-case that might be better done via a fork of the project, it makes the public API more complicated for specific use cases.

Okay, here's my last suggestion: What about simply making some protected float currentVelocityX; fields and keeping the method signature of the draw and drawInternal methods ? That would mean no compatibility issues, only internal modifications, and only users that actively seek out the feature would find it so there would be no detriment to the immediate ease of use.


Xcode "Build documentation" not working with Swift Macro package in project

Description
fatal error: module map file
Intermediates.noindex/GeneratedModuleMaps-iphonesimulator/SwiftSyntaxMacros.modulemap' not found
when building documentation for a project with a dependency on SwiftMacro in Xcode 15.2 or Xcode 15.3
It seems like there are more swift syntax package module map files are missing from the  GeneratedModuleMaps-iphonesimulator folder, when comparing to GeneratedModuleMaps folder.
Steps to Reproduce
No response

I've also filed an issue: FB13548539

Issues about Xcode is strictly out of scope for this repo. This will be tracked using the mentioned radar and feedback instead.

@kimdv @ahoppen is there a link I can follow for tracking?

I don’t think there will be a GitHub issue tracking this since this needs to be fixed in Xcode, which is not open source. @d-ronnqvist Please correct me if I’m wrong.


Fails to rerender component once data is loaded

I've noticed an odd issue while using react-query with next js where components sometimes do not rerender when data finishes loading (loading to success). From what I can tell, it only happens on the first render of the app and when multiple components are using the same query. In addition to the multiple components, one of them needs to have a side effect that causes a rerender on the first render (ex useEffect that sets some state).
Code sample: https://codesandbox.io/s/stoic-currying-n4h7x?file=/pages/_app.js
In the sample there are two pages, index and works, where the index page demonstrates the conditions that trigger the bug.
I've added a gif to help explain what I am talking about. Note the issue only happens on the first app render on the main index page where it calls set state from the effect but not on the first app render for the 'works' page. On the index page, making the sidebar rerender by incrementing the count fixes/syncs the state.

Same issue

I start getting a similar issue on the first app render as well after upgrading react-query's version. After some research, I think the issue was introduced in v1.3.5.
In the codesandbox below, we can see that:

The issue goes way if you choose a version before v1.3.5 (e.g. v1.3.4).
Commenting the useEffect in Main.jsx fixes the issue also.

https://codesandbox.io/s/long-mountain-73425?file=/src/components/Main.jsx

Also started seeing this. It doesn't trigger an update in the hook consumer.
Downgrading to 1.3.4 fixed the issue for me.

@thebuilder I think that the bug was actually introduced in 1.3.0, I went through and tested the different versions in codesandbox and they started to break with 1.3.0...

1.3.0 has the bug
1.2.9 works correctly

I've tracked down the commit that introduced the bug.

@thebuilder I think that the bug was actually introduced in 1.3.0, I went through and tested the different versions in codesandbox and they started to break with 1.3.0...

1.3.0 has the bug
1.2.9 works correctly

Interesting 🤔So, we might be dealing with two different issues here.
@kyle-mccarthy , just for the record, as I mentioned, you can easily see in the codesandbox below, which is essentially a simplified version of yours, in CRA with asyn/await, that the faulty version is v1.3.5.
Btw, thank you for the sandbox 🙏
https://codesandbox.io/s/long-mountain-73425?file=/src/components/Main.jsx

@jcmnunes oh yeah that is interesting... I wonder if they are the same bug but different conditions on which it occurs.
I tracked down the line of code that is actually causing the problem (well mine at least). I think that it may be a race condition or something of the sort. Commenting the line out fixes the problem but would break suspense from what I can tell.
https://github.com/tannerlinsley/react-query/blob/v1.4.1/src/useBaseQuery.js#L79

@jcmnunes oh yeah that is interesting... I wonder if they are the same bug but different conditions on which it occurs.
I tracked down the line of code that is actually causing the problem (well mine at least). I think that it may be a race condition or something of the sort. Commenting the line out fixes the problem but would break suspense from what I can tell.
https://github.com/tannerlinsley/react-query/blob/v1.4.1/src/useBaseQuery.js#L79

Nicely done @kyle-mccarthy 👍But that line is added precisely in v1.3.5. That checks out with what I found. Am I missing something? It seems we agree on the faulty version after all.

@jcmnunes So that line of code is part of the problem, but there was also a change to the queryCache introduced in 1.3.0 when the subscribe method was changed. https://github.com/tannerlinsley/react-query/compare/v1.2.9...v1.3.0#diff-2c6b0e709da79e736512dd96001d9716
I forked the repo and added my fix, it looks like it resolves both of our problems. https://github.com/kyle-mccarthy/react-query/commit/623a3dcc0af528eb5e1c5fb5707cdeadd9b48bea
I can make PR with the fix, however, I am not sure what the repercussions are of not filtering out instances that are used for suspense.

I can make PR with the fix, however, I am not sure what the repercussions are of not filtering out instances that are used for suspense.

Yes, I totally understand that. We might need help from @tannerlinsley on this one ;)

I'm pushing a potential fix (pending the tests actually pass in CI this time... 🙄 )

I think it's gonna work!

@tannerlinsley awesome! BTW I just checked and the code on master does fix both issues. Thank you!


os-iperf: Add option to set port

Important notices
Before you add a new report, we ask you kindly to acknowledge the following:
[x] I have read the contributing guide lines at https://github.com/opnsense/plugins/blob/master/CONTRIBUTING.md
[x] I have searched the existing issues and I'm convinced that mine is new.
[x] When the request is meant for an existing plugin, I've added its name to the title.
It would be nice to have an option to set port for Iperf because setting port on clients on every run is very annoying.
Describe the solution you'd like
I would like an input field in the /ui/iperf.

+1 on this request. Because without this option, you always need to configure a FW rule manually for each session.


add support for payment surcharges

Added support for payment surcharges, but it also could be used to implement surcharges in general.
The payment surcharges defined per country are still missing in this implementation.

Hello,
thank you for creating this pull request.
I have opened an issue on our Issue Tracker for you. See the issue link: https://issues.shopware.com/issues/PT-9144
Please use this issue to track the state of your pull request.

@nicoanders Thank you for your work. If you rebase it to our master and resolve any conflicts, I see no trouble in releasing it.

@seggewiss Thanks for caring about the PR.
In all of my tests I could not verify that there is some data missing.
I also added some unit test to ensure some base functionalities.
Could you please describe the steps to fail with more details? Especially what are the surcharge values in the according payment method?

@nicoanders No need to thank me :)
First to reproduce this error please pull this branch not any forked version into a fresh environment.

Create a new backend order as the payment method choose invoice (surcharge of 2,50€)
-> add any product, customer and create the order
Open the regular order overview and click on edit.

What we see:
-Big yellow warning "Customer was deleted or not found"
-For example, these fields are missing: IP-Address, date time, customer and so on
What we have debugged so far:
The Problem seems to appear on the flush. Before the flush, the object is complete and contains all data, after the flush data gets lost somehow.

Hello. Thank you for your contribution. This does not work correctly. Like Sebastian said it does not create the order correctly. Would be nice of you could solve the described issues. Otherwise we can not merge this pull request.

Hi @htkassner,
I will provide a solution within this week.

We will close this PR for the moment, due to inactivity, but would be happy if you would contribute this again with another PR. Thank you.


Support ClickHouse as an observability backend

Proposal
We see more and more adoption of ClickHouse as an observability backend that can efficiently deal with very large datasets with good support for OTel. At the moment, it's best suited for logging and tracing support but ClickHouse has on the roadmap for this year a PromQL compatibility layer that will enable the metrics use-case as well.
Here are some references:

OLAP for Monitoring with ClickHouse on Kubernetes, at eBay
HTTP Analytics for 6M requests per second using ClickHouse, at Cloudflare
A cost-effective logging platform using Clickhouse for petabyte scale, at Zomato
Fast and Reliable Schema-Agnostic Log Analytics Platform, at Uber
ClickHouse for Observability, at Gitlab
LLM Monitoring, at Helicone
ClickHouse for OpenTelemetry Traces, at Resmo

ClickHouse is also used as a backend for some popular observability SaaS providers including:

Signoz.io
Highlight.io
Qryn
BetterStack

Disclaimer: I work at ClickHouse and we will be happy to help!

Hi @Ryado,
It's really cool to see observability backend like ClickHouse that would like to support Perses !!
I think it can make sense that Perses can support other thing than just Prometheus or Tempo. For example time to time, people would like to connect Perses to a mysql database.
But before taking time to adopt others datasources, I think we really need to work on the plugin part. Today implementing a plugin is quite hard and it needs to be done in the upstream repository because it needs to be compiled with everything else.
It becomes more and more urgent to be able to externalise the plugin and so to be able to load a plugin at the runtime. If you want to help on this area, that would be super cool !
Once it is done, we can then consider if adding a ClickHouse plugin directly in Perses makes sense or if you should just provide it on your own side.

Makes total sense. Please let us know when the plugin architecture is ready and we can definitely consider a contribution to support ClickHouse

Hey @Nexucis, very interested if there's any progress on the plugin integration. Perhaps we could even implement this in the upstream repository if the internal API is stable enough. Will you be at KubeCon NA 2024? I'm in the CNCF Slack too if you have time to chat about this more.
Thanks!


Can't play an audio file that was downloaded from server but the data is the same

Hello! I am enjoying your framework but have some problems with file reading. I use Novocaine to upload data to parse.com and then retrieve it back. I then can't play what was retrieved.
        PFQuery *q = [PFQuery queryWithClassName:@"Test"];
        [q getObjectInBackgroundWithId:audioId block:^(PFObject * _Nullable object, NSError * _Nullable error) {
            PFFile *file = object[@"file"];
            [file getDataInBackgroundWithBlock:^(NSData * _Nullable data, NSError * _Nullable error) {
                NSString *p = [NSSearchPathForDirectoriesInDomains(NSDocumentDirectory, NSUserDomainMask, YES).firstObject<EMAIL_ADDRESS>                [data writeToFile:p atomically:YES];

                self.fileReader = [[AudioFileReader alloc]
                                   initWithAudioFileURL:[NSURL fileURLWithPath:p]
                                   samplingRate:self.audioManager.samplingRate
                                   numChannels:self.audioManager.numOutputChannels];

                [self.fileReader play];

                [self.audioManager setOutputBlock:^(float *data, UInt32 numFrames, UInt32 numChannels)
                 {
                     [wself.fileReader retrieveFreshAudio:data numFrames:numFrames numChannels:numChannels];
                 }];
            }];

I am getting Error: Opening file URL (ExtAudioFileOpenURL) ('dta?'). I compared the data that was uploaded to the one that I downloaded and they are 100% equal. isEquatToData: just says that. What can be the problem? I called play on manager before this block so it doesn't matter.

It's unclear to me if this is an issue with Novocaine, or with the surrounding code. I'm going to close the issue, but if you can demonstrate it's an issue with Novocaine with a contained test case, I will reopen.


Updating jQuery

Hello!

Type: enhancement

In raising this pull request, I confirm the following:
Upgrading jQuery for the API generation
Thanks

This relates to the dependencies - security check from GitHub

Thank you


[FEATURE] Inline HTML is displayed in footer

Steps to reproduce
Tell us about your environment:

Puppeteer version: 1.7.0
Platform / OS version: MacOS 10.13.6
Node.js version: v8.2.1

What steps will reproduce the problem?

With foo.js:

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();
  await page.goto(`data:text/html,<html><body>Hey there</body><html>`, {waitUntil: 'networkidle2'});
  await page.pdf({
    path: 'inline.pdf',
    format: 'A4',
    displayHeaderFooter: true,
    format: 'A6',
    margin: {
      bottom: '2cm'
    }
  });

  await browser.close();
})();

$ node foo.js

What is the expected result?
To be able to display something other than the source HTML for the URL.  I definitely wouldn't call this issue a bug.. it is the expected result, however it would be more useful to be able to specify the 'display url' via the pdf options, particularly when the page content is inline HTML. Current alternative would be to override the footerTemplate to try match the 'standard' template, but that feels like overkill.

https://example.com

  /

I see from the source that the options are somewhat passed verbatim to the client via Page.printToPDF, so it would appear that this feature would need to be implemented upstream first. Is this something that would be considered??
What happens instead?
The inline HTML is displayed in the footer:

I've found I can resolve this issue by using request interception (as apposed to data URL) as detailed here: https://github.com/GoogleChrome/puppeteer/issues/728#issuecomment-359047638


Face detection don't work on AWS Lambda due to node-canvas not working on node 8.10

Hi there!
I am trying to get this up and running on AWS Lambda but are having trouble as it seem the 'canvas' package is broken on node 8.10. I am trying to get some face detection going.
https://github.com/Automattic/node-canvas/issues/1252#issuecomment-437598572
It looks like its kind of a pain to try and run any other version of node on AWS Lambda, so I started trying to use it without the canvas package. As you mention in the README and I also noticed that the faceapi.locateFaces() function also takes a Tensor4D class as input. I have never used Tensorflow and I am a little confused as how to turn a ArrayBuffer from axios into a correctly shaped Tensor4D object.
I am fetching a jpeg image using axios.
I found the tf.tensor4d function but not sure what shape and dtype it should be.
Do you have any idea?
My code so far:
const { data: imageBuffer } = await axios.get(url, {
	responseType: 'arraybuffer'
})
const imageTensor = tf.tensor4d(imageBuffer, [?, ?, ? ,?])
const faces = await detector.locateFaces(imageTensor)

Error messages look similar to this one:
Error: Based on the provided shape, [1,2,3,4], and dtype float32, the tensor should have 24 values but has 68695
Any help is greatly appreciated!

Hey man, hows it going?
Ohh that's a pity, node-canvas is obviously the easiest way to use face-api.js with node.
Well you can either pass in tf.Tensor3Ds or tf.Tensor4Ds with a batch size of 1:
const imageTensor = tf.tensor3d(imageBuffer, [height, width, channels]), where channels should be 3 and in RGB order.
However, the imageBuffer you receive from axios is most likely jpeg or png encoded right? You have to create the image tensor from the raw image data, so you will have to decode the data first. There are probably npm packages, which can do that for you. For example I have seen people using ffmpeg for this.

Thanks!
Tried the get-pixels npm package and it works!
get-pixels return a 4 channel array all the time, even for jpegs 🤷 , so had to remove the alpha channel.
const pixels = await new Promise<Pixels>(resolve => {
	getPixels(url, (err, pixels: Pixels) => {
		if (err) {
			throw err
		}
		console.log('pixels:', pixels)
		resolve(pixels)
	})
})

// remove alpha channel
const RGBValues = []
pixels.data.forEach((px, i) => {
	if ((i + 1) % 4 != 0) {
		RGBValues.push(px)
	}
})
const imageTensor = tf.tensor3d(RGBValues, [pixels.shape[1], pixels.shape[0], 3]) as any
const faces = await detector.locateFaces(imageTensor)

Now to the task of getting it up on Lambda without breaking their code size limit, wish me luck!

Thanks!
Tried the get-pixels npm package and it works!
get-pixels return a 4 channel array all the time, even for jpegs 🤷 , so had to remove the alpha channel.
const pixels = await new Promise<Pixels>(resolve => {
	getPixels(url, (err, pixels: Pixels) => {
		if (err) {
			throw err
		}
		console.log('pixels:', pixels)
		resolve(pixels)
	})
})

// remove alpha channel
const RGBValues = []
pixels.data.forEach((px, i) => {
	if ((i + 1) % 4 != 0) {
		RGBValues.push(px)
	}
})
const imageTensor = tf.tensor3d(RGBValues, [pixels.shape[1], pixels.shape[0], 3]) as any
const faces = await detector.locateFaces(imageTensor)

Now to the task of getting it up on Lambda without breaking their code size limit, wish me luck!

Thanks, that helped me. But it's quite slowly (1000ms) compared to canvas ( < 10ms ).

tensorflow team is working on a solution: https://github.com/tensorflow/tfjs/issues/298#issuecomment-442263569

Nice!

It wasn't easy, but I finally got it running in a Lambda on AWS.
The tfjs-node package includes a native library and has to be built using the correct environment. I achieved this using Docker and the lambci/lambda:nodejs8.10 image from the https://github.com/lambci/docker-lambda project. This image seem to be one the best images to simulate the Lambda environment.
The built tfjs-node module includes a 110mb binary file.
@tensorflow/tfjs-node/deps/lib/libtensorflow.so
The Lambda size limit is 250mb (uncompressed).
Well, with 140mb left for other modules it should be fine right?
I tried deploying the package using serverless deploy resulting in this cryptic error message.
ENOENT: no such file or directory, open<EMAIL_ADDRESS>The file exists alright, but its a symlink that points to
libtensorflow.so -><EMAIL_ADDRESS>Ahh, the symlink was created inside the docker container and it is a not a relative link. Ok, so i delete the symlink and created a new one that is relative.
libtensorflow.so -> ../../deps/lib/libtensorflow.so
But zipping up the package, using serverless deploy results in a zip that when uncompressed is 343mb ?? Using Disk Inventory X on the uncompressed folder I saw this:

Why are there 2 large binaries? Shouldn't one of them just be a symlink ? The symlink is gone, and replaced with a copy of the binary. Hmm.
After a bit of research I learned that the default behaviour when zipping symlinks is that they get "resolved" (link is followed and original content is copied). Ok. But there is a --symlinks flag for the zip program that can modify this behaviour to keep symlinks as they are, instead of resolving them. This solved the size issue, nut now I realised that I depend on a local project that is linked that actually need to be resolved when packaged. I couldn't find any way to specify what folder/file should be resolved or not when packaging through serverless. There is a way to exclude files/folders from package though. I excluded the symlink.
package:
    exclude:
        -<EMAIL_ADDRESS>
So using the following commands I first package the project (excluding the symlink) and then manually include the symlink again into the zip archive. (-y is the shorthand for --symlinks)
sls package --package my-artifacts
zip -y my-artifacts/serverless-face-api.zip<EMAIL_ADDRESS>
Now I have a package that is 233mb! Yeah, 17mb to spare! Hehe. Ofc there are more size reduction that can be made be excluding more stuff, like excluding unused weights/models from face-api etc.. But I was just happy to get below the limit.
Happy as a unicorn on christmas I deployed my neat "little" package to AWS.
sls deploy --package my-artifacts
.. and lived happily ever after.

libtensorflow.so appears to be 183mb now! don't suppose you could share your package.json for version numbers?

Sure, here are my deps, haven upgraded in a while :)
{
    "@tensorflow/tfjs-node": "^0.2.1",
    "axios": "^0.18.0",
    "face-api.js": "^0.17.1",
    "get-pixels": "^3.3.2",
    "lodash": "^4.17.11",
    "module-alias": "^2.1.0",
    "moment": "^2.23.0",
    "monk": "^6.0.6",
    "url-join": "^4.0.0"
}

The @tensorflow package (version 1.2.3) is now 294MB!  libtensorflow.so.1.14.0 is now 216MB, and libtensorflow_framework.so.1.14.0 is another 35MB. Pretty sure there is now way to get this package into Lambda.
@MatthewAlner did you manage to get it working with a newer version? Or do I need to roll all the way back to the versions used by @bobmoff

Perhaps you could try to deploy using https://www.openfaas.com/

I didn't in the end 😞

Thanks for all the helpful info in this issue, and of course thanks again to @justadudewhohacks . I did eventually manage to get it working on Lambda, but it wasn't easy. I ran into all the same problems that @bobmoff did, and if I'd read his post more carefully at the start I would have saved myself a lot of time (in particular the libtensorflow.so linking issue). I'm using the Node 10.x runtime.
The newer versions of tfjs-node just get bigger and bigger, especially their bundled .so files. There is no way I could find to make the newer versions fit within Lambda's 250MB limit, so I had to roll way back to v0.2.1. You also need to roll face-api.js back to a similarly old version, as it seems face-api.jsis coupled to a specific version oftfjs-node`. Below is my deps:
  "dependencies": {
    "@tensorflow/tfjs-node": "^0.2.1",
    "face-api.js": "^0.17.1",
    "get-pixels": "^3.3.2"
  }

If you really wanted to use the latest version of Tensorflow and Face-api, I suspect you could use a technique like this https://github.com/lucleray/tensorflow-lambda, which basically uploads a zipped copy of the dependencies, and then unzips them into /tmp before running them. There is obviously overhead for unzipping the files, but if your lambdas instances are often reused then that initial overhead fades away.

Hey @bobmoff, just wondering if you had any issues with memory leaks in your setup? My face detection lambdas get reused most of the time because they get called so often, and I've noticed the memory used slowly grows with each invocation, until it finally breaks the Lambda memory limit and starts again. No idea if it's get-pixels, tfjs-node or face-api.js that is the issue.

Howdy @henrydawson. No, sorry. I havent experienced that, but that is probably due to the fact that I havent had the pressure like you seem to have, so my containers/lambdas have probably been recycled before that happenes.

Hi @henrydawson and all,
just some feedback on canvas running on lambda and also a question.
I've managed to make canvas run on lambda by using https://github.com/lambci/docker-lambda to make some tests. Thanks to the "build" image I had to run a bash shell on the docker build image to:
1/ run npm install
2/ copy 3 libraries from the docker build image /lib64 to the root of my project: libblkid.so.1, libmount.so.1, libuuid.so.1
I'm now trying to use https://github.com/lucleray/tensorflow-lambda for tensorflow but with no luck.
My little project is based on one of the examples from the repository. It uses the common directory as in the examples directory and I've tryed to subsitute the import '@tensorflow/tfjs-node'; from the env.ts file with import "tensorflow-lambda" but it does not work.
It looks like tfjs-node have a mechanism to supersede the tfjs-core functions but this is not happening with tensorflow-lambda. Any hint on how I could make this happen ?
Thanks in advance !

@bobmoff i am new to this, and wanted to ask if you've got an example code to get started with face-api.js and AWS lambda?

@bobmoff i am new to this, and wanted to ask if you've got an example code to get started with face-api.js and AWS lambda?

Sorry. Not using this any more. But Lambda have upped the limit to 10GB for each function so size should not be a problem any longer.

@bobmoff I really wanna move this facial recognition to lambda. Any help would be highly appreciated. I tried with this version also
"dependencies": {
    "@tensorflow/tfjs-node": "^0.2.1",
    "face-api.js": "^0.17.1",
    "get-pixels": "^3.3.2"
  }

but still limit exceeding.

Are you reaching the max limit of 10gb ?
The issue I had was getting below 250mb.

Are you reaching the max limit of 10gb ?
The issue I had was getting below 250mb.

Going above deployment package unzipped limit size (250mb)

If you switch using containers you can use 10 gb.
https://aws.amazon.com/blogs/aws/new-for-aws-lambda-container-image-support/

Hi, I did get this working on Lambda a long time ago, but that was with older versions, and I ran into a lot of issues (especially the hard to resolve memory issues mentioned above). Eventually, I gave up on Lambda and just run it on EC2 using spot instances, which was cheaper and better for my workload. It was also simpler as I didn't have mess around with the file size issues.
That said, I recently used EFS with Lambda for some image processing that required extra space, and it was really easy to use. I imagine you could use EFS to get around all the size limits.
https://aws.amazon.com/blogs/compute/using-amazon-efs-for-aws-lambda-in-your-serverless-applications/

@bobmoff @henrydawson thank you both of you for pointing me in the direction.

@bobmoff I have successfully deployed in Lambda using containers. But I'm facing one issue. I'm just doing faceapi.detectSingleFace().withFaceLandmarks().withFaceDescriptor() in lambda to detect single face and returning that output as a response via API Gateway. I can't able to return without doing JSON.stringify(result) and If I do stringify the result, that result not working in final comparison. I dont know what I'm doing wrong.


Update README.md

Codecov Report

Merging #40 into master will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff          @@
##           master    #40   +/-   ##
=====================================
  Coverage     100%   100%
=====================================
  Files           2      2
  Lines          72     72
  Branches       16     16
=====================================
  Hits           72     72

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 927af9f...0e516af. Read the comment docs.

Codecov Report

Merging #40 into master will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff          @@
##           master    #40   +/-   ##
=====================================
  Coverage     100%   100%
=====================================
  Files           2      2
  Lines          72     72
  Branches       16     16
=====================================
  Hits           72     72

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 927af9f...0e516af. Read the comment docs.

Thanks @richardtorres314! ;)


Should the "environment" episode be shortened or moved outside the lesson?

I believe I spent too much time on this topic.

It stays in, as it introduces useful commands and concepts that are reused later. But the delivery should be improved, especially wrt to timing.


Ion Toolbar color isn't rendered correctly in safari if there are multiple toolbars in one header

Bug Report
Ionic Info
<EMAIL_ADDRESS>
Describe the Bug
If a header contains more than one ion-toolbar, the ion-toolbar background color isn't rendered correctly.
Steps to Reproduce
Steps to reproduce the behavior:

View this: https://codepen.io/corysmc/full/EpzJVR/
In Chrome the colors are correct
In Safari the background colors are all light, button/text colors are correct.

Related Code
https://codepen.io/corysmc/full/EpzJVR/
Expected Behavior
color is consistent across browsers.
Additional Context
We have several screens where I might want a few toolbars in the header, the primary toolbar is dark, where the search toolbar is light.
Also note, this is broken in beta.0, beta.1, beta.2, and works in alpha.11.

Thank you for the issue! We'll look into this.

Will be fixed in the beta.4 release. 🙂


fix: batch inf example should use new lifecyle API

It's failing CI over in https://github.com/modal-labs/modal-examples/pull/285

Thanks!


Maximum nu of multi agents that can be supported

Hi Support Team
I am working on a survey for Carla capabilities and need few clarifications regarding the number of supported agents.
a) What is the maximum number of agents that can be supported on a normal desktop(16GB RAM, GPU, Linux)
b) Is it possible to add custom vehicles. I want to design my own vehicle and use it inside simulation framework.
Neeraj

Hi Team
Can you please revert back on this issue
Neeraj

@pravinblaze could you please provide help with this question?


fix: PseudoTerminal not work

Types

[x] 🐛 Bug Fixes

Background or solution
Changelog
PseudoTerminal not work

/publish

LGTM


Demo is one version ahead of github code ?

It appears that the github code is at version 1.1.1, but the Demo is at 1.1.2. And there appears to be a slight bug in the presentation of previews in 1.1.1.  The demo version appears to be condensed (uglified?), so it's not easy to work with.
Would it be possible to update the code base to 1.1.2 ?
Thank you!

Sure, I have noticed lately that the Uglify makes some compressed macros and tiddler do not work correctly! I used uglified version for demo and drag and drop install with "small is better" in mind!
I will update to the latest version this weekend!

The release is not compressed and updated to TW 5.3.3


Fixed old syntax in 03.mdx

Updated syntax change:
sp.import_script_from_url -> sp.io.import_script_from_url
sp.import_template -> sp.io.import_template
sp.bytes_of_string -> sp.utils.bytes_of_string
Fixed typo:
assume_consecutive_tokens -> assume_consecutive_token_ids
Please refer to issue #358

Hi @bhaskarSingh, I would like to request for review on this change. Thanks


Changes to PathAlterationDetector/PathAlterationObserverScheduler

Rename PathAlterationDetector to PathAlterationObserverScheduler as the current name is confusing. The class does not detect anything.
Currently, passing an interval <= 0 will throw an exception in start(). Change the logic to not schedule anything instead.
Trivial simplification in addPathAlterationObserver()

LGTM.


Use reserved OVS controller ports for default Antrea ports

Use reserved OVS controller ports for default Antrea ports
Tunnel port, gateway port and uplink port.
These reserved port numbers (starting from 32,768) will never be
auto-assigned by OVS. By using them, we can avoid surprising ofport
changes in some edge cases.
Note that if these ports already exist when the Agent starts, we will
not re-create them or mutate their ofport. The new ofport values will
only be used when creating the OVS ports for the first time (e.g., on a
new K8s Node, or after a Node restart). That is the simplest solution
and is consistent with existing behavior. It should also be sufficient
for avoiding #6192, which was typically triggered by creating a new
tunnel port when updating the Antrea configuration in an existing
cluster.
After this change, we will also assume that br-int ports stored in OVSDB
always have the "antrea-type" external ID. This external ID became
required in Antrea v1.5, so this should be an acceptable change,
especially considering that this change is destined for the Antrea v2
release, which is a major version bump. Users will not be able to
upgrade from Antrea v1.5 to Antrea v2.0, but that this is not a
supported upgrade path anyway (for other reasons).
We also add some logic to prevent creating a port on the OVS bridge if a
required external ID is missing.
Fixes #6192

@wenyingd these are good points. I need to improve the code so that we handle all ports like the tunnel port: if it already exists, keep using the existing port with no changes. If the port needs to be created, use the new ofport_request values.

BTW, do we need to customize a new reserve port for host interface, which is now used in AntreaIPAM, and it may be used on Windows in future to replace the bridge interface?

Do you mean HostInterfaceOFPort? We use the UplinkOFPort (3) reserved value for this.
Is there another one I am missing?

/test-all
/test-flexible-ipam-e2e

@wenyingd these are good points. I need to improve the code so that we handle all ports like the tunnel port: if it already exists, keep using the existing port with no changes. If the port needs to be created, use the new ofport_request values.

BTW, do we need to customize a new reserve port for host interface, which is now used in AntreaIPAM, and it may be used on Windows in future to replace the bridge interface?

I see what you mean now. But can you remind me why this is not BridgeOFPort (OFPP_LOCAL / 0xfffffffe)?

With AntreaIPAM and VM Agent scenario, we now create a different OVS port to take over the role of the uplink, so the latest implementation is to rename the uplink as ${originalName}~ , and name the new host interface as ${originalName}.  In this way, 1) the nic configured with Node's IP looks the same as what it is was before running antrea, then it could reduce the impact on other processes running on the Node/VM which may have dependency on the nic's name. 2) we keep OVS bridge as "br-int", so the new host interface is a different port, then we can't use the reserved LOCAL port (0xfffffffe).
This mode is also planned on Windows container case, @XinShuYang  has a patch working on it.

/test-vm-e2e

After https://github.com/antrea-io/antrea/pull/6216 is merged, I will rebase, squash commits, and run tests again.

/test-flexible-ipam-e2e

/test-all
/test-flexible-ipam-e2e
/test-vm-e2e
/test-windows-all

/test-all
/test-flexible-ipam-e2e
/test-vm-e2e
/test-windows-all

/test-windows-all

/test-windows-all

Windows CI failed due to Get-NetIPInterface failure, it seems br-int was not found after antrea agent started.
Error log:

===== Check Interface DHCP Status =====
Get-NetIPInterface : No matching MSFT_NetIPInterface objects found by CIM query for instances of the
ROOT/StandardCimv2/MSFT_NetIPInterface class on the  CIM server: SELECT * FROM MSFT_NetIPInterface  WHERE
((InterfaceAlias LIKE 'br-int')) AND ((AddressFamily = 2)). Verify query parameters and retry.
At line:1 char:2

(Get-NetIPInterface -InterfaceAlias br-int -AddressFamily IPv4).Dhcp

 + CategoryInfo          : ObjectNotFound: (MSFT_NetIPInterface:String) [Get-NetIPInterface], CimJobException
 + FullyQualifiedErrorId : CmdletizationQuery_NotFound,Get-NetIPInterface

Newly created uplink DHCP status is different from the original adapter. Original DHCP: Enabled
, br-int DHCP:

Thanks @XinShuYang, I was able to reproduce locally:
PS C:\var\log\antrea> cat '.\antrea-agent.exe.EC2AMAZ-EHTEEQ1.WORKGROUP_EC2AMAZ-EHTEEQ1$.log.INFO.20240418-232214.3356'
Log file created at: 2024/04/18 23:22:14
Running on machine: EC2AMAZ-EHTEEQ1
Binary: Built with gc go1.21.5 for windows/amd64
Log line format: [IWEF]mmdd hh:mm:ss.uuuuuu threadid file:line] msg
I0418 23:22:14.296934    3356 log_file.go:93] Set log file max size to 104857600
W0418 23:22:14.354355    3356 options_windows.go:68] AntreaProxy is not enabled. NetworkPolicies might not be enforced correctly for Service traffic!
I0418 23:22:14.356588    3356 agent.go:105] "Starting Antrea agent" version="v2.0.0-dev-b46ba51"
I0418 23:22:14.359131    3356 client.go:89] No kubeconfig file was specified. Falling back to in-cluster config
I0418 23:22:14.421688    3356 prometheus.go:189] Initializing prometheus metrics
I0418 23:22:14.432940    3356 ovs_client.go:70] Connecting to OVSDB at address \\.\pipe\C:openvswitchvarrunopenvswitchdb.sock
I0418 23:22:15.443925    3356 ovs_client.go:89] Not connected yet, will try again in 2s
I0418 23:22:17.447747    3356 ovs_client.go:89] Not connected yet, will try again in 4s
I0418 23:22:21.459490    3356 discoverer.go:82] Starting ServiceCIDRDiscoverer
I0418 23:22:21.470700    3356 agent.go:377] Setting up node network
I0418 23:22:21.586204    3356 agent.go:991] "Got Interface MTU" MTU=1450
I0418 23:22:27.391941    3356 net_windows.go:456] "Creating HNSNetwork" name="antrea-hnsnetwork" subnet="<IP_ADDRESS>/24" nodeIP="<IP_ADDRESS>/24" adapter={"Index":2,"MTU":1500,"Name":"Ethernet 3","HardwareAddr":"BrhWpt87","Flags":51}
I0418 23:22:40.530606    3356 net_windows.go:605] Enabled Receive Segment Coalescing (RSC) for vSwitch antrea-hnsnetwork
I0418 23:22:40.530606    3356 net_windows.go:544] "Created HNSNetwork" name="antrea-hnsnetwork" id="F5951EC0-156C-423A-8E4F-124CD6E441F1"
I0418 23:22:40.533079    3356 ovs_client.go:137] Created bridge: 533bd55c-2283-4078-a96c-a235ab0b6c28
E0418 23:22:40.645905    3356 agent_windows.go:260] Failed to add uplink port Ethernet 3: missing required externalID 'antrea-type' for port 'Ethernet 3'
F0418 23:22:44.717311    3356 main.go:53] Error running agent: error initializing agent: missing required externalID 'antrea-type' for port 'Ethernet 3'

I will push a new commit to address this.
Do you know if we upload the agent logs as artifacts for the Windows CI jobs? I couldn't find them.

/test-windows-all

@wenyingd @tnqn please take a look at the new commit. There was a test failure on Windows because the uplink port was being created without the antrea-type external ID

/test-all

@wenyingd @tnqn please take a look at the new commit. There was a test failure on Windows because the uplink port was being created without the antrea-type external ID

Good to see the new check catches it.

/test-flexible-ipam-e2e

TestAntreaIPAMAntreaPolicy/TestGroupNoK8sNP/Case=ACNPEgressDropSCTP is failing for test-flexible-ipam-e2e. It is unrelated to this PR. The TestAntreaIPAMAntreaPolicy/TestGroupNoK8sNP test group has been flaky, and this should be tracked by https://github.com/antrea-io/antrea/issues/6237.

This is a pretty significant change and it will not be back-ported for several reasons.
Historically, production users have not run into #6192.


Fix macro crash when handling sealed case classes

Fixes #628
Sealed classes can be instantiated directly. Therefore, when generating the typeTag, I included the sealed class itself. This ensures that the macro correctly handles sealed classes without subclasses. To check whether it’s a sealed class and not a trait or abstract class, I used the following condition:
sealedParents.find(_ == tpe.typeSymbol)

Since trait and abstract class cannot be instantiated, I believe this approach works. However, I could also explicitly check that the symbol is not a trait or an abstract class, if needed.
What do you think?

@nox213 looks great, thanks!


Rel url

TODO

more tests and documentation for the trailing slash dilemma

Coverage increased (+0.03%) to 97.943% when pulling 19152fad640d2a3edb90b65b4ce508b2f27452cf on rel-url into 4d9cbf0cf9c1e08f70872e1d3e42891116dcc7ad on v7.


helm: introduce affinity to select specific nodes for the DaemonSet

This patch allows users to define custom affinity rules in values.yaml, specifying preferred nodes for plugin DaemonSet Pods. Follows Kubernetes structure for affinity fields.

This LGTM. I just wonder if we should also add support for simple label-based nodeSelectors ?

Done.


some warnings about node 12 and set-output

could u spare some time to fix it?
thx

Hi @Ritchie1108, this should be resolved now.
Please use the latest version 1.2.1 in your workflows.
Thanks for opening an issue!


feat: stubs mounting option

We should support
mount: {
  stubs: {
    ComponentToStub: true // default stub
    Another: h => h('div') // custom stub
  }
}

I am going to investigate this more with the following in mind:

stub as an "empty" vue component
when you find a stub, it returns a VueWrapper
provide your own custom "stub"

This can be considered an "advanced" usage, mainly provided for backwards compat - ideally people should find and assert on dom elements and their markup.


Added Bubble sort implementation in cpp and python

Added bubble sort implementation in cpp and python.
#1

Could you please edit the README file too ?

I have added Bubble sort in README


[W-15177355] Update collapsible block styling

Match Salesforce styling for accordion items, or as Asciidoc calls them, collapsible blocks.
Testing

Tested in Chrome and Safari.
Tested across multiple screen resolutions.
Added example collapsible blocks to the preview site for testing.

Including a few screenshots of the output below.
Stacked blocks:

Hover styling:

Wrapped title and heading in block:

Thanks for the thorough testing as always! I though it looked a bit funny during testing as well, but left it since it matched the current behavior here.
I went ahead and tracked down the issue--our code wasn't finding any innerText for the headers, which makes sense since the tables aren't visible on page load. Switching to textContent fixes the issue. While I was at it, I reduced the table margin so it wouldn't look so wonky:

As a side-note, I don't know why we chose not to display the mobile table toggle for nested elements, but it was done intentionally so I left it. You can see where that's set here.


[REQUEST] Improve Renaming

I would like to suggest improving the renaming. Currently the renaming is not very helpful:
vol_000-0
I would suggest having one:
[**NAME OF MANGA** ] - VOL. [**#**] - CH. [**#**].cbz

You always have a folder in which the chapters are located.
Unfortunately, not all sites allow you to do so.
For example, sometimes there are chapters of this content:
Volume 4 Chapter 33.4
And sometimes it is not addressed in any way. Only hash-url for page.
But I'll try.
Keep for updates.

@1271 What about scrapping the text of the URL links themselves and not the URL itself?

Clarify please.
English is not my native language. )

I am suggesting grabbing the name not from the URL itself but from the hyperlink.

Sorry, I do not have access to the page where you received the link.
I can not know what name the hyperlink had.
Some providers use the manga title as the folder name. This will be used in manga-py version 2.
I'm sorry, but changing all providers is not profitable now.
Please use version 2 when it is released.
Planned time of release - the beginning of 2019.

@1271 I was referring to kissmanga and mangarock, those are the only two reliable sites I have been. I figure mangadex could be good too.
The links to the manga have all the information there.
On an unrelated note, can manga-py put this into a pdf format instead of a cbz one?

pdf?  Yes it is possible.
I was referring to kissmanga and mangarock (,-_-)
You did not indicate this in the message.
https://github.com/yuru-yuri/manga-dl/issues/117#issue-358781729
Please wait for the new version of manga-py.
In this update, the ability to change the name of the archive will be added.
If you still need pdf support, please make a separate issue.
I would not want to mix a few things together.
Thank you for using manga-py.

@1271 I am building manga-py directly from GitHub, just an FYI.
Please add support for MangaDex for proper renaming as it has higher quality releases.

Check version <IP_ADDRESS> please.

@1271 I will check this out, I have been out sick for a little bit but I will check over the weekend and post the results here.

Do not hurry. Thanks for your work.
I hope you'll get better soon!

I close it because there is no feedback from you.
If you have any questions, click the reopen button below.


Setup up Vercel deployment for development

Setup Vercel deployment to set up a development environment. This will allow us to setup preview branches.

Complete


v560tne-v0.9.1-rc3-testing-fixes

fix usb-hid-and-msc-support tests missing skip
if tests in firmware not supported

@mkopec rebased

CI checks are failing though :(


Invalid suggestion maxSurge found in values.yaml

Describe the bug
There is a comment in the charts/values.yaml file on line 77 stating that maxSurge is an applicable setting for within the updateStrategy field. You cannot use the maxSurge option on a daemonset pod despite what the comment states.
How to reproduce it
There is nothing to reproduce for this bug, it is just a small change to a comment. However, if you try to use the maxSurge option within a daemonset pod it will not work.
Expected behaviour
Line 77 should not include any reference to the maxSurge option when working with a daemonset pod.
Screenshots

Opened a PR to fix this issue:
https://github.com/falcosecurity/charts/pull/264


Goimports doesn't work in GoSublime anymore.

I whenever installed Sublime Text on a new computer I followed this tutorial and Goimports worked automatically in GoSublime. But the last time I installed it, it's not working anymore.

If you use on Windows, there is something wrong with goimports.
Fix %GOPATH%/src/golang.org/x/tools/imports/fix.go
--- a/fix.go
+++ b/fix.go
@@ -254,10 +254,12 @@ func fixImports(fset *token.FileSet, f *ast.File, filename string) (added []stri
        results := make(chan result)
        for pkgName, symbols := range refs {
                go func(pkgName string, symbols map[string]bool) {
-                       sibling := packageInfo.Imports[pkgName]
-                       if sibling.Path != "" {
-                               results <- result{ipath: sibling.Path, name: sibling.Alias}
-                               return
+                       if packageInfo != nil {
+                               sibling := packageInfo.Imports[pkgName]
+                               if sibling.Path != "" {
+                                       results <- result{ipath: sibling.Path, name: sibling.Alias}
+                                       return
+                               }
                        }
                        ipath, rename, err := findImport(pkgName, symbols, filename)
                        r := result{ipath: ipath, err: err}

Then reinstall goimports
go install golang.org/x/tools/cmd/goimports

Thank You @nasitra! It worked for me.
Did you push this change to the GoSublime?

The change merged into 'golang/tools', not GoSublime.
https://github.com/golang/tools/commit/6e57528ade4c045edb91dac8af1c4a3ab30fa738
Now, we don't need to change the code locally.
You can get the latest goimports program and update it.

go get -u golang.org/x/tools/cmd/goimports


[Remote Migration] Changes for Primary Relocation during migration

Description
Allows relocation from docrep primary to remote primary and remote primary to remote primary .
This also seeds remote store while moving from docrep to primary .
Related Issues
Resolves  https://github.com/opensearch-project/OpenSearch/issues/12689

Check List

[x] New functionality includes testing.

[x] All tests pass

[x] New functionality has been documented.

[x] New functionality has javadoc added

[x] Failing checks are inspected and point to the corresponding known issue(s) (See: Troubleshooting Failing Builds)
[x] Commits are signed per the DCO using --signoff
[ ] ~Commit changes are listed out in CHANGELOG.md file (See: Changelog)~
[ ] ~Public documentation issue/PR created~

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

Do we need changes behind a Feature flag?

The mixed mode is already behind a feature flag . So by virtue of that most of the risky code is already under feature flag .

> Task :server:test

Tests with failures:
 - org.opensearch.transport.RemoteClusterClientTests.testConnectAndExecuteRequest

This test passes locally though and is unrelated to the change. Going to retry again .

Third time unlucky :-(
> Task :server:test

Tests with failures:
 - org.opensearch.transport.RemoteClusterClientTests.testConnectAndExecuteRequest

Flaky test is discussed here: https://github.com/opensearch-project/OpenSearch/issues/12338 and not related to changes in this PR.