regression in handling of circular references

The attached document has a regression in handling of circular references.
As an example it complains about infinite circular reference detected: results: stats -> results -> results [20266:7] | stats -> results -> results but this circular reference doesn't actually exists, results doesn't link to itself at all.
So it seems to be erroneously marking things as circular references that aren't
Here is the list of errors:
ERROR   validation error: [line 20266] resolving-references - infinite circular reference detected: results: stats -> results -> results [20266:7] | stats -> results -> results
ERROR   validation error: [line 20266] resolving-references - infinite circular reference detected: #/components/schemas/results: stats -> results -> results [20266:7] | stats -> results -> results
ERROR   validation error: [line 20266] resolving-references - infinite circular reference detected: results: stats -> results -> results [20266:7] | stats -> results -> results
ERROR   validation error: [line 22794] resolving-references - infinite circular reference detected: realtime_measurements: realtime -> realtime_entry -> realtime_measurements -> object_size_1g [22794:7] | realtime -> realtime_entry -> realtime_measurements -> object_size_1g
ERROR   validation error: [line 22794] resolving-references - infinite circular reference detected: #/components/schemas/realtime_measurements: realtime -> realtime_entry -> realtime_measurements -> object_size_1g [22794:7] | realtime -> realtime_entry -> realtime_measurements -> object_size_1g
ERROR   validation error: [line 22794] resolving-references - infinite circular reference detected: realtime_measurements: realtime -> realtime_entry -> realtime_measurements -> object_size_1g [22794:7] | realtime -> realtime_entry -> realtime_measurements -> object_size_1g

openapi.zip
These errors weren't showing in vacuum v0.4.3 the previous version we were using

does this show up in libopenapi also?

good question I don't know, our code bails out before this gets to the point we are interacting with the libopenapi model

https://github.com/pb33f/libopenapi/blob/main/index/resolver.go#L446 Is the issue, the hard limit of 100 levels deep of recursion, it too limited for this spec, so it throws up false positives, thinking they are circles, when really they are just very, very deeply nested.

This was fixed with the release v0.14


Refactored the contibutors section

Refactored te contributors section:

Use divs instead of lists
Rearranged the section to be grid based

Instead of all the contributors appearing one below the another, they are now shown as a responsive grid

Merged, @rajmayank! Thank you so much for working on this. 😄 Feel free to add yourself to the list of Contributors! ✨


Add activate account button to the end of market creation if user hasn't done this

https://www.figma.com/file/IpIAYVQPeQfuT5TTUboQpo4S/Market-creation?node-id=4206%3A138199

added - closing


localhost address stdout has additional dot (.) in it.

When running trunk serve The addresses the server is listening on are printed to stdout. Most are in dotted decimal notation, e.g. http://<IP_ADDRESS>:2600/, which are printed correctly, however localhost is printed as http://localhost.:2600/ with an additional trailing dot before the port. [code]
Is this intentional to force proxying?

Moved to discussion #893 .


[IDEA/REQUEST] :  Make default bold font more distinguished.

Is your feature request related to a problem? Please describe.
It's hard to distinguish between bold font and normal font in dark mode. It will be great if the default bold font can be made more bold so that it can be clearly seen as bold
Describe the solution you'd like
A clear and concise description of what you want to happen.
It will be great if the default bold font can be made more bold so that it can be clearly seen as bold
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
We can change the font in the style settings as an alternative.
Additional context
Add any other context or screenshots about the feature request here.
It's a low-priority request.

The issue was from my side. With default font setting in Style setting  plugin ('IBM Plex Sans") it's working fine. I was using "iA Writer Quattro V" font. Closing the issue.


code for source only experiments

Thanks for sharing the code. I'm wondering would you like to share the code for reproducing the source only results?

Hi, thanks for interests of our paper. Sure. I will upload it by the end of today or tmr.

Hi, the source-only code is uploaded, please let me know if you might need further information. Thanks.


Support Portainer Agents

Based on Inside a Swarm cluster

I checked out this PR to my machine but cannot merge because when I try to login Portainer shows me an error: "dial unix /var/run/docker.sock: connect: no such file or directory". Is it working on your machine (without the Traefik part)?

Did you delete the contents of the 'portainer' volume before re-executing? The portainer only starts the configuration if the '/ data' folder is empty. It ran normally here!

This reported error would happen if it were attempting to use the old configuration, since the volume '/var/run/docker.sock' has not mapped.

Great! It worked after removing previous volume. Thanks.


last: 1592 -> 1607

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/project/last/versions.
meta.description for last is: Genomic sequence aligner
meta.homepage for last is: https://gitlab.com/mcfrith/last
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found 1595 with grep in /nix/store/r4qilmk1xz93c2hwmibqr70igf7zvg5s-last-1595
found 1595 in filename of file in /nix/store/r4qilmk1xz93c2hwmibqr70igf7zvg5s-last-1595

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3 total rebuild path(s)

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nix-store -r /nix/store/r4qilmk1xz93c2hwmibqr70igf7zvg5s-last-1595 \
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  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

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Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/project/last/versions.
meta.description for last is: Genomic sequence aligner
meta.homepage for last is: https://gitlab.com/mcfrith/last
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built on NixOS
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found 1607 with grep in /nix/store/irjd9a1w9qxzh29axsz9v2bdgch56kn8-last-1607
found 1607 in filename of file in /nix/store/irjd9a1w9qxzh29axsz9v2bdgch56kn8-last-1607

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First fifty rebuilds by attrpath

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Either download from Cachix:
nix-store -r /nix/store/irjd9a1w9qxzh29axsz9v2bdgch56kn8-last-1607 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
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nix-build -A last https://github.com/r-ryantm/nixpkgs/archive/bbc3d88974b5afd99362c652fd2e58fb0d8949b4.tar.gz

Or:
nix build github:r-ryantm/nixpkgs/bbc3d88974b5afd99362c652fd2e58fb0d8949b4#last

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/irjd9a1w9qxzh29axsz9v2bdgch56kn8-last-1607
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fix: Fixes namespace on CreateSessionResponse

Description

Updates namespace on CreateSessionResponse to BasisTheory.net.Sessions.Responses

Testing required outside of automated testing?

[x] Not Applicable

Screenshots (if appropriate):

[x] Not Applicable

Rollback / Rollforward Procedure

[x] Roll Forward
[ ] Roll Back

Reviewer Checklist

[ ] Description of Change
[ ] Description of outside testing if applicable.
[ ] Description of Roll Forward / Backward Procedure
[ ] Documentation updated for Change

:tada: This PR is included in version 1.45.1 :tada:
The release is available on:

v1.45.1
GitHub release

Your semantic-release bot :package::rocket:


Write a GO program to find gcd of two numbers by recursion

Description
Write a GO program to find gcd of two numbers by recursion
GCD (Greatest Common Divisor) of two numbers is the largest number that divides both of them. A simple way to find GCD is to factorize both numbers and multiply common factors.
Input  : 12 18
Output : 6

How to contribute

Save the solution in find_gcd_of_two_numbers_by_recursion.go file
Add find_gcd_of_two_numbers_by_recursion.go file in program/find-gcd-of-two-numbers-by-recursion folder

!assign


Use os-package signals rather than syscall

Removes a direct dependency that can be platform-dependent in favor of the os abstraction for the same signal types.
Signed-off-by: Michael Smith<EMAIL_ADDRESS>

Oh, Kill isn't the same as SIGTERM. Nevermind.


Add support for AW 15R2 [Comes under Echo series 13R2, 17R3]

Describe the bug
Didn't detect it as supported device eventhough it uses same lighting as 13R2 and 17R3. Also had to copy LightFX.dll to root folder for alienfx-prober 26[number of zones] to detect the lighting zones properly.
To Reproduce
Steps to reproduce the behavior:

Unusual delay while detecting the zones via prober in cmdline
Sometimes the color changes correctly and sometimes it doesn't
3.Attached a screenie with device pid, api version and vid.

Expected behavior
A clear and concise description of what you expected to happen.
Screenshots
If applicable, add screenshots to help explain your problem.

Desktop (please complete the following information):

OS: Windows 10 21H2
Browser: Edge 96.x, Firefox 95.x

Additional context
None

Ok, let's check...

Probe does not require LightFX.dll. But it can scan names from it if original Dell's one available. So it's useless to copy my emulator before names defined (it will have 0 lights).
Yes, some pins not connected to the lights. In probe, just press "Enter" to skip this, you don't need to have all 28. Also, you can press CTRL+C to stop probe if all lights defined.
Indicator lights (hdd, Wi-Fi, capslock) can be only visible if active - so keep your Wi-Fi connected and capslock on to detect it.
Yes, i see you have the same v2 protocol like mine old 13R2. But light mappings can vary from model to model.
After setting light names, switch to "Color" tab and define default color for it - otherwise it will stay at initial color.
What's wrong with colors? Can you, please, be a bit more specific?

PS: In fact, probe is for bulk set from command line, in case you don't want to use GUI. I recommend use alienfx-gui to define lights instead.
PPS: Most probably, fan control will not work for your gear, even if you can enable it. You can help me to implement it later on, but it's tricky for old systems.

Ok, let's check...
1. Probe does not require LightFX.dll. But it can scan names from it if original Dell's one available. So it's useless to copy my emulator before names defined (it will have 0 lights).

2. Yes, some pins not connected to the lights. In probe, just press "Enter" to skip this, you don't need to have all 28. Also, you can press CTRL+C to stop probe if all lights defined.

3. Indicator lights (hdd, Wi-Fi, capslock) can be only visible if active - so keep your Wi-Fi connected and capslock on to detect it.

4. Yes, i see you have the same v2 protocol like mine old 13R2. But light mappings can vary from model to model.

5. After setting light names, switch to "Color" tab and define default color for it - otherwise it will stay at initial color.

6. What's wrong with colors? Can you, please, be a bit more specific?

PS: In fact, probe is for bulk set from command line, in case you don't want to use GUI. I recommend use alienfx-gui to define lights instead. PPS: Most probably, fan control will not work for your gear, even if you can enable it. You can help me to implement it later on, but it's tricky for old systems.

Thanks.
I think I have found the issue with color not changing when I have assigned multiple color morphs and timings along with events due to older AlienFX SDK which does not allow w/o crashing the app. I can set all zones to single color w/o any issue.
So whenever I try to change the status LED and power LED the alienfx simply doesn't apply the changes. I think AFX SDK 2.7 redist dll is too old. I tried replacing it with AWCC 4.5.19 but it didn't work. Too bad Dell has locked out the SDK.
Also I am able to adjust the fans but its buggy due to EC and functions similarly to HWINFO fan control.
Even seeing better battery life with light enabled w/o AWCC.
I did complete uninstall and reinstall and completely replaced it with alienfx-tools since its lighter and efficient. Now no more waiting or 10 mins for AWCC splash screen.

Hmm.... my tools doesn't need any DSK DLL, it works at direct hardware level. However, i publish my own LightFX.DLL EMULATOR - so you can eliminate AWCC completely, if you wish. But older version doesn't install the service, so just quit it is enough.
Yes, you need to choose - hardware effects OR software effects (monitoring, ambient, haptics). It can't work at the same time.
Fan control didn't work because your gear have other EC mapping - i only support 13R2 between old models now. But my app detected you have an old Alienware system, so it's trying to enable it anyway. It just doesn't work. As i said, i can add support for your system as well, but it will require some effort from you as well for helping me to define mappings and other ACPI data.
Uff... There are many questions from the beginner, so i plan to open another WIKI page about "how to start".
Anyway, i glad you configure things out, feel free to ask questions if you have.

I don't think hardware effects, ambients and haptics are supported on Echo series. Software effects is enabled. Due to old AFX SDK its quite buggy.
Thanks.

it's supported into my tools.
You v2 chip have 4-bit per color (BTW you can correct white point for more natural white), hardware Pulse, Morph, and it's combinations.
Software effects are supported at any API version, but consume some CPU (not so much).

Hmm but that color correction still has slight pink/blue hues when applying to all zones so I went with Light Blue almost similar to MBP or Surface keyboard light.
Couldn't get SW effects to apply correctly for power or status zones. Whenever I apply them few zones get applied to pink or different color not chosen and starts to flicker.
One thing I forgot to mention is, I am able to get the fan to work correctly based on hotspot/sensors from EC esp. DRAM, PCH, GPU, CPU etc and was also able to adjust fan graph. Only issue is if I want to revert anything I need to Select Power Limit to Level 1 otherwise the fans keep spinning until PC is restarted or shut down.

White point: Yes. it's not always possible to set clear white - as i said, your system only have 4-bit (16 grades) per color, so mixing is hard. I can do it correctly at mine 13R2 by decreasing red. And yes, keyboard zones mix each other, so it's a bit tricky.
SW effects: looks strange for me. First, i don't use Dell SDK, so it completely doesn't matter did it present or not. Power button can be tricky (did you mark it as a power button?), but indicator lights should be the same as others (the only difference it doesn't disabled then other lights off). Power off lights should be set upon exit/sleep/shutdown/hibernate to default settings in Color tab. But sometimes (for long power off) the system reset the chip to factory defaults. There is another way to set default lights, but it took 3-5 seconds and provide the same result.
Fans: Well... I wonder it works - it should not. Can i see your ACPI BIOS dump?
Power modes is tricky. First, i store the power mode you have at start of the application, and then set it back at exit. Seems like it doesn't work for your gear. As a result, it stays at Manual mode all the time. Die to the fact your system have direct fan control (RPMs instead of boost at newer systems), fans stuck at last RPMs defined in app. Until reboot or system will be really hot (emergency mode will be initiated in this case). We can try to disable manual mode if it is possible into your BIOS.

Ok... Check the latest release. What important for you:

Now you can switch fan mode using ALT+CTRL+0..1 (0 manual, 1 auto) then app running.
Application forced to switch to Auto mode at quit/shutdown for your gear.

Have installed the latest release; will test the hotkey for fan control.
The chip is faulty or broken with 3rd party. I had different colors being applied by games and they won't switch/restore to custom colors. I'm not fussed with custom colors working and all set all LEDs to white but some zones apply Pink Left Keyboard, Alienhead logo is orange.

Ok, let's check it.
First, there is no difference between AWCC and my tools - both share the same hardware interface, so results should be the same.
But my tools have wider possibilities, so it can interfere sometimes.
For your case, please check 3 things:

Is light defined in Device and set to white at Color tab? (just for sure)
Disable software effects (set it to "off" into top-left dropdown into application window).
Check groups - they have priority above single light. Try to remove light from group(s).

In general, you can use "Info" button at Color tab to estimate final light color (and how it generated).
If it still has the wrong color, i will need to check your settings - please export registry tree from HKCU/SOFTWARE/Alienfx_SDK and HKCU/SOFTWARE/Alienfxgui and send it to me (or attach here).
PS: Pink is possible as some diodes can have different specter (and v2 always mix a bit more red), but yellow... This means NO red in light at all. Is both of them have correct colors into AWCC?
PPS: I have a hardware issue with tron lights at mine 13R2 before, but i lost blue (in fact, it just becomes dark) for all tron lights. This was visible in any software.

Also, what about games? Do you use mine LightFX or Dell one?

afx_regfiles.zip
@T-Troll I don't use the LightFX library in games/apps that supports AFX. With AWCC I had to disallow it and some light combos flashing caused severe headaches for me.
Have attached the regfiles requested.
My Right Tron light is off since it won't display white.

Yes, i see.
Setting looks correct, effects off, all lights to white (but it can be not white for this 4-bit lights).
So... One keyboard zone can be a bit red die to this. Try to switch to "Devices", press "Test White" to switch all lights to white, then play with white point (just decrease red one) until it will be more white. In fact, it's for this, for my 13R2 is 176-255-255 for clear white.
But maybe in your case, i need per-light white point.... I'll think about it.
Is right tron have the same non-white into AWCC? As i said, i have this before, then have broken cable to screen. And, by the way, lost blue as well (just like you). It's easy to check - set it to red, green, blue (basic) and check brightness - if blue is darker -this is like this. Check cables and replace.
PS: If you just require basic colors, you can disable "Gamma correction" in settings - it makes them close to the screen colors, but brightness curve modified.

Yes, i see. Setting looks correct, effects off, all lights to white (but it can be not white for this 4-bit lights). So... One keyboard zone can be a bit red die to this. Try to switch to "Devices", press "Test White" to switch all lights to white, then play with white point (just decrease red one) until it will be more white. In fact, it's for this, for my 13R2 is 176-255-255 for clear white.
But maybe in your case, i need per-light white point.... I'll think about it.
Is right tron have the same non-white into AWCC? As i said, i have this before, then have broken cable to screen. And, by the way, lost blue as well (just like you). It's easy to check - set it to red, green, blue (basic) and check brightness - if blue is darker -this is like this. Check cables and replace.
PS: If you just require basic colors, you can disable "Gamma correction" in settings - it makes them close to the screen colors, but brightness curve modified.
Yeah even my macro cable was broken when I was testing the new oem battery and the system was very hot and after touching the cable which was brittle and instantly broke off.
I will try that RGB values.


Add git hash to footer for easy version checking

not a bad suggestion.

thanks! is on my todo list for when I have time


Help! SaaS Accelerator Issue: 500 Error on Admin Site

After deploying your Marketplace SaaS Accelerator, I changed settings on the Admin site for sending email notifications and added SMTP configuration. However now I'm getting a 500 error message when loading the application config page on the admin site (screenshot below). I thought maybe I fat fingered something, so I connected to the SQL table and reverted the settings in those rows back to NULL and restarted the App Service, but same results.
Any ideas? How can I go about troubleshooting this? Thanks in advance!

Hi @mattsoseman - can you try setting them to empty strings from db. This issue is fixed and will be available in the new release of SaaS accelerator. #647#633

Hi @mattsoseman - can you try setting them to empty strings from db. This issue is fixed and will be available in the new release of SaaS accelerator. #647 #633

That fixed it, thanks so much Santhosh!

Glad its fixed, @mattsoseman. Closing this for now, please let us know if you have any other questions.


Question on Custom Shaders:

What is your question?
I have been tweaking with OpenFL for a while now in regards to Custom Shaders, and all seems to work really well when I put the shader on camGame via Playstate.. However, if I were to put it on the camHUB: although the camHUB does fortunately get the shader effect, everything in the background goes completely dark.. I have tried multiple solutions but none seem to work for me, is this a common issue or am I making a very simple mistake? I truly feel like this is an issue on my end rather than a bug with the source.
With that big wall of text out of the way, I do fortunately have an example of the issue (with an example of the .frag file:

We managed to get it to work, thanks anyways.


Add word_model_path to parliament corpora

In the first instance, this PR is intended to activate the Irish word models, but it also prepares addition of word models for Canada, Denmark and Norway.

NB: as I don't want to deploy changes from #1484 just yet, I will also make a hotfix branch of this, rebased on main.


Unable to find via Package Control

I'm not sure if this is the right place, but I am unable to install SublimeLinter-pylint via Package Control in Sublime Text 3. This is weird considering it is located here: https://packagecontrol.io/packages/SublimeLinter-pylint
This is all that I am seeing.

Any help would be appreciated.

Are you sure it's not already installed ?

Let's just say this was a little embarrassing. It's been a long day.

😁


A few questions on running FLAML distributedly via Ray on compute clusters in AzureML

Hi @sonichi:
My team are running FLAML distributedly using Ray on compute clusters in AzureML. We have a few questions since we've never used FLAML in this environment before and hope you could provide some insights.

With this setting, what is the best way to log and register the optimal model returned of each learner in AzureML using mlflow? Shall we simply do mlflow.sklearn.log_model(automl.best_model_for_estimator('LearnerA'), "BestModelLearnerA") and then mlflow.register_model(model_uri=f"{run.info.artifact_uri}/LearnerA", name='flaml-LearnerA') ?

Where is the log file and how to change the directory for it?

Thank you!

It looks good to me. @ruizhuanguw @prithvikannan @mshtelma what do you think?
How did you submit the AzureML job? When you open an AzureML experiment, usually there is a tab

under which you will find folders in the left panel. There is a folder named "outputs" and you can output in a log file there.

For example, you can run automl.fit(log_file_name="outputs/your_log_file.log") in an AzureML job.

I did not tried registering model using mlflow before. But it looks right according to the Azure ML doc
second @sonichi's suggestion.

@sonichi agreed, that mlflow snippet should work. @flippercy let me know if you have any issues.

@prithvikannan Do the following codes make sense?
import mlflow
ray_on_aml = Ray_On_AML()
ray = ray_on_aml.getRay()
mlflow.set_tracking_uri(ws.get_mlflow_tracking_uri())
automl.fit(X_train = data_dev_balanced_B_X, y_train = data_dev_balanced_B_y,  sample_weight=data_dev_balanced_B_w,
X_val = data_val_balanced_B_X, y_val = data_val_balanced_B_y, sample_weight_val=data_val_balanced_B_w, **settings)
mlflow.sklearn.log_model(automl, "automl")
mlflow.sklearn.log_model(automl.best_model_for_estimator('MylightGBM'), "MylightGBM")
mlflow.sklearn.log_model(automl.best_model_for_estimator('MyXgboost'), "MyXgboost")
mlflow.register_model(model_uri=f"{run.info.artifact_uri}/MylightGBM", name='flaml-distributed-MylightGBM')
mlflow.register_model(model_uri=f"{run.info.artifact_uri}/MyXgboost", name='flaml-distributed-MyXgboost')
Thank you.

@sonichi, @prithvikannan:
Thank you very much for the reply. A few more questions:

Usually we use a bunch of customized learners for FLAML. It seems that if we only use one learner, no matter what it is, the automl process can be done distributedly and the model can be registered. However, if we use more than one learner such as:

"estimator_list": ['LearnerA', 'LearnerB'],
The automl still can finish with no issue; when logging and registering the models, there is always a weird error message:

Any idea on what it means? Not sure which parameter it refers to.

If we only use one learner, although the model can be built, logged and registered successfully, there is always an error at the end of the process stating that the pkl file already exists.

"message": "User program failed with Exception: UserError: Resource Conflict: ArtifactId ExperimentRun/dcid.distribute-automl-v2_1666366028_5f2255a6/automl/model.pkl already exists.",
Any idea on what causes this?
Appreciate your help.

Re: the error with param length, we have bounded params to be <255 bytes. My guess is that https://github.com/microsoft/FLAML/blob/58227a976bdbf91617a639831f1ed247bcc41538/flaml/automl.py#L3113 is the line that causes the issue, since this will log all of the automl params in a dict. @flippercy can you share the stack trace? @sonichi, since we are already logging params individually, can we remove this line?
Re: artifact logging, my guess is this is some sort of race condition. I am not familiar with Ray-FLAML interaction, so I'm not of much use here.

@prithvikannan @sonichi
Here is the stack trace:
Warnings:
AzureMLCompute job failed.
JobFailed: Submitted script failed with a non-zero exit code; see the driver log file for details.
Reason: Job failed with non-zero exit Code
Show less
ActivityFailedException                   Traceback (most recent call last)
Input In [9], in <cell line: 19>()
16 run = exp.submit(config)
18 print(run.get_portal_url())  # link to ml.azure.com
---> 19 run.wait_for_completion(show_output=True)
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/core/run.py:843, in Run.wait_for_completion(self, show_output, wait_post_processing, raise_on_error)
841 if show_output:
842     try:
--> 843         self._stream_run_output(
844             file_handle=sys.stdout,
845             wait_post_processing=wait_post_processing,
846             raise_on_error=raise_on_error)
847         return self.get_details()
848     except KeyboardInterrupt:
File /anaconda/envs/azureml_py38/lib/python3.8/site-packages/azureml/core/run.py:1096, in Run._stream_run_output(self, file_handle, wait_post_processing, raise_on_error)
1094         file_handle.write("\n")
1095     else:
-> 1096         raise ActivityFailedException(error_details=json.dumps(error, indent=4))
1098 file_handle.write("\n")
1099 file_handle.flush()
ActivityFailedException: ActivityFailedException:
Message: Activity Failed:
{
"error": {
"code": "UserError",
"message": "User program failed with RestException: INVALID_PARAMETER_VALUE: Response: {'Error': {'Code': 'ValidationError', 'Severity': None, 'Message': 'No more than 255 characters per params Value. Request contains 1 of greater length.', 'MessageFormat': None, 'MessageParameters': None, 'ReferenceCode': None, 'DetailsUri': None, 'Target': None, 'Details': [], 'InnerError': None, 'DebugInfo': None, 'AdditionalInfo': None}, 'Correlation': {'operation': '9f1081f11e8cf0a21df39f7f0a5b4b7a', 'request': '34711cbb5b6fc9b2'}, 'Environment': 'southcentralus', 'Location': 'southcentralus', 'Time': '2022-10-21T20:20:14.3227161+00:00', 'ComponentName': 'mlflow', 'error_code': 'INVALID_PARAMETER_VALUE'}",
"messageParameters": {},
"detailsUri": "https://aka.ms/azureml-run-troubleshooting",
"details": []
},
"time": "0001-01-01T00:00:00.000Z"
}
InnerException None
ErrorResponse
{
"error": {
"message": "Activity Failed:\n{\n    "error": {\n        "code": "UserError",\n        "message": "User program failed with RestException: INVALID_PARAMETER_VALUE: Response: {'Error': {'Code': 'ValidationError', 'Severity': None, 'Message': 'No more than 255 characters per params Value. Request contains 1 of greater length.', 'MessageFormat': None, 'MessageParameters': None, 'ReferenceCode': None, 'DetailsUri': None, 'Target': None, 'Details': [], 'InnerError': None, 'DebugInfo': None, 'AdditionalInfo': None}, 'Correlation': {'operation': '9f1081f11e8cf0a21df39f7f0a5b4b7a', 'request': '34711cbb5b6fc9b2'}, 'Environment': 'southcentralus', 'Location': 'southcentralus', 'Time': '2022-10-21T20:20:14.3227161+00:00', 'ComponentName': 'mlflow', 'error_code': 'INVALID_PARAMETER_VALUE'}",\n        "messageParameters": {},\n        "detailsUri": "https://aka.ms/azureml-run-troubleshooting\",\n        "details": []\n    },\n    "time": "0001-01-01T00:00:00.000Z"\n}"
}
}

Re: the error with param length, we have bounded params to be <255 bytes. My guess is that
https://github.com/microsoft/FLAML/blob/58227a976bdbf91617a639831f1ed247bcc41538/flaml/automl.py#L3113
is the line that causes the issue, since this will log all of the automl params in a dict. @flippercy can you share the stack trace? @sonichi, since we are already logging params individually, can we remove this line?

I doubt that's the cause because (1) there is no error when one learner is used, and (2) the error happens after automl.fit(). It happens when logging the model.

Re: artifact logging, my guess is this is some sort of race condition. I am not familiar with Ray-FLAML interaction, so I'm not of much use here.

Does this error happen only when ray is used? @flippercy which line causes the error?

@flippercy Another question: Does the logging and registering code work for non-flaml models?

@sonichi , @prithvikannan:

The error happens when the models returned by FLAML were logged.
It is unrelated with any specific learner. I got the same error with the default learners in FLAML.
The logging and registering code work for both non-flaml models and flaml models built without Ray.

The codes with issues are:
ray_on_aml = Ray_On_AML()
ray = ray_on_aml.getRay()
mlflow.set_tracking_uri(ws.get_mlflow_tracking_uri())
with mlflow.start_run() as run:
automl.fit(X_train = data_dev_balanced_B_X, y_train = data_dev_balanced_B_y,  sample_weight=data_dev_balanced_B_w,
X_val = data_val_balanced_B_X, y_val = data_val_balanced_B_y, sample_weight_val=data_val_balanced_B_w, **settings)
mlflow.sklearn.log_model(automl.best_model_for_estimator('lgbm'), "lgbm-flaml")
mlflow.sklearn.log_model(automl.best_model_for_estimator('xgboost'), "xgboost-flaml")
mlflow.sklearn.log_model(automl.best_model_for_estimator('catboost'), "catboost-flaml")
mlflow.sklearn.log_model(automl.best_model_for_estimator('rf'), "rf-flaml")
mlflow.sklearn.log_model(automl.best_model_for_estimator('extra_tree'), "extra_tree-flaml")

mlflow.end_run()

@flippercy It would be very helpful if you can provide a minimal reproducible example.

@sonichi @ruizhuanguw @prithvikannan Thank you for the reply guys! I am off today and will give you some updates tomorrow.

@sonichi , @ruizhuanguw and @prithvikannan:
I did a few tests with both the default learners and customized learners; the result is confusing:

If I use customized learners without Ray on a VM, there is no issue at all with logging and registering codes.
If I use customized learners with Ray on a compute cluster, I got the error aforementioned and the models cannot be logged.
If I use default learners with Ray on a compute cluster, I still got the error aforementioned but the models can be logged and registered successfully.
If I use non-flaml models such as lightgbm, there is no issue with logging and registering codes.

I can confirm that the problem happens when trying to log models using mlflow.sklearn.log_model. My customized learners are all like below:
class MyMonotonicXGBGBTreeClassifier(BaseEstimator):
def __init__(self, task = 'binary:logistic', n_jobs = num_cores, **params):

    super().__init__(task, **params)

    self.estimator_class = XGBClassifier

    # convert to int for integer hyperparameters
    self.params = {
        'n_jobs': params['n_jobs'] if 'n_jobs' in params else num_cores,
        'booster': params['booster'] if 'booster' in params else 'gbtree',
        'use_label_encoder': params['use_label_encoder'] if 'use_label_encoder' in params else False,
        'eval_metric': params['eval_metric'] if 'eval_metric' in params else 'auc',
        'learning_rate': params['learning_rate'],
        'gamma': params['gamma'],
        'max_depth': int(params['max_depth']),
        'min_child_weight': int(params['min_child_weight']),
        'subsample': params['subsample'],
        'colsample_bylevel':params['colsample_bylevel'],
        'n_estimators':int(params['n_estimators']),
        'reg_lambda': params['reg_lambda'],
        'reg_alpha': params['reg_alpha'],
        'random_state': params['random_state'] if 'random_state' in params else randomseed,
        "monotone_constraints": params['monotone_constraints'] if 'monotone_constraints' in params else monotone,

   }

@classmethod
def search_space(cls, data_size, task):

    space = {
    'max_depth': {'domain': tune.uniform(lower=4, upper=8), 'init_value': 8, 'low_cost_init_value': 8},
    'n_estimators': {'domain': tune.uniform(lower = 50, upper = 500), 'init_value': 200, 'low_cost_init_value': 200},
    'min_child_weight': {'domain': tune.loguniform(lower = 0.00001, upper = 10), 'init_value': 0.001, 'low_cost_init_value': 0.001},
    'subsample': {'domain': tune.uniform(lower = 0.7, upper = 1), 'init_value': 0.7, 'low_cost_init_value': 0.7},
    'colsample_bylevel': {'domain': tune.uniform(lower = 0.6, upper = 1), 'init_value': 0.8, 'low_cost_init_value': 0.8},
    'learning_rate': {'domain': tune.loguniform(lower = 0.00001, upper = 1), 'init_value': 0.01, 'low_cost_init_value': 0.01},
    'gamma': {'domain': tune.loguniform(lower = 0.000000000001, upper = 0.001), 'init_value': 0.00001, 'low_cost_init_value': 0.00001},
    'reg_lambda': {'domain': tune.loguniform(lower = 0.0001, upper = 2), 'init_value': 1, 'low_cost_init_value': 1},
    'reg_alpha': {'domain': tune.loguniform(lower = 0.000000000001, upper = 1), 'init_value': 0.000000000001, 'low_cost_init_value': 0.000000000001},
    }
    return space

automl.add_learner(learner_name = 'MyXgboost', learner_class = MyMonotonicXGBGBTreeClassifier)

@sonichi , @ruizhuanguw and @prithvikannan:
I did a few tests with both the default learners and customized learners; the result is confusing:

If I use customized learners without Ray on a VM, there is no issue at all with logging and registering codes.
If I use customized learners with Ray on a compute cluster, I got the error aforementioned and the models cannot be logged.
If I use default learners with Ray on a compute cluster, I still got the error aforementioned but the models can be logged and registered successfully.
If I use non-flaml models such as lightgbm, there is no issue with logging and registering codes.

I can confirm that the problem happens when trying to log models using mlflow.sklearn.log_model. My customized learners are all like below:
class MyMonotonicXGBGBTreeClassifier(BaseEstimator):
def __init__(self, task = 'binary:logistic', n_jobs = num_cores, **params):

    super().__init__(task, **params)

    self.estimator_class = XGBClassifier

    # convert to int for integer hyperparameters
    self.params = {
        'n_jobs': params['n_jobs'] if 'n_jobs' in params else num_cores,
        'booster': params['booster'] if 'booster' in params else 'gbtree',
        'use_label_encoder': params['use_label_encoder'] if 'use_label_encoder' in params else False,
        'eval_metric': params['eval_metric'] if 'eval_metric' in params else 'auc',
        'learning_rate': params['learning_rate'],
        'gamma': params['gamma'],
        'max_depth': int(params['max_depth']),
        'min_child_weight': int(params['min_child_weight']),
        'subsample': params['subsample'],
        'colsample_bylevel':params['colsample_bylevel'],
        'n_estimators':int(params['n_estimators']),
        'reg_lambda': params['reg_lambda'],
        'reg_alpha': params['reg_alpha'],
        'random_state': params['random_state'] if 'random_state' in params else randomseed,
        "monotone_constraints": params['monotone_constraints'] if 'monotone_constraints' in params else monotone,

   }

@classmethod
def search_space(cls, data_size, task):

    space = {
    'max_depth': {'domain': tune.uniform(lower=4, upper=8), 'init_value': 8, 'low_cost_init_value': 8},
    'n_estimators': {'domain': tune.uniform(lower = 50, upper = 500), 'init_value': 200, 'low_cost_init_value': 200},
    'min_child_weight': {'domain': tune.loguniform(lower = 0.00001, upper = 10), 'init_value': 0.001, 'low_cost_init_value': 0.001},
    'subsample': {'domain': tune.uniform(lower = 0.7, upper = 1), 'init_value': 0.7, 'low_cost_init_value': 0.7},
    'colsample_bylevel': {'domain': tune.uniform(lower = 0.6, upper = 1), 'init_value': 0.8, 'low_cost_init_value': 0.8},
    'learning_rate': {'domain': tune.loguniform(lower = 0.00001, upper = 1), 'init_value': 0.01, 'low_cost_init_value': 0.01},
    'gamma': {'domain': tune.loguniform(lower = 0.000000000001, upper = 0.001), 'init_value': 0.00001, 'low_cost_init_value': 0.00001},
    'reg_lambda': {'domain': tune.loguniform(lower = 0.0001, upper = 2), 'init_value': 1, 'low_cost_init_value': 1},
    'reg_alpha': {'domain': tune.loguniform(lower = 0.000000000001, upper = 1), 'init_value': 0.000000000001, 'low_cost_init_value': 0.000000000001},
    }
    return space

automl.add_learner(learner_name = 'MyXgboost', learner_class = MyMonotonicXGBGBTreeClassifier)

Does **settings of AutoML.fit() contain model_history=True?

@sonichi Yes it is specified that model_history = True.
Since the behaviors of default learners and customized learners are different (although the same error returned for both, models built with default learners can be registered at least), I suspect that there is something wrong with my customized learners when used with Ray on compute clusters. Could you take a look at it, please?
Thank you.

I tried to reproduce the error but couldn't. Things work fine when I use your example custom learner. My code is:
from ray_on_aml.core import Ray_On_AML
from flaml import AutoML, tune
from flaml.model import BaseEstimator
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
import mlflow
from xgboost import XGBClassifier

data, target = load_breast_cancer(return_X_y=True, as_frame=True)
train_x, test_x, train_y, test_y = train_test_split(data, target, test_size=0.25)
num_cores = 1
randomseed = 42
monotone = None

class MyMonotonicXGBGBTreeClassifier(BaseEstimator):

    def __init__(self, task = 'binary:logistic', n_jobs = num_cores, **params):

        super().__init__(task, **params)

        self.estimator_class = XGBClassifier

        # convert to int for integer hyperparameters
        self.params = {
            'n_jobs': params['n_jobs'] if 'n_jobs' in params else num_cores,
            'booster': params['booster'] if 'booster' in params else 'gbtree',
            'use_label_encoder': params['use_label_encoder'] if 'use_label_encoder' in params else False,
            'eval_metric': params['eval_metric'] if 'eval_metric' in params else 'auc',
            'learning_rate': params['learning_rate'],
            'gamma': params['gamma'],
            'max_depth': int(params['max_depth']),
            'min_child_weight': int(params['min_child_weight']),
            'subsample': params['subsample'],
            'colsample_bylevel':params['colsample_bylevel'],
            'n_estimators':int(params['n_estimators']),
            'reg_lambda': params['reg_lambda'],
            'reg_alpha': params['reg_alpha'],
            'random_state': params['random_state'] if 'random_state' in params else randomseed,
            "monotone_constraints": params['monotone_constraints'] if 'monotone_constraints' in params else monotone,
        }

    @classmethod
    def search_space(cls, data_size, task):

        space = {
            'max_depth': {'domain': tune.uniform(lower=4, upper=8), 'init_value': 8, 'low_cost_init_value': 8},
            'n_estimators': {'domain': tune.uniform(lower = 50, upper = 500), 'init_value': 200, 'low_cost_init_value': 200},
            'min_child_weight': {'domain': tune.loguniform(lower = 0.00001, upper = 10), 'init_value': 0.001, 'low_cost_init_value': 0.001},
            'subsample': {'domain': tune.uniform(lower = 0.7, upper = 1), 'init_value': 0.7, 'low_cost_init_value': 0.7},
            'colsample_bylevel': {'domain': tune.uniform(lower = 0.6, upper = 1), 'init_value': 0.8, 'low_cost_init_value': 0.8},
            'learning_rate': {'domain': tune.loguniform(lower = 0.00001, upper = 1), 'init_value': 0.01, 'low_cost_init_value': 0.01},
            'gamma': {'domain': tune.loguniform(lower = 0.000000000001, upper = 0.001), 'init_value': 0.00001, 'low_cost_init_value': 0.00001},
            'reg_lambda': {'domain': tune.loguniform(lower = 0.0001, upper = 2), 'init_value': 1, 'low_cost_init_value': 1},
            'reg_alpha': {'domain': tune.loguniform(lower = 0.000000000001, upper = 1), 'init_value': 0.000000000001, 'low_cost_init_value': 0.000000000001},
        }
        return space

def _test_ray_classification():
    # from sklearn.datasets import make_classification

    # ray.init(address="auto")
    # X, y = make_classification(1000, 10)
    automl = AutoML()
    automl.add_learner("myxgb", MyMonotonicXGBGBTreeClassifier)
    automl.fit(
        train_x, train_y, X_val=test_x, y_val=test_y, time_budget=60, metric="accuracy", task="classification", n_concurrent_trials=2,
        estimator_list=["lgbm", "myxgb"], model_history=True
    )
    print("best loss", automl.best_loss)
    print(automl.best_model_for_estimator("lgbm"))
    print(automl.best_model_for_estimator("myxgb"))
    mlflow.sklearn.log_model(automl.best_model_for_estimator("myxgb"), "MyXGB")
    mlflow.sklearn.log_model(automl.best_model_for_estimator("lgbm"), "LGBM")

if __name__ == "__main__":
    ray_on_aml = Ray_On_AML()
    ray = ray_on_aml.getRay()
    if ray:
        _test_ray_classification()

@sonichi:
Thank you very much for your help. With your codes, I've figured out that the issue is due to the following codes:
with mlflow.start_run() as run:
.......
mlflow.end_run()
If I add them to your example as:
with mlflow.start_run() as run:
automl.fit(
train_x, train_y, X_val=test_x, y_val=test_y, time_budget=60, metric="accuracy", task="classification", n_concurrent_trials=2,
estimator_list=["lgbm", "myxgb"], model_history=True
)
mlflow.end_run()
I get the same error mentioned earlier.
However, without these two lines, I do not know how to pull the uri of models in AzureML and register them. Any suggestions?

@sonichi:
Thank you very much for your help. With your codes, I've figured out that the issue is due to the following codes:
with mlflow.start_run() as run:
.......
mlflow.end_run()
If I add them to your example as:
with mlflow.start_run() as run:
automl.fit(
train_x, train_y, X_val=test_x, y_val=test_y, time_budget=60, metric="accuracy", task="classification", n_concurrent_trials=2,
estimator_list=["lgbm", "myxgb"], model_history=True
)
mlflow.end_run()
I get the same error mentioned earlier.
However, without these two lines, I do not know how to pull the uri of models in AzureML and register them. Any suggestions?

@sonichi:
Thank you very much for your help. With your codes, I've figured out that the issue is due to the following codes:
with mlflow.start_run() as run: ....... mlflow.end_run()
If I add them to your example as:
with mlflow.start_run() as run: automl.fit( train_x, train_y, X_val=test_x, y_val=test_y, time_budget=60, metric="accuracy", task="classification", n_concurrent_trials=2, estimator_list=["lgbm", "myxgb"], model_history=True ) mlflow.end_run()
I get the same error mentioned earlier.
However, without these two lines, I do not know how to pull the uri of models in AzureML and register them. Any suggestions?

mlflow.sklearn.log_model is executed out of the with clause, right? I don't think you need to add the with clause to get the uri. I'm not an expert of AzureML. If you are using AzureML sdk v2, consider https://learn.microsoft.com/en-us/azure/machine-learning/how-to-deploy-mlflow-models?tabs=fromjob%2Cmir%2Csdk#deploy-using-azure-ml-clisdk-v2

@sonichi My team managed to used other ways to pull the model uri after training and save the model. Problem solved.
Thank you very much for your help with the debugging! I've learned a lot.


An error occurred while upgrading the D455 firmware using rs-fw-update on Ubuntu 20.04 focal LTS system with hardware RK3588S

Required Info

Camera Model
D455

Firmware Version
<IP_ADDRESS>-><IP_ADDRESS>

Operating System & Version
ubuntu20.04 focal LTS

Kernel Version (Linux Only)
5.10

Platform
rk3588s

SDK Version
2.55.1 ,2.56.0.,2.56.2

Language
c++

Segment
others

Issue Description
I have a batch of D455 cameras with firmware version <IP_ADDRESS>;
I compiled SDK versions 2.55.1, 2.56.0, and 2.56.2 in rk3588s;
I upgraded the camera from <IP_ADDRESS> to <IP_ADDRESS> using the compiled rs fw update, and three of the cameras encountered the following issue (two of them were normal);

The image shows that the camera with firmware version <IP_ADDRESS> has been re-upgraded.
The image is for reproducing the error message; Specifically, after upgrading the camera from <IP_ADDRESS> to <IP_ADDRESS>, the camera entered recovery mode and could not be restored and upgraded through RS-FW-update-R. The error message is as follows:

I can only upgrade the recovery mode camera to version <IP_ADDRESS> using the realsense viewer tool（ 2.55.1 version） on Windows；
May I ask why rs-fw-update on Linux has this problem.

Hi @diplomatist  There is a Windows version of the firmware update tool called Intel.RealSense.FW.Update that can be downloaded from the 'Assets' file list on the SDK Releases page.
https://github.com/intelrealsense/librealsense/releases
So you could try that.  However, problems with updating multiple cameras have also occasionally been reported with that tool too.

One of the set of multiple cameras may go into recovery mode if it experiences an interruption during the update.  A RealSense user at https://github.com/IntelRealSense/librealsense/issues/7095#issuecomment-879995800 found that once it is in recovery mode then may take several tries of the -r recovery command before recovery works.

Hi @MartyG-RealSense ！
I used viewer or rs-fw-update on Linux to upgrade the firmware of a single D455, and almost 100% of the attempts failed. Later, I changed the connection line for testing and found that the success rate of upgrading firmware was much higher;
An additional situation needs to be explained:
These three D455s were originally connected to three RK3588s development boards;
Due to construction issues, RK3588s was connected to a 220V power supply, which caused the power supply of RK3588s to burn out;
I connected these three D455s to the Linux viewer or Windows viewer with the correct firmware and they all worked properly;
But it is not possible to upgrade using these three cables in the Linux viewer or RS-FW-update program, and it can be upgraded through the Windows viewer (not yet upgraded in FW.Uupdate.exe of Windows);
Due to objective reasons, I have many D455 devices that are unable to easily upgrade firmware on Windows;

By 'connection line', do you mean the USB cable please?  If you do, are you using the official 1 meter USB cables supplied with the cameras for the firmware update or a USB cable of your own choice?
If you are using your own cable and that cable is lengthy then it is recommendable to change to the official short 1 m cable when performing a firmware update and then change back to the other cable, though I can appreciate that this may not be practical to do in some situations, especially where you have many cameras that may also be difficult to access in person.
You could test whether the rate of success increases with having the micro-sized end of the cable inserted into the base of the D455 in one of two particular directions.  The micro-sized end of the cable is two-way insertion, and sometimes a camera will perform better when the micro-connector is inserted in a certain direction.


NavigationView TogglePaneTopPadding issue

My page xaml
<Page x:Class="WinUITestApp.MainPage"       xmlns="http://schemas.microsoft.com/winfx/2006/xaml/presentation"       xmlns:x="http://schemas.microsoft.com/winfx/2006/xaml"       xmlns:controls="using:Microsoft.UI.Xaml.Controls">     <controls:NavigationView AlwaysShowHeader="True"                              Header="Header"                              IsBackButtonVisible="Visible" /> </Page>
My code for title bar
var coreTitleBar = CoreApplication.GetCurrentView().TitleBar;    coreTitleBar.ExtendViewIntoTitleBar = true;

Change NavigationView to Windows.UI...

Thank you for reporting this issue. What you're seeing in your first screenshot is by design, and will soon be updated in the Windows.UI namespace as well. When extending into the title bar, your app content gets drawn to the top of the window, but there's still a transparent title bar component that physically overlays your app window. As a result, users won't be able to click on your (disabled in the second screenshot) back button, were it to become enabled. To improve this user interaction, we automatically move NavigationView's components (but not its background color) down from the top of the window. This way, all buttons remain interactive without additional work by the app author.


feat: restructure android-core docs

Description
This PR restructures the android-core docs to align with the new structure of the web-core docs.
Resolved issues
closes: MOB-1581
Pending sections:

Reference | Will be adding it gradually.

I also intended to review the Local User and Livestream docs as part of this task but for now we have kept them unchanged. Will do it in a separate PR later.

@palashgo thanks for fixing the typos 🙇


SB3 integration with an existing callback

SB3 integration currently uses a callback. I already have a SB3 callback in my code. How can I use both an existing and wandb callbacks at the same time?

I am trying the stable baseline 3 integration.
Stable baseline has callbacks that I am currently using in my agent training.
https://stable-baselines.readthedocs.io/en/master/guide/callbacks.html
I understand that wandb using callbacks as well.
How can they work together?

That's what I'm asking. Is it possible to call two callbacks?

Yes this was helpful thank you


[mustache] Add more text processing functions

Based on Apache commons-text & commons-lang3

f_escape_csv
f_escape_ecma_script
f_escape_html3
f_escape_html4
f_escape_java
f_escape_json
f_escape_xml10
f_escape_xml11
f_escape_xsi
f_chop
f_delete_whitespace
f_normalize_whitespace
f_reverse
f_strip
f_swapcase

Also ad a function to recursively eval templates, pairs well with f_file_read.

Released in v1.3.0 -> https://github.com/jreleaser/jreleaser/releases/tag/v1.3.0


[Bug] Loader won't work for files with an extension other than ".css" (such as ".pcss" or ".postcss")

Related PR: #17
There's no option to change the test either.

Coming across this myself, any change this will be addressed?

This also happens with .vue files that have <style lang="postcss">.
As workaround remove the lang attribute (but then syntax highlighting breaks).
Or fix it by setting the webpack config yourself:
webpackFinal(webpackConfig) {
    // Same config as what @storybook/addon-postcss produces, but for Vue <style lang="postcss"> blocks
    webpackConfig.module?.rules.push({
      test: /\.postcss$/, // Matches lang="postcss" in Vue files
      sideEffects: true,
      use: [
        require.resolve("style-loader"),
        require.resolve("css-loader"),
        require.resolve("postcss-loader"),
      ],
    });;

So please update the addon to match more extensions.

Official twitter PostCSS recommendation use .pcss extension for PostCSS based sources.
https://twitter.com/PostCSS/status/661645290622083073
This change is required to comply with official requirements.

That is a 6 year old Tweet, so I'm not sure it's relevant anymore? I believe either do not work with Storybook, correct?

What has changed in six years? postcss is still not css. The general rule is that the file format should match its content, for many reasons.
For instance it postcss has different syntax highlighting, lint rules, snippets, etc. In any case, people themselves must decide what is more convenient for them.

I think we are agreeing here as Storybook fails with .pcss or .postcss and using .css for PostCSS files isn't ideal.

Also running into this issue.

I have the same issue.


Add target param to reportback file select query to send it to slave db

What's this PR do?
send reportback item queries to the slave database
Any background context you want to provide?
Apparently each query can be treated like a unique snowflake ❄
Currently blocked by DoSomething/devops/issues/140
And my own inability to know how to make sure this actually works!
Relevant tickets
Refs #6616

@sheyd and I tested this on thor and it seems to work! merging in meow!


Assembly errors building on Mac OSX

Hello
I had to fix about 5-6 assembly errors when attempting to build on Mac OSX.  It does not appear to me these were Mac-specific considering they were straight up missing libraries in the packages.config files, for example NodaTime in Api/packages.config. Please try building from scratch.
Current master of Lean; Mac OSX 10.11.6; Xamarin Studio 6.1.2/44

This has been addressed in recent commits. Please pull down master and follow the instructions in ReadMe to put the right DLL in place.  https://github.com/QuantConnect/Lean/pull/989


⚠ Bofrost.be has degraded performance

In c79fbe1, Bofrost.be (https://www.bofrost.be) experienced degraded performance:

HTTP code: 200
Response time: 1081 ms

Resolved: Bofrost.be performance has improved in 9adcedc.


Adjust Feed Pulls

According to necessary steps as per internal recommendations.

[x] onlyAddExtraIndex  is set in auth-dev-feed.yml. It needs to be false and done as an operation for each targeted feed.
[x] Index URL needs to be selectively targeted in create_and_install.py for tox.ini

Follow-up issue filed here.


Update Readme of Jaguar Car Project

I'm always frustrated when I don't see Proper readme so ,I will update the readme in order to ease the idea for everyone to find the new project requests.
I want to update the readme file of Jaguar Car Project

@TusharKesarwani Kindly assign this to me under SSOC 2.O

@TusharKesarwani sir , please assign this to me under SSOC 2.0
it is not responsive and its UI is also not very attractive I would like to  work on it

Create a new issue with a proper explanation of the bug


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getting currentDirectory of startupProject and operating in that directo...

...ry part of #823

Can probably repeat yourself less if you introduce a pattern like this...
return Execute(
    startupProject,
    () =>
    {
        DoStuff();

        return 0;
    });

...and move the directory changing to the Execute method.

Ping!

:shipit:


Checksum verification fails for cosmosdb-emulator installation

Description
When running agent install for windows2022
I think we need to update the checksum to "DB9D5E496C5FDAE17C12C03385D2BAC973DA61C280023D9FDC9A6020220BEE41"
In the file Install-AzureCosmosDbEmulator.ps1
==> azure-arm.image: Checksum verification failed: expected D21A0476B7F3439319BE6A1060935E7C865FEFA87C47943C9A6D595137703F49, got
==> azure-arm.image: DB9D5E496C5FDAE17C12C03385D2BAC973DA61C280023D9FDC9A6020220BEE41
==> azure-arm.image: At C:\Program Files\WindowsPowerShell\Modules\ImageHelpers\InstallHelpers.ps1:919 char:9
==> azure-arm.image: +         throw "Checksum verification failed: expected $expectedHash,  ...
==> azure-arm.image: +         ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
==> azure-arm.image:     + CategoryInfo          : OperationStopped: (Checksum verifi...C9A6020220BEE41:String) [], RuntimeException
==> azure-arm.image:     + FullyQualifiedErrorId : Checksum verification failed: expected D21A0476B7F3439319BE6A1060935E7C865FEFA87C47943C9
==> azure-arm.image:    A6D595137703F49, got DB9D5E496C5FDAE17C12C03385D2BAC973DA61C280023D9FDC9A6020220BEE41
==> azure-arm.image:
Platforms affected

[X] Azure DevOps
[ ] GitHub Actions - Standard Runners
[ ] GitHub Actions - Larger Runners

Runner images affected

[ ] Ubuntu 20.04
[ ] Ubuntu 22.04
[ ] Ubuntu 24.04
[ ] macOS 12
[ ] macOS 13
[ ] macOS 13 Arm64
[ ] macOS 14
[ ] macOS 14 Arm64
[ ] Windows Server 2019
[X] Windows Server 2022

Image version and build link
windows2022
Is it regression?
no
Expected behavior
Install cosmosdb emulator
Actual behavior
==> azure-arm.image: Checksum verification failed: expected D21A0476B7F3439319BE6A1060935E7C865FEFA87C47943C9A6D595137703F49, got
==> azure-arm.image: DB9D5E496C5FDAE17C12C03385D2BAC973DA61C280023D9FDC9A6020220BEE41
==> azure-arm.image: At C:\Program Files\WindowsPowerShell\Modules\ImageHelpers\InstallHelpers.ps1:919 char:9
==> azure-arm.image: +         throw "Checksum verification failed: expected $expectedHash,  ...
==> azure-arm.image: +         ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
==> azure-arm.image:     + CategoryInfo          : OperationStopped: (Checksum verifi...C9A6020220BEE41:String) [], RuntimeException
==> azure-arm.image:     + FullyQualifiedErrorId : Checksum verification failed: expected D21A0476B7F3439319BE6A1060935E7C865FEFA87C47943C9
==> azure-arm.image:    A6D595137703F49, got DB9D5E496C5FDAE17C12C03385D2BAC973DA61C280023D9FDC9A6020220BEE41
==> azure-arm.image:
Repro steps
Run install vm image on windows 2022

Can also vouch for this we are getting the same errors for window-2022:

==> azure-arm.image: Provisioning with powershell script: C:/a/1/s/runner-images/images/windows/templates/../scripts/build/Install-AzureCosmosDbEmulator.ps1
azure-arm.image: Downloading package from https://aka.ms/cosmosdb-emulator to C:\Users\packer\AppData\Local\Temp\r05cffti.msi...
azure-arm.image: Package downloaded in 1.3 seconds
==> azure-arm.image: Checksum verification failed: expected D21A0476B7F3439319BE6A1060935E7C865FEFA87C47943C9A6D595137703F49, got
==> azure-arm.image: DB9D5E496C5FDAE17C12C03385D2BAC973DA61C280023D9FDC9A6020220BEE41
==> azure-arm.image: At C:\Program Files\WindowsPowerShell\Modules\ImageHelpers\InstallHelpers.ps1:919 char:9
==> azure-arm.image: +         throw "Checksum verification failed: expected $expectedHash,  ...
==> azure-arm.image: +         ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
==> azure-arm.image:     + CategoryInfo          : OperationStopped: (Checksum verifi...C9A6020220BEE41:String) [], RuntimeException
==> azure-arm.image:     + FullyQualifiedErrorId : Checksum verification failed: expected D21A0476B7F3439319BE6A1060935E7C865FEFA87C47943C9
==> azure-arm.image:    A6D595137703F49, got DB9D5E496C5FDAE17C12C03385D2BAC973DA61C280023D9FDC9A6020220BEE41
==> azure-arm.image:
==> azure-arm.image: Provisioning step had errors: Running the cleanup provisioner, if present...

HI @vd84 ,
Thanks for raising the issue, we're working on the issue.

@vd84  cosmosdb-emulator signature has been updated, Could you please retry by forking latest code from main branch.
Closing this issue,Thank you.


doc: ncbi datasets

Description of proposed changes
Since the transition from NCBI Virus to NCBI datasets, revised the documentation to reflect changes in how metadata and sequences are fetched from NCBI.
Feel free to propose alternative wording or descriptions.
Related issue(s)

https://github.com/nextstrain/monkeypox/commit/82ace30abd07bec140c7e14aee29a46c7bfb28a8
https://github.com/nextstrain/dengue/pull/13#pullrequestreview-1675235743

Checklist

[ ] Checks pass

Thanks @joverlee521! Updated centralized Nextstrain installation docs in https://github.com/nextstrain/docs.nextstrain.org/pull/172 and added a software requirments section. This PR is ready for review.


Add version: TabbyML.Tabby version v0.15.0

Pull request has been created with komac v2.3.0 :rocket:
Microsoft Reviewers: Open in CodeFlow

Automatic Validation ended with:

Installation failed with exit code -1978334960
2024-08-21 21:18:00.244 [FAIL] D:\a_work\1\s\external\pkg\src\AppInstallerRepositoryCore\RepositorySource.cpp(757)\WindowsPackageManager.dll!00007FFB3443C11F: (caller: 00007FFB341C8D6F) LogHr(1) tid(140c) 8A15005E     Msg:[D:\a_work\1\s\external\pkg\src\AppInstallerRepositoryCore\Rest\Schema\HttpClientHelper.cpp(30)\WindowsPackageManager.dll!00007FFB34342B08: (caller: 00007FFB343EBC20) Exception(1) tid(140c) 8A15005E ]
2024-08-21 21:18:04.496 [FAIL] D:\a_work\1\s\external\pkg\src\AppInstallerRepositoryCore\RepositorySource.cpp(757)\WindowsPackageManager.dll!00007FFB3443C11F: (caller: 00007FFB341C8D6F) LogHr(1) tid(1ee4) 8A15005E     Msg:[D:\a_work\1\s\external\pkg\src\AppInstallerRepositoryCore\Rest\Schema\HttpClientHelper.cpp(30)\WindowsPackageManager.dll!00007FFB34342B08: (caller: 00007FFB343EBC20) Exception(1) tid(1ee4) 8A15005E ]
2024-08-21 21:18:12.414 [FAIL] D:\a_work\1\s\external\pkg\src\AppInstallerRepositoryCore\RepositorySource.cpp(757)\WindowsPackageManager.dll!00007FFB146CC11F: (caller: 00007FFB14458D6F) LogHr(1) tid(1320) 8A15005E     Msg:[D:\a_work\1\s\external\pkg\src\AppInstallerRepositoryCore\Rest\Schema\HttpClientHelper.cpp(30)\WindowsPackageManager.dll!00007FFB145D2B08: (caller: 00007FFB1467BC20) Exception(1) tid(1320) 8A15005E ]
2024-08-21 21:27:52.177 [CLI ] ShellExecute installer failed:<PHONE_NUMBER>
MSI (s) (4C:00) [21:18:21:452]: PROPERTY CHANGE: Adding OutOfDiskSpace property. Its value is '0'.
MSI (s) (4C:00) [21:18:21:452]: PROPERTY CHANGE: Adding OutOfNoRbDiskSpace property. Its value is '0'.
MSI (s) (4C:00) [21:18:21:452]: PROPERTY CHANGE: Adding PrimaryVolumeSpaceAvailable property. Its value is '0'.
MSI (s) (4C:00) [21:18:21:452]: PROPERTY CHANGE: Adding PrimaryVolumeSpaceRequired property. Its value is '0'.
MSI (s) (4C:00) [21:18:21:452]: PROPERTY CHANGE: Adding PrimaryVolumeSpaceRemaining property. Its value is '0'.
Property(S): OutOfDiskSpace = 0
Property(S): OutOfNoRbDiskSpace = 0
Property(S): PrimaryVolumeSpaceAvailable = 0
Property(S): PrimaryVolumeSpaceRequired = 0
Property(S): PrimaryVolumeSpaceRemaining = 0
MSI (s) (4C:3C) [21:18:22:374]: PROPERTY CHANGE: Adding OutOfDiskSpace property. Its value is '0'.
MSI (s) (4C:3C) [21:18:22:374]: PROPERTY CHANGE: Adding OutOfNoRbDiskSpace property. Its value is '0'.
MSI (s) (4C:3C) [21:18:22:374]: PROPERTY CHANGE: Adding PrimaryVolumeSpaceAvailable property. Its value is '0'.
MSI (s) (4C:3C) [21:18:22:374]: PROPERTY CHANGE: Adding PrimaryVolumeSpaceRequired property. Its value is '0'.
MSI (s) (4C:3C) [21:18:22:374]: PROPERTY CHANGE: Adding PrimaryVolumeSpaceRemaining property. Its value is '0'.

Automated error analysis suggests -1978334960 may mean Failed to install package dependencies.
Automated error analysis suggests 8A15005E may mean APPINSTALLER_CLI_ERROR_PINNED_CERTIFICATE_MISMATCH - The server certificate did not match any of the expected values.
(Automated response - build 887.)

Pushed some changes and seems to work for me:

See https://github.com/microsoft/winget-pkgs/pull/168629#issuecomment-2307168149 for validation.

@wingetbot waivers Add Validation-Installation-Error

@stephengillie Is there something else I need to do? I keep getting notifications regarding validation.


[WIP] Compressed instruction support

Summary
This PR adds compressed extension 'C' support to BlackParrot. This is a WIP
Issue Fixed
Generally unhappiness with lack of C support.
Area
FE instruction scanning and BE instruction issuing
Reasoning (outdated, confusing, verbose, etc.)
This extension is required by the 'A22' RISC-V profile, meaning that general purpose Linux distributions will require it in the future.
Additional Changes Required (if any)
This PR is WIP because of a need for cleanup and optimization
Analysis
There are potential new timing paths in FE and impact to performance in the worst and average cases. Branching to a misaligned instruction has an additional cycle of latency, which can degenerate for a mixed set.
Verification
Standard regression, with manual inspection of erroneous instruction fetches
Additional Context
#1098 provided the baseline for this work

Closing for some work


[Security] Remove unused package-lock.json

Description
Currently, Ostracon documentation isn't generated using VuePress. However, there is a package-lock.json in the repository to build the documentation.
This PR removes this file (it is automatically generated by make build-docs), as outdated library versions in this file will be reported for security vulnerability checking.
This issue was reported by dependabot in https://github.com/line/ostracon/pull/334. Note, however, that this isn't a serious problem at the moment since we aren't using VuePress as mentioned above.
Closes: #XXX

@tnasu Indeed. I'll fix it.


remove kbson fork

see https://github.com/jershell/kbson/issues/11

Any news here? I need to configure some Bsons and use kMongo.

I'v just made the PR in kbson project https://github.com/jershell/kbson/pull/16
What is your need? Is it not covered by registerModule or registerSerializer ? (https://litote.org/kmongo/object-mapping/#the-kotlinx-serialization-choice)


chore: update capsule sdk

Updates Capsule SDK
Attempts to fix issue where faucet button displays used state incorrectly

Closing in favor of: https://github.com/capsule-org/react-example/pull/13


Slack test

slack test

commenting from slack

closing from slack (test done)

 Test Github issues in slack


Attempted import error: 'features'.'map' is not exported

Hi Faith
thanks for this & the Medium article
I'm trying to follow it- but can't get past this error:
Attempted import error: 'features'.'map' is not exported from '../data/data.json' (imported as 'features').
ERROR in ./src/components/Map.js 70:18-30
export 'features'.'map' (imported as 'features') was not found in '../data/data.json' (possible exports: 0, 1, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 2, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 3, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 4, 40, 41, 42, 43, 44, 45, 46, 5, 6, 7, 8, 9)

thank you in advance,
Andrew

thanks for the quick reply
Yes, I'm using your geojson- it works fine in other Leaflet maps and the structure looks o.k & it loads ok in QGIS- so I don't think it is this

Andrew

Ah, I see.
Then share a snippet of your Map.js file.
The whole of it.
Because I don't understand what that  '.map'  is
On Fri, Jun 9, 2023 at 1:56 AM barney2074 @.***> wrote:

thanks for the quick reply
Yes, I'm using your geojson- it works fine in other Leaflet maps and the
structure looks o.k & it loads ok in QGIS- so I don't think it is this
[image: image]
https://user-images.githubusercontent.com/25944617/244528805-8a53a57e-fe0c-402c-a522-0e833382a65c.png
Andrew
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Hi
thanks for the reply.
To cut a long story short:

I was having a few other problems with Node.js- it was 99% working- but not quite right.
It seemed to be related to multiple user accounts on the same PC, but running applications as a non-admin user
Anyway- I removed everything, changed permissions and everything is working fine

So sorry for the false alarm
thanks for sharing your work- I  found it very useful
Andrew

Glad to hear it!
On Sat, Jun 10, 2023 at 2:15 AM barney2074 @.***> wrote:

Hi
thanks for the reply.
To cut a long story short:

I was having a few other problems with Node.js- it was 99% working-
but not quite right.
It seemed to be related to multiple user accounts on the same PC,
but running applications as a non-admin user
Anyway- I removed everything, changed permissions and everything is
working fine

So sorry for the false alarm
thanks for sharing your work- I found it very useful
Andrew
—
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https://github.com/fmuchembi/census-kenya/issues/2#issuecomment-1585231971,
or unsubscribe
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Kenya |Cell: +254 726 219 092 |
Email: @.***|
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add .vscode/settings.json to allow testing and debugging of the unit tests inside vscode

.vscode/settings.json is currently included in .gitignore and I believe should be unique to each user, thoughts ?

in theory it should be depending on the package structure no?

I mean that not everyone uses vscode for testing, additionaly, you may want to modify the testing scheme depending on your usecase in vscode locally (for instance using unittest or pytest which yield different results), also, those files might differ depending on vscode version!

so you suggest we don't put it in github, and each of us use it independently?

Yes !


restructure the test context struct

Buy some headroom

Not a huge fan of the name executionState but I don't have a better suggestion!

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Fix issue with box and whiskers plot not handling non 0 lower bounds correctly.

Fix issue with box and whiskers plot not handling non 0 lower bounds correctly.

Corrected whether upper or lower bounds are negative or positive or non zero quartile box will form correctly.


Add .dtypes property to Dataset and test dtype(..)

Also would be nice to split it in 2 tests, since you now have two tests in 1 function, better 2 functions or more in 1 file

Thanks, awesome work.


Effect documentation

Would be cool to somewhere document all the possible effects, since there are none given and you can't read them out in Home assistants develeopers tool. E.g. i can't know what to set for "disco" mode or for "candle" mode.

Effects are not implemented. Will close this issue for now but I open for pull requests


Add public helper method for unwrapping

We are using ReflectionMagic for a method returning object (whose runtime type can be both a primitive or a complex type).
The problem is that "string".AsDynamic().RealObject fails because of the wrapper skipping.
I am proposing to expose a helper method for the unwrapping (the code is already present in PrivateReflectionDynamicObjectBase.Unwrap).

Hey, thank you for bringing up this issue and also bringing in a pull request at the same time! Unfortunately I'm having trouble understanding your use case. I do agree that unwrapping whatever AsDynamic() is invoked on should have a place somewhere in the library, I just want to make sure we are fixing the right problem.
Per your pull request, you can unblock for now by implementing your own unwrapping code:
public static object Unwrap(object o)
{
    if (o is PrivateReflectionDynamicObjectBase wrappedObj)
        return wrappedObj.RealObject;

    return o;
}

Could you explain why are trying to round-trip the result through a call to AsDynamic()? Are you trying to call a method which should be located at runtime based on the real type? Calling obj.AsDynamic().RealObject will just give you what you already had: obj. Or, as you have noticed, for certain types no wrapping is done, causing that call to throw an exception at runtime.

Thanks for your patience. I understand the use-case might not obvious or common.
We are using ReflectionMagic .AsDynamic() in the typical sense, i.e. instance.AsDynamic().InternalMethod().
Things get interesting when the non-public method has a return type of object, but the real type can range from primitive to complex. A real-world example would be: dynamic deserialized = serializer.AsDynamic().InternalDeserialize(serializedObject).
Now, we are not interested in chaining further reflection calls on deserialized, but just unwrapping the reflection helper to an object. Because we are dealing with compile-time object, usages of it will generally involve reflection, e.g. serialization: JsonConvert.SerializeObject(deserialized). The problem would be that the reflection code of the serializer hits the wrapper type instead of the type of the real object.
We've had unwrapping needs in two cases: one for making sure an object is serialized properly, and another in making sure that a proper generic type is created, e.g. typeof(Generic<>).MakeGenericType(deserialized.GetType()). This felt like it would warrant creating an issue, in the sense of making ReflectionMagic API more complete.

Sorry for leaving you hanging on this. I'm thinking about an API but can't really get the naming down properly, I came up with this:
public static class DynamicHelper
{
   public static object Unwrap(dynamic d);
}

I don't like things named Helper, but can't really think of anything better.

Since this would be reversing .AsDynamic() which is essence of the ReflectionMagic API, I'm not sure we can come up with a less generic name.
Another not ideal, choice would be ReflectionMagic as a class name.

Fixed in #32


Getting error: no such module 'Iconic'

When testing on device/emulator it works allright, but when trying to build the .ipa I get this error: error: no such module 'Iconic', any advice?

@dzenbot Github has stopped sending me notifications, I'm seeing this just now.
That said, I fixed my issue and I don't even remember how, I think had some issues in my project setup.
Thanks, and closing this issue....


dns/bind: Plugin Improvements

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, open and closed, 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.

Is your feature request related to a problem? Please describe.
There are a couple of missing features I'd like to use in the dns/bind plugin and I'm working on adding them, I'm opening this issue to gather feedback/suggestions.
Describe the solution you'd like

Better Key management, allowing you to re-use keys for multiple zones.
Slave Zone Master configuration, this would allow you to re-use masters/keys for multiple zones.
RFC 2136 support, dependent on 1. , but would allow for a master zone to be updated by something like K8s external DNS or similar type dynamic DNS

Better Key Management (I've already started work on this here https://github.com/sestary/opnsense-plugins/tree/keys):

[x] Create a new Key management page, where you can add/remove keys (name, algo and secret fields)
[x] Keys are added to named.conf
[x] Add multiple key selector to master zone dialog
[x] Update slave zone dialog to select key
[x] Dedicated section to allow updates to the RNDC Key (default will use existing key) https://github.com/opnsense/plugins/issues/2196, completed in PR #3239.
[x] Create migration from existing key setup

Slave Zone Master configuration:

[ ] Create a new Masters page, where you can add/remove masters, this would allow you to specify the IP/Port and select the Key
[ ] Update the named.conf logic to support new masters
[ ] Add multiple key selector to the slave zone dialog

RFC 2136 Support:

[ ] Add RFC 2136 allow-update support. This would simply reference existing ACLs like Allow Query
[ ] Add RFC 2136 update-policy support. Three options here:

Only support one rule per zone
Support multiple rules, this would need to be a separate model (I haven't figured out a way to add multiple fields multiple times)
Add a simple text field for users to add their own rules to (rather not do this since it's error prone)

Other things I'd like to do at some point:

[x] Update master/slave in official nomenclature as per https://github.com/opnsense/plugins/pull/3222#issuecomment-1357428183 done in https://github.com/opnsense/plugins/pull/3234
[ ] Advanced field that allows any Bind name.conf option to be added through a text box in General settings and in the zone dialogs. Allowing for custom advanced config without direct support in the Plugin.
[ ] Views?

@mimugmail @fichtner Let me know what you think of this. Is there anything else that makes sense to be added?

I would like to update DNS records from DHCP. As far as I can see on the DHCP-side everything is here and your changes would add the required bind configuration. Please let me know if you have a testable version, I would be happy to give it a try.

I would love support for Forward Only DNS zones, the zone configuration is quite simple.
zone "somedomain.com" {
type forward;
forward only;
forwarders { <IP_ADDRESS>; <IP_ADDRESS>; };
};
I use quite a few of these for internal only domains on VPN tunnel setups, to point them to the correct internal DNS server on the other end. Some times its just you don't get permissions to copy a slave zone. And sometimes the server doesn't support it.

@bugspencor I will let you know once I have a testable version with the RFC 2136 Support.
@dweimer That should be relatively easy to add, definitely something I could use as well.

Is it possible to include DNS overrides? As I understand it, this is done via RPz entries or?

@lucaschoeneberg This is possible, but I'd have to look into it. This is not a feature I'd be using so it'd be low priority for me to implement it. Might be good to open a separate feature request for it.

@lucaschoeneberg @sestary I have done a simple implementation of overrides.  It uses a master zone called rpzlocal and a one line change to the template see my comment here https://github.com/opnsense/plugins/issues/3276
I am very interested in views, because that's really the correct way to do split horizon config.

@sestary any news about RFC 2136 support?

Right now I don't have any news I've ran into a couple of problems getting some of the functionality to work reliably. The main problem is with the migrations. This plugin is one of the only plugins that uses multiple models to represent the data and doing a migration from one model to another to add new features is proving to be more difficult than I thought.
The second issue I've identified while doing the initial RFC 2136 support is that essentially it would need to be setup like a secondary zone where you can't create/list/delete the records on the UI. This is because the records are stored in the config file and there doesn't seem to be a good way to sync the dynamic information in the zone file so that when you edit a manually added record it erases all of the dynamic entries.
I've investigated adding a UI records manager which uses RFC 2136 in the background, but at that point I'm almost rewriting the entire plugin. Coupled with the migration issues above and I'm wondering if it's easier to just do a new plugin with an easier to maintain data model.

For 1) we discussed this not too long ago and you can do https://github.com/opnsense/core/blob/84f0bcdbdb182c104c07b1170daf8a4927655253/src/opnsense/mvc/app/models/OPNsense/Core/Migrations/M1_0_0.php#L42-L44 to pin down the migration to a specific model. The other issue is that you need to bump all version numbers of models to the same target version the migration exists for in order to cleanly execute it.

About 2) I'm not sure what you try to do. Usually we split configuration data and runtime data. Sometimes configuration data is expanded with runtime information, but runtime information is never used to be turned into configuration data.

For 1) we discussed this not too long ago and you can do https://github.com/opnsense/core/blob/84f0bcdbdb182c104c07b1170daf8a4927655253/src/opnsense/mvc/app/models/OPNsense/Core/Migrations/M1_0_0.php#L42-L44 to pin down the migration to a specific model. The other issue is that you need to bump all version numbers of models to the same target version the migration exists for in order to cleanly execute it.

Setting the model that the migration is part of isn't the problem. The problem is migrating data from the General Model to a new model for example but keeping a link in General to the entries created under the new model. The code here: https://github.com/sestary/opnsense-plugins/blob/forwardzone/dns/bind/src/opnsense/mvc/app/models/OPNsense/Bind/Migrations/M1_2_0.php#L43 is how far I got with trying to get that to work. It's broken but I'm not sure of a good way to implement this.

About 2) I'm not sure what you try to do. Usually we split configuration data and runtime data. Sometimes configuration data is expanded with runtime information, but runtime information is never used to be turned into configuration data.

The problem is that Bind will add dynamically added entries to the zone files (initially in a journal file but those are written to the main zone file very X min). Right now in the plugin those are templated so when you hit save because you added a new entry the file is overwritten and all dynamic entries are now gone. So there are two options that are viable:

Have dynamic only zones, this way you'd have to setup a keys that allow updates to the zone even for admins, so that automatic updates from tools and admin go through the same route. (definitely the easiest)
Treat all the zones as dynamic and rewrite the "save" function to do the updates through the rndc utility. The biggest issue with this approach would be having a dynamically updated entry override the static entry and that would still show the old value in the config.

As @howudodat pointed out: being able to do a proper split horizon dns vía bind views would be awesome!
I am struggling to setup such a split horizon dns with the given UI tools right now...

I have a few suggestions for additions, I hope they are welcome:

I think we should have the ability to define forwarders running on non standard ports. As of now you can only add forwarders running on port 53
Adding support for DNS-over-TLS and DNS-over-HTTPS for bind9. This was introduced in bind 9.17
Planning ahead for Bind 9.19 which added support for DNS-over-TLS for forwarders

Is there any progress being planned for this? It'd be great if we could use rndc keys with custom zones with the bind plugin.
Maybe this could be split off into multiple smaller features that perhaps are more digestible and not as ambitious up front?

Stumbled onto this issue after needing my bind to support RFC 2136 and manually updating the template file so it doesn't overwrite me constantly, but official support would be fantastic!  I agree with @0dragosh that the goals here were a bit overly optimistic and could have been broken down into smaller parts that would be more than sufficient for most users needs

@los93sol I've since discovered you can leverage /usr/local/opnsense/service/templates/OPNsense/Bind/named.conf to at least partially hack your way around the config file overwrites. Have not played with it enough though.
If you do manage to get a proper template config working through service restarts for RFC2136 I'd love to see it!

I recently found out that my use case (being able to resolve dhcp clients in the LAN via unbound) is already working with current opnsense.
I'm using opnsense-unbound as resolver and unbound forwarding to bind for my primary LAN domain and reverse zones. IIRC I enabled "Register DHCP Leases" in unbound and also set the domain in System/Settings/General. Unbound seems to first resolve the known DHCP leases and forwards the rest to DNS.
Maybe that helps anybody else.

It is unfortunate that this has not seen any progress recently. RFC 2136 Support would significantly help in some ipv6 hosting use-cases. Currently I have bind running in a separate container acting as the authoritative server for my local domain.  The lack of allow-update support prevents me from using the os-bind plugin instead. Easy configuration to let the DHCP services do local DDNS would be great.


Bump to latest minor releases

Signed-off-by: Lukas Reschke<EMAIL_ADDRESS>

Deployed on internal_updater_server


What would lead to the Frame type unexpected exception

I am using the example code to transmit a file.
I try several times. Sometimes it throws the Frame type unexpected exception. Sometimes it works fine.
So I am  wondering what would cause the exception

You would have to provide more details (eg: a reproducer) for us to understand this better.


flutter_gallery__start_up timeToFirstFrameMicros regressed

Sometime around 2019-02-27, flutter_gallery__start_up timeToFirstFrameMicros got about 10% slower.
cc @HansMuller @jason-simmons

@liyuqian Is it possible that https://github.com/flutter/flutter/pull/28537/ had an impact on gallery start-up time?

@HansMuller @Hixie that's definitely due to #28537. It's a tradeoff between worst frame time and start up time. I rebaselined other benchmarks and forgot this one. Rebaselining it now.

Rebaselined. Close the issue as the regression is expected.