Broken installation (both via PyPi and GitHub)

It appears as though one is unable to install the qiskit-quantinuum-provider package either via the PyPi server (as it is not present) or via Git. IOW, doing:
pip3 install qiskit-quantinuum-provider

is broken as the PyPi link is broken. Alternatively, attempting to install the package via Git, that is:
python -m pip install 'qiskit-quantinuum-provider @ git+ https://github.com/qiskit-community/qiskit-quantinuum-provider'

also fails. It seems as if the last commit to this project was at the end of March of 2023. Are there any plans to continue development on this project or has it been deprioritized? If the latter, are there any specific adaptations one would have to do in order to make use of this provider pattern within Qiskit?
fyi @mtreinish, @1ucian0 @chris-theroux

Hi @1ucian0
Thanks for the quick reply.

Because there was not release after the rename, you should be able to still do pip install qiskit-honeywell-provider. You can also install from github like this:

This would be great to provide in the README. Otherwise, I'm not sure if it would be possible for users to be aware of this. Perhaps this is obvious to those internally, but for me, this was definitely a surprise :)
Regarding being able to use the package, I have a question about usage. I see that the .save_account method naturally points to the Honeywell page for user login. Naturally, I'd rather use the qapi.quantinuum.com/ URL instead. I see that one can configure this (in principle) in the proxies variable
    import os
    from qiskit.providers.honeywell import Honeywell
    USERNAME = os.environ.get("QUANTINUUM_USERNAME")
    PASSWORD = os.environ.get("QUANTINUUM_PASSWORD")
    Honeywell.save_account(USERNAME,
                           proxies = { 'urls': {'http':
<EMAIL_ADDRESS>                           'https':
<EMAIL_ADDRESS>                           } })

    backends = Honeywell.backends()
    backend = Honeywell.get_backend(machine)

However, this seems to fail is appears to be pointing to the Honeywell login link despite the fact that (I thought) I was configuring it to login to a different URL. I'm most likely doing something wrong, but is it obvious what that might be? Thank you again for your help!
Here is the error output upon trying to call the associated save_account method:
/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/__init__.py:38: FutureWarning: This is the final release of qiskit-honeywell-provider. It will be replaced by the qiskit-quantinuum-provider package in the future.
  warnings.warn("This is the final release of qiskit-honeywell-provider. "
Enter your password:
Traceback (most recent call last):
  File "/Users/vincent.russo/Projects/resarch/unitary_fund/metriq-api/benchmark/benchmark/QC-App-Oriented-Benchmarks/quantum-fourier-transform/qiskit/qft_benchmark.py", line 427, in <module>
    backends = Honeywell.backends()
               ^^^^^^^^^^^^^^^^^^^^
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/honeywellprovider.py", line 92, in backends
    if not self._api.has_token():
           ^^^^^^^^^^^^^^^^^^^^^
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/api/honeywellclient.py", line 76, in has_token
    return bool(self.client_api.session.credentials.access_token)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/api/session.py", line 96, in credentials
    self.update_auth()
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/api/session.py", line 89, in update_auth
    self.headers.update({'Authorization': self._credentials.access_token})
                                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/credentials/credentials.py", line 146, in access_token
    return self._login()
           ^^^^^^^^^^^^^
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/credentials/credentials.py", line 274, in _login
    self._authenticate()
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/credentials/credentials.py", line 205, in _authenticate
    status_code, message = self._request_tokens(body)
                           ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/credentials/credentials.py", line 155, in _request_tokens
    response = sess.post(
               ^^^^^^^^^^
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/requests/sessions.py", line 635, in post
    return self.request("POST", url, data=data, json=json, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/vincent.russo/Library/Caches/pypoetry/virtualenvs/benchmark-Is--SOOG-py3.11/lib/python3.11/site-packages/qiskit/providers/honeywell/api/session.py", line 170, in request
    raise RequestsApiError(ex, message) from None
qiskit.providers.honeywell.api.exceptions.RequestsApiError: HTTPSConnectionPool(host='qapi.honeywell.com', port=443): Max retries exceeded with url: /v1/login (Caused by ProxyError('Cannot connect to prox


contribute.md for each repository

It was brought up today in the All Hands call (ipfs/pm#243) that we could have a Contribute.md in each repository. As we already have a contribute section in every repo, as outlined by Standard Readme, this wouldn't be too much of an extra step, and it would flag everyone opening an issue or a PR on an IPFS repository to check the contributor guidelines. It could also hold a section for tests.
I think this is a good idea. What do you think?

This is a pretty awesome example of a contributing file: https://github.com/zkat/pacote/blob/latest/CONTRIBUTING.md

@dignifiedquire What do you think we could take from that?

I think the CONTRIBUTING.md @dignifiedquire linked is a very good example. Has a nice table of contents with many ideas on how people contribute, with links to each section explaining more. Seems to have come from this generator: https://www.npmjs.com/package/weallcontribute

Do we want a CONTRIBUTING.md per repo, or a main one to all repos that is linked from a CONTRIBUTING.md in every repo (so that Github reminds contributors to check it) ?

I think ideally we have the same file in every repo and a tool to sync it from a master file

That'll quickly dirty up the git history. Might be better to have a CONTRIBUTING.md in each repo that just links to a central one. You can repurpose the Contribute section of the README to point to the main one, too.

Yeah, that's what I did here: https://github.com/libp2p/js-libp2p/blob/master/CONTRIBUTING.md
Looks good?

LGTM.

moved to https://github.com/ipfs/testing/issues/48


Are all Reducer registered globally?

May I know is Action / Reducer are always registered globally?
In the Plnkr example, app/action-reducers.ts registered some actions. If I have a large application, looks like I have to be careful with naming my action name, make sure there is no duplication.

Yes, you do have to be careful not to create reducers that share a name.
You can define reducers in multiple classes though, like this:
@Reducer('add')
export class AddActionReducers {
  add(state)      { return { count: state.count + 1 } }
}

@Reducer('remove')
export class RemoveActionReducers {
  remove(state)   { return { count: state.count - 1 } }
}

This will help with organising your reducers for larger applications, but doesn't help with the name problem.
I'll have a think about possible solutions.  The first that comes to mind is namespacing, but I'm not sure what the syntax for that would look like yet - perhaps something like this?
@Reducer('product:add', 'product:remove')
export class ActionReducers {
  add(state)      { return { count: state.count + 1 } }
  remove(state)   { return { count: state.count - 1 } }
}

Or perhaps:
@Namespace('product')
@Reducer('add', 'remove')
export class ActionReducers {
  add(state)      { return { count: state.count + 1 } }
  remove(state)   { return { count: state.count - 1 } }
}

I'm leaning towards the latter.

Thanks for quick reply. I am new to Redux so cannot provide any comment on your solutions.
Does other ng2 redux library has the same problem?

Redux itself shares this problem.  Remember that actions are just functions registered against an identifier.
Taking redux out of the equation, how would you typically solve this problem?  By changing the function names to be unique or "namespacing" the functions using modules/classes.
You might find this useful: reactjs/redux #786 examples - how to implement action type namespacing ?

I'm assuming this issue is resolved.


New version: Nvidia.CUDA version 11.6

[X] Have you signed the Contributor License Agreement?
[X] Have you checked that there aren't other open pull requests for the same manifest update/change?

[X] Does your manifest conform to the 1.0 schema?

Microsoft Reviewers: Open in CodeFlow

🤔
				Response Code: 0
				Response: An error was encountered while processing request. Exception:
Exception Message: Cannot get DNS address for host 'winget-pme.azurefd.net' (No such host is known). (type TeamFoundationServerException)


RFC0035: Warning Emissions, -OS parameter, and -MaximumPSVersion parameter

PR Summary
Changes implemented from RFC0035.
Add support for the following new parameters:

-OS {Windows | Linux | MacOS} where an operating system (or possibly combination of them) can be specified as required.
-MaximumPSVersion <V>[.<v>], where a maximum PowerShell version can be specified as required.

PR Context
In about_Requires, it is stated that:

You can use #Requires statements in any script. You cannot use them in functions, cmdlets, or snap-ins.

Currently however, this is untrue, as #requires statements are allowed by the parser/tokenizer anywhere in a script and then effectively hoisted to the top of that script to be checked before any part of the script is executed, no matter where they are placed. To warn users of unexpected behaviour, #requires statements appearing after any line that is not blank or a comment (i.e. any semantic statement) will generate a warning at parse-time about being hoisted to the top of the script. Other comments, such as hashbangs, and blank lines preceding a #requires will not generate this warning.

[x] PR has a meaningful title

Use the present tense and imperative mood when describing your changes

[x] Summarized changes
[x] Make sure all .h, .cpp, .cs, .ps1 and .psm1 files have the correct copyright header
[ ] This PR is ready to merge and is not Work in Progress.

If the PR is work in progress, please add the prefix WIP: or [ WIP ] to the beginning of the title (the WIP bot will keep its status check at Pending while the prefix is present) and remove the prefix when the PR is ready.

Breaking changes

[x] None
OR
[ ] Experimental feature(s) needed

[ ] Experimental feature name(s):

User-facing changes

[ ] Not Applicable
OR
[x] Documentation needed

[ ] Issue filed:

Testing - New and feature

[ ] N/A or can only be tested interactively
OR
[x] Make sure you've added a new test if existing tests do not effectively test the code changed

Tooling

[x] I have considered the user experience from a tooling perspective and don't believe tooling will be impacted.
OR
[ ] I have considered the user experience from a tooling perspective and enumerated concerns in the summary. This may include:

Impact on PowerShell Editor Services which is used in the PowerShell extension for VSCode (which runs in a different PS Host).
Impact on Completions (both in the console and in editors) - one of PowerShell's most powerful features.
Impact on PSScriptAnalyzer (which provides linting & formatting in the editor extensions).
Impact on EditorSyntax (which provides syntax highlighting with in VSCode, GitHub, and many other editors).

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.:x: ivanshen sign nowYou have signed the CLA already but the status is still pending? Let us recheck it.

I've played around with the warnings a bit and there's no easy way I can see to get them to write to a stream. So the possibilities are:

We forget about writing warnings, since it's a small addition externally but a big change to the code, is hard to test and doesn't work well with how the parser is designed
We turn them into runtime errors by checking the ScriptRequirements property on the AST when it's run
We make it easier for the static parser instance to pick up the current runspace and write warnings to streams
We look into what the right test hook solution would be

Tailing off your second idea there, couldn't we also then equally just make them runtime warnings in the same way we could make them runtime errors? 🤔

Oh sorry I meant warnings! Will edit

That also prevents issues like script caching meaning no warning gets output

@rjmholt Please update you review.

@SteveL-MSFT we might want a label or similar here?


Potential Fix (sorta?)

I don't know where to put this, but because I have the knowledge (and the patience), I managed to get this tool to work on Mac. Just used Winebottler and installed some simple wine tricks and it runs perfectly.
I can send my current file (to make things easier) and allow Mac users to use this app if people wish.
P.S. An error might show up if you open it for the first time, but it never shows up after the first instance

Hi kebbles007! Sorry for the late reply
Thanks for the info! I have to take a look if I can compile the tool in Mac when I have some spare time (I use Mac myself, but to code and run the tool I use Parallels Desktop to virtualize Windows :P); I'll create a new issue about it :).
I remember that apps generated with WineBottler are quite heavy, so I'm not sure if it should be uploaded here. In the meanwhile it may be better to explain the whole process so anyone with a Mac can do it themselves. Would you like to write a guide about it?
Thanks!

DDFF Toolkit for Mac.rtfd.zip
I typed it up in TextEdit, feel free to message me if there are any probelms


Remove unused toml build-dependency

yes, guess this is a left-over from the previous profiles approach.


Fix: addon store&show complicated parameter

fix complicate args storage
Signed-off-by: 楚岳<EMAIL_ADDRESS>Description of your changes
eg: vela addon enable velaux imagePullSecrets={myreg,myreg2}
request <IP_ADDRESS>:8000/api/v1/addons/velaux/status will return
{
    "name": "velaux",
    "phase": "enabled",
    "args": {
        "imagePullSecrets": [
            "myreg",
            "myreg2"
        ]
    },
}

Refer to ：https://github.com/oam-dev/velaux/issues/372
I have:

[ ] Read and followed KubeVela's contribution process.
[ ] Related Docs updated properly. In a new feature or configuration option, an update to the documentation is necessary.
[ ] Run make reviewable to ensure this PR is ready for review.
[ ] Added backport release-x.y labels to auto-backport this PR if necessary.

How has this code been tested

Special notes for your reviewer

please addon test case to indicate the error

added


Embedded blog links no longer exist

The blog post appears to no longer exist:
https://blog.okturtles.org/2022/10/convert-wordpress-to-static-site/

Hi @ruskintech, you've found our repo for a blog post that hasn't been published yet! 😄
Hopefully we'll have this out soon, my apologies for the delay.

Ha! How unlike me to show up early.

Honestly I'm surprised myself 😅
We wanted to release it after we released some other stuff, and that "other stuff" has been taking quite a long time.

Published!
https://blog.okturtles.org/2024/10/convert-wordpress-to-static-site/


AttributeError: 'NoneType' object has no attribute 'keys'

Thank you for the amazing tool. I am handling WES data.
When I ran the following code, I get the error shown below.
What would the the problem?
sig.sigProfilerExtractor("matrix", "Total_Exome_True", "/data/project/ESCC2/4.analysis/DNA/1.Variant_Calling/SigProfiler/Total_Exome_True/output/SBS/Total.SBS96.exome.txt", reference_genome="GRCh38", opportunity_genome="GRCh38", exome=True)
There may be an issue with the formatting of your matrix file.
Extracting signature 24 for mutation type 96
The matrix normalizing cutoff is 9600

Time taken to collect 100 iterations for 24 signatures is 409.37 seconds
Optimization time is 2.136180877685547 seconds
The reconstruction error is 0.0818, average process stability is 0.09 and
the minimum process stability is -0.29 for 24 signatures

There may be an issue with the formatting of your matrix file.
Extracting signature 25 for mutation type 96
The matrix normalizing cutoff is 9600

Time taken to collect 100 iterations for 25 signatures is 512.07 seconds
Optimization time is 3.96828031539917 seconds
The reconstruction error is 0.0849, average process stability is 0.1 and
the minimum process stability is -0.24 for 25 signatures

There may be an issue with the formatting of your matrix file.

 De Novo Fitting .....
There may be an issue with the formatting of your matrix file.

 Decomposing De Novo Signatures  .....
There may be an issue with the formatting of your matrix file.
There may be an issue with the formatting of your matrix file.
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/Yonsei/python/3.8.1/lib/python3.8/site-packages/SigProfilerExtractor/sigpro.py", line 862, in sigProfilerExtractor
    decomp.spa_analyze(allgenomes, output, signatures=processAvg, genome_build=genome_build, cosmic_version=cosmic_version, exome=exome, verbose=False,
  File "/opt/Yonsei/python/3.8.1/lib/python3.8/site-packages/SigProfilerAssignment/decomposition.py", line 520, in spa_analyze
    final_signatures = sub.signature_decomposition(processAvg, mutation_type, layer_directory2, genome_build=genome_build,cosmic_version=cosmic_version,signature_database=signature_database, mutation_context=mutation_context, add_penalty=0.05, connected_sigs=connected_sigs,remove_penalty=0.01, make_decomposition_plots=make_decomposition_plots, originalProcessAvg=originalProcessAvg,new_signature_thresh_hold=new_signature_thresh_hold,sig_exclusion_list=sig_exclusion_list,exome=exome, m_for_subgroups=m_for_subgroups)
  File "/opt/Yonsei/python/3.8.1/lib/python3.8/site-packages/SigProfilerAssignment/decompose_subroutines.py", line 369, in signature_decomposition
    byte_plot = sp.run_PlotDecomposition(originalProcessAvg[denovo_cols],
  File "/opt/Yonsei/python/3.8.1/lib/python3.8/site-packages/SigProfilerAssignment/DecompositionPlots/PlotDecomposition.py", line 513, in run_PlotDecomposition
    denovo_plots_dict = convert_to_imgReaderDict(denovo_plots_dict)
  File "/opt/Yonsei/python/3.8.1/lib/python3.8/site-packages/SigProfilerAssignment/DecompositionPlots/PlotDecomposition.py", line 162, in convert_to_imgReaderDict
    for name in image_dict.keys():
AttributeError: 'NoneType' object has no attribute 'keys'

I uploaded the
JOB_METADATA_Extractor.txt
and
SigProfilerMatrixGenerator_Total_GRCh382024-03-30.out.txt.
Also the input matrix.
Total.SBS96.exome.txt

Hi @jennyp76,
I have tested with your input file with the following versions and was unable to reproduce your error:
SigProfilerAssignment      0.1.4
SigProfilerExtractor       1.1.23
sigProfilerPlotting        1.3.22
Could you please update to the following versions? Please reach out if your issue persists.

I've encountered this before and my debugging led me to corrupt Pickle files (*.pkl) in sigProfilerPlotting/templates. What helped was uninstalling sigProfilerPlotting and reinstalling. Then the script ran successfully.
pip uninstall SigProfilerPlotting -y; pip install SigProfilerPlotting
Hope this helps,
Marc

Please re-open this thread if you are still encountering this issue, thanks!


Flag to append to the quickfix list

Currently a new location/quickfix list gets created always.
It would be nice if Grepper could optionally append to an existing one instead.

I added :Grepper -append!

@mhinz It looks like if I use :GrepperAg -append <query>, -append is not respected... Could you check please?

@balta2ar You can't.
Look at how it is defined with :com GrepperAg:
command! -nargs=+ -complete=file GrepperAg Grepper -noprompt -tool ag -query <args>

So, in your case Grepper would run ag --vimgrep -append <your query>.


Support for automated tests and dev environments

Supports automated tests, travis ci (not implemented on main repo) and docker-compose for dev environments

merged as no impact on node app or db


coininsider.com blocked

coininsider.com is blocked in hosts but appears to be a normal news site.
I double-checked by searching the URL on reddit to see if there were any scam issues and all appears normal.

Hi @mokahless thank you for this.
The domain coininsider.com comes to us from the KADhosts list.  Can you please report this concern at the link below?  Thanks.
https://github.com/PolishFiltersTeam/KADhosts/issues


[Waiting for Source Code Merge] Bring PVC Protection Feature to Beta

Documentation for PR:
https://github.com/kubernetes/kubernetes/pull/59052
Target release: 1.10

This change is

@msau42 @tengqm I believe I've addressed your comments. Should I squash the commits?

/lgtm

lgtm, please squash

Commits squashed.

/hold cancel
/approve
(pending PR for feature updates has been merged)


Error: undefined constant Stream::State::Idle

When compiling the client
client.request(headers) do |headers, body|
             ^------
Error: instantiating 'Duo::Client#request(HTTP::Headers)'

In lib/duo/src/duo/client.cr:57:36

 57 | stream = @connection.streams.create
                                   ^-----
Error: instantiating 'Duo::Streams#create()'

In lib/duo/src/duo/streams.cr:47:24

 47 | def create(state = Stream::State::Idle)
                         ^------------------
Error: undefined constant Stream::State::Idle

After changing to Duo::State::Idle, it compiled ok. But there is exeption:
Unhandled exception:  (Duo::Error)
  from /home/ali33/lib/duo/src/duo/connection.cr:217:9 in 'read_frame_header'
  from /home/ali33/lib/duo/src/duo/connection.cr:62:7 in 'call'
  from /home/ali33/lib/duo/src/duo/client.cr:33:7 in 'initialize'
  from /home/ali33/lib/duo/src/duo/client.cr:10:5 in 'new'

Is the client usable when connecting to other host other than localhost?

I manually changed the max_frame_size value, then it can connect to the server. But the server responded with message HTTP/1.1 400 Bad Request\r\nDate: Tue, 30 Nov 2021 09:11:31 GMT\r\nContent-Type: text/html; charset=UTF-8\r\nContent-Length: 166\r\nConnection: close\r\n\r\n\r\n<title>400 Bad Request</title>\r\n\r\n
400 Bad Request
\r\n
nginx\r\n\r\n\r\n

@Dan-Do thanks for reporting this. Let me know if you have a fix for this if yes feel free to create a PR

Allow me a few days to look into this issue.


Add HMAC functions

I know this is going to sound crazy, but would it be possible to squash all these together? In my opinion it makes reviewing easier.

Also, LOL @ 11/29. I'm so sorry about the delay. puts head in hands


Docs.MS CI Updates for Azure.Extensions.AspNetCore.DataProtection.Keys

Docs.MS CI Updates for Azure.Extensions.AspNetCore.DataProtection.Keys

Docs Build status updates of commit 046e922:
:white_check_mark: Validation status: passed

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bundlepackages/azure-dotnet.csv
:white_check_mark:Succeeded

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For any questions, please:Try searching in the Docs contributor and Admin GuideSee the frequently asked questionsPost your question in the Docs support channel

Docs Build status updates of commit 2a5f948:
:x: Validation status: errors
Please follow instructions here which may help to resolve issue.

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:x:Error

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[Error-BackendEngineExceptionError] An exception occurred during the build process. Please check the raw log and retry building your content again. If the issue persists, please open a ticket in https://SiteHelp and include the URL of publishing report as well as below information: One or more errors occurred..
[Error-BackendEngineExceptionError] An exception occurred during the build process. Please check the raw log and retry building your content again. If the issue persists, please open a ticket in https://SiteHelp and include the URL of publishing report as well as below information: Absolute path rootPath: W:\k1ks-s couldn't be found.

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Note: Your PR may contain errors or warnings unrelated to the files you changed. This happens when external dependencies like GitHub alias, Microsoft alias, cross repo links are updated. Please use these instructions to resolve them.
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PHPLIB-989: Move persistable class documentation to tutorial

PHPLIB-989
This moves the documentation on classes implementing MongoDB\BSON\Persistable from the BSON reference to a tutorial. It was already written as a tutorial, and linking it as a tutorial on the homepage will make it more visible to users.
I've also considered doing the same with the Type Map information, but considering that persistable classes cover typemap functionality as well, I'm not sure we'll want to. Any opinions @jmikola?

since my Giza build environment is broken.

Just fixed it and was able to preview this PR. Everything looks good.


Need to perform some action when view is expended.

Describe your suggested feature
Thank you for the great library, i am developing an application which needs to perform some function without user action and set to textview, which is inside the layout expandedView = LayoutInflater.from(this).inflate(R.layout.results, null). when expended view is visible this function will execute and perform some task. how to achieve this?
Other details
No response
Acknowledgements

[X] I have searched the existing issues and this is a new ticket, NOT a duplicate or related to another open or closed issue.
[X] I have written a short but informative title.
[X] I have updated the library to the latest Version.
[X] I will fill out all of the requested information in this form.

@TorryDo

Hi @nicemak 👋. Sorry for the late reply,
If I understand your question correctly, you want to execute some functions after the expanded-view is visible and set the TextView  right?
If so, then after you call expand() function to show the expanded-view, you can find the id of the TextView and set the text directly
val textView = expandedView.findViewById(R.id.yourTextViewId)
textView.text = "hello world"


Pr/39

closes #39
Changes

[x]<EMAIL_ADDRESS>[ ] update golang in Dockerfile
[ ] fix tests
[ ] fix /account/coins

Pull Request Test Coverage Report for Build 774

7 of 36 (19.44%)  changed or added relevant lines in 3 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage decreased (-2.5%) to 68.106%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

bitcoin/client.go
6
8
75.0%

services/account_service.go
0
27
0.0%

Totals

Change from base Build 760:
-2.5%

Covered Lines:
1104

Relevant Lines:
1621

💛  - Coveralls


automate transcript upload

Pre-Flight checklist

[x] Testing

[x] Code is tested
[x] Changes have been manually tested

What are the relevant tickets?
https://github.com/mitodl/ocw-studio/issues/752
What's this PR do?
This pr adds code to automatically upload videos to 3play for transcription after they are created on youtube.
How should this be manually tested?
(Required)
Where should the reviewer start?
(Optional)
Any background context you want to provide?
(Optional)
Screenshots (if appropriate)
(Optional)
What GIF best describes this PR or how it makes you feel?
(Optional)

Codecov Report

Merging #777 (6fcfa60) into master (4c9fddf) will increase coverage by 3.24%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master     #777      +/-   ##
==========================================
+ Coverage   91.54%   94.78%   +3.24%
==========================================
  Files         187       92      -95
  Lines        6976     2626    -4350
  Branches     1095      567     -528
==========================================
- Hits         6386     2489    -3897
+ Misses        514      135     -379
+ Partials       76        2      -74

Impacted Files
Coverage Δ

videos/api.py

videos/constants.py

videos/tasks.py

videos/threeplay_api.py

videos/urls.py

videos/views.py

websites/serializers.py

websites/site_config_api.py

content_sync/models.py

content_sync/__init__.py

... and 85 more

Continue to review full report at Codecov.

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Enh/dark mode images

This pull request adds a light-background version of the SVG images used in README and uses this trick to use this version in dark mode (and the original files otherwise). It also makes a miniscule tweak to datacat3_the_toolset (letter O filling). Fixes #110
I've decided to use an off-white background (#eff1f5 / rgb(239, 241, 245)) instead of plain white - I like it, but it can be easily changed.

Thanks @mslw this looks good to me. Also like the nifty light/dark switch!


Currently, clicking 'Reviews' in the navbar redirects to the gallery section, but it should lead to a non-existing reviews section. I intend to create a dedicated reviews section for the redirection.

Is your feature request related to a problem? Please describe.
When we click on reviews in the navbar, it redirected us to gallery section on the home page. Instead it should be redirected to reviews section which is not present.
Describe the solution you'd like
So I would like to create a review section to which we can redirect on clicking reviews.

Are you contributing under any open-source program ?
Yes, under JWoC 24

@pranjal12-web That's a very good issue. I want to suggest you that make the REVIEW button in navbar as GALLERY & also make a separate page as REVIEW with some picture & interactive section
Nut we already have a feedback issue assigned. #145  So I am not closing this issue. if she fails to submit her PR , I will assign you this

@pranjal12-web you are assigned. there is already a feed back page there. make all of your changes there in your way make it interactive & also make the navbar changes as I have told you in the previous comment

Sure!!


Fix missing space between pipe and xargs

Pretty much that.
Thanks for maintaining this!

looks good; as long as passing travis-ci it's fine; the circle-ci I'm not sure how does it work


[Improvement-3369][api] Introduce interface for monitor, processinstance, queue service for clear code

What is the purpose of the pull request

Introduce interface for monitor, processinstance, queue service for clear code*

Brief change log

Add MonitorServiceImpl, ProcessInstanceServiceImpl, QueueServiceImpl class
Format code style
Remove unused code for clear code

Verify this pull request
This pull request is already covered by existing tests.

close by #4765


Compiler crash when declaring same library function as Int and Bool

Finally reproduced it in carc.in:
https://carc.in#/r/14t3
lib Terminal
  fun f_int = some_fun() : Int32
  fun f_bool = some_fun() : Bool
end

Terminal.f_bool()
Terminal.f_int() != 0

On my computer (ArchLinux, x86_64 ) it crashes the compiler too.

Good catch!
This will eventually give a compile error saying you can't declare a function twice.

Huh, so a Bool helper has to be moved to another module.
Maybe it is slightly off-topic, but is there some way to merge external lib functions and their helpers into one namespace?
Of cource I can create a Module, wrap every function from a lib there and then add helpers to this module, but the process of wrapping everything doesn't seem right, as Lib already wrapped it with a nice syntax.
Or lib functions usage together with their helpers isn't idiomatic at all?

Actually I can see this making sense as a feature:
lib LibPlatformSpecificWeirdness
  {% if flag?(:darwin) %}
    fun do_a = does_a_and_b(decides_on_this : Foo) : Foo
    fun do_b = does_a_and_b(decides_on_this : Foo) : Foo
  {% else %}
    fun do_a = does_a(does_not_decide_on_this : Foo) : Foo
    fun do_b = does_b(does_not_decide_on_this : Foo) : Foo
  {% end %}
end

No, I don't have a real world example of that at hand, but I find it very imaginable. Of course defining the same external symbol twice with different signatures should still error, across all libs.

@konovod What lib are you binding to?

Right now - (BearLibTerminal)http://foo.wyrd.name/en:bearlibterminal
But i think it can be useful for many libraries with not very complex API.

I see a Crystal lib as saying "This is what I import from the C library". Then one writes a nice wrapper around that.
We could maybe mix both, but I think it's maybe cleaner this way, as the two "worlds" are separate.
In this case your library seems very simple, where most (or all) functions can be called with integers and strings. In most cases libraries are more complex and provide structs and other types that need to be passed around.
One idea @waj had, and I kind of like it (but I'm not sure), is to allow adding fun to types. For example:
module Terminal
  @[Extern]
  fun delay = terminal_delay(period : Int32); end
end

But then we'd need to allow adding @[Link] attributes to modules and maybe classes.
Eventually I think we'll also allow marking structs as @[Extern] so you don't need to write too many wrappers, so adding these small conveniences is maybe good, though we'd have to write a full RFC detailing all of the aspects.

I see a Crystal lib as saying "This is what I import from the C library". Then one writes a nice wrapper around that.

Well, perhaps it is a right way, especially if libs will be generated automatically. But such nice syntax, enums and #to_unsafe made me think that lib itself can be a nice wrapper, at least for "lightweight" libraries. It just needs something like extends Lib in a Module or something like this.
On the other hand @[Extern] would solve the problem, even though i understand it is a big change.


More efficient memory backends

The memory backends are all implemented using heapq. This allows for some succinct code when using different crawl ordering, but it's less efficient than choosing more appropriate datastructures for each specific ordering (LIFO, FIFO, etc.)

IMO, it's a premature optimization. Most of the time people use memory backend just to check that scrapy+frontera+spider mix is working, and to debug issues in other backends. IMO, no one expects performance from memory backend, and it's not used in production. Any other use cases?

It's currently being used internally in Scrapinghub @sibiryakov and people are worrying about CPU and memory usage. If these are toy or test implementations it should be very clearly marked. I favour making some small changes so that they perform as you'd expect. I am not talking about low level optimizations, but things like using a list (instead of heap) for a LIFO.

It is also the superclass of the hcf backend, which is really an hybrid (it does not always store requests in hcf, it can also send requests directly to memory)

I rewrote memory LIFO and FIFO using deque in https://github.com/scrapinghub/frontera/pull/81

any ideas what can be more efficient for DFS and BFS than heapq?

Hi @sibiryakov , I think that list and sets/dicts (depending on the implementation) should be fine (or any other constant time access collection) but -- maybe this is a very silly question -- given that efficient implementations of DFS/BFS uses stacks/queues -- what's the main difference between FIFO/LIFO and DFS/BFS?

@wilfre DFS stands for Depth-first, and BFS is Breadth-first. If you could imagine a link graph, than DFS is crawls links having the biggest distance from root (seeds in our case) document, and BFS is opposite, the smallest. Efficient data structure for such problem is likely HEAP, arranged by distance, which is currently implemented in Frontera by means of heapq module.

Hi @sibiryakov, yes I think you're right if we would need to be prepared for any distance metric, or if the distance is somehow updated, but if we consider the distance as the number of hops from the root (please correct me if I'm wrong) we could use queues and stacks that are basically FIFO and LIFO datastructures like:
def bfs(G, s):
    P, Q = {s: None}, deque([s])    # Parents and FIFO queue
    while Q:
        u = Q.popleft()             # Constant-time for deque
        for v in G[u]:
            if v in P: continue     # Already has parent
            P[v] = u                # Reached from u: u is parent
            Q.append(v)
        # yield u
return P                            # Parent's tree

def dfs(G, s):
    U, S = set(), [s]               # Visited-set and list used as stack
    while S:
        u = S.pop()                 # LIFO pop
        if u in U: continue
        U.add(u)                    # Marking it as visited
        S.extend(G[u])              # Could also be Q.extend(G[u][::-1])
        yield u                     # Report u as visited

That's why I thought that maybe they were similar or share some similiraty. Please let me know if I'm mistaken.

@wilfre Thanks for your suggestion, it looks interesting.
Two points:

we don't have a link graph until the documents are crawled, therefore G will be updated on every iteration in our case.
your dfs implementation seems wrong, crawl should proceed from root to leafs, in your implementation it behaves more like bfs, iterating first pages within 1-hop distance.

@sibiryakov No problem, maybe a simple crawl example could help us validate the differences.
About the other points:
1: there's no need to have the complete graph G beforehand (it's being discovered by the DFS/BFS traversal), that doesn't change how BFS or DFS should behave because at each node (page) you can know which are the node's neighbors (or maybe I'm missing something).
2. it's actually this guy's implementation (http://www.apress.com/9781430232377 pag. 102 - iter_dfs -) but you can test it with this to get the feeling (you should see a complete branch before the other gets visited):
G = {1: [2, 3],
     2: [4], 4: [5], 5: [6], 6: [7], 7: [],
     3: [8], 8: [9], 9: [10], 10: [11], 11: [12], 12: []}
for elem in dfs(G, 1):
    print elem


Server error during vercel deployment

Theme error popping up along with server error during deployment

#97 Issue has been resolved by adding 'use client' in google analytics page


Arrow function style

Codecov Report

Merging #549 (24fbb44) into master (0277196) will not change coverage.
The diff coverage is n/a.

@@            Coverage Diff            @@
##            master      #549   +/-   ##
=========================================
  Coverage   100.00%   100.00%
=========================================
  Files           11        11
  Lines          133       133
  Branches        16        16
=========================================
  Hits           133       133

Obsoleted by #1420


vendor: sirupsen/logrus v1.7.0

full diff: https://github.com/sirupsen/logrus/compare/v1.6.0...v1.7.0
removes dependency on github.com/konsorten/go-windows-terminal-sequences
Features:

a new buffer pool management API has been added
a set of <LogLevel>Fn() functions have been added

LGTM


Handle ImageNotFound error with the :not_found handler

Fixes #101

Coverage increased (+0.007%) to 96.634% when pulling 31fdc43252a05f9ecace7aaaf9782550782d3ba7 on 404_not_found into a4c9189e13a53c3ccdc66aae02a0ea9796e58b22 on master.


How to plot a VolSourceEstimate with a discrete source space?

I have a pre-defined discrete source space and a corresponding leadfield for the subject, but no MRI data. There is following data for source space with 20001 dipoles:
pos_p: (20001, 3) locations
pos_nn: (20001, 3) orientations
pos_e: (39998, 3) triangles of the surface
With those I create source space using
vol_src = mne.setup_volume_source_space(None, pos={'rr': pos_p, 'nn': pos_nn},  surface = {'rr':pos_p, 'tris': pos_e})
which is of a kind 'discrete'.
Then I have a source estimate data of shape (20001, 2000) and a VolSourceEstimate
stc = mne.VolSourceEstimate(data, vertices=np.array(range(20001)), tmin=-1, tstep=0.001)
I try stc.plot(vol_src) and get ValueError: Source space must be volume type, got discrete.
Is there a way to plot a VolSourceEstimate with discrete source space? The source space includes a triangular surface edges, so shouldn't it be possible to plot it as a surface?

please provide a full code snippet to replicate the error with just a copy
paste

The source space includes a triangular surface edges, so shouldn't it be possible to plot it as a surface?

This must have come from some other software or custom definitions -- if you use MNE's setup_source_space the relationship to the FreeSurfer surfaces is automatically kept track of and you end up with a surface source space.
Is this an option for you?
If not, we can at least probably add basic vector plotting support, but it won't interpolate into a surface mesh properly. Another option is to figure out a way to morph your data onto the standard FreeSurfer surface definition for the subject...

Looking again, I think there is a misunderstanding. When you do:
vol_src = mne.setup_volume_source_space(..., surface = {'rr':pos_p, 'tris': pos_e})

you are setting the surface within which source space points must exist if setting up a volumetric grid. If you pass pos as a dict specifying positions, it's ignored. Maybe a docstring update would be useful here.
One thing we could do is add support to _Brain to allow passing surface=dict(...) to give the surface to plot onto directly. However, I think something that would probably work better for you is instead mapping your source space data onto the nearest FreeSurfer vertex locations for the given subject. Then many more nice functions will be available for you.
Do you have FreeSurfer reconstructions for your subject(s)?

Thank you for your answer. Now I understand why it didn't work.
Unfortunately, I don't have FreeSurfer reconstructions of the subject.

Can you upload your surface(s) and your STC somewhere? I can look into how difficult it is to hack into our _Brain object to allow a custom surface + discrete source space.

Closing--I think if using non-FreeSurfer data we can't currently help, but at some point if someone uses a discrete source space for example with sample I think we could figure out how to visualize it at least using a VectorSourceEstimate-like vector plot

I encountered exactly the same problem as @kpauski.
I have a resting state fMRI time series extracted from the brain areas in AAL atlas, i.e. a data matrix of shape (200, 116). I want to treat the fMRI time series as estimated EEG sources and take advantage of MNE toolbox to do some computation and visualization. So I did the following:
ts = np.random.randn(200, 116) # time series

atlas = nilearn.datasets.fetch_atlas_aal()
atlas_img = nibabel.load(atlas['maps'])
aal_coords = nilearn.plotting.find_parcellation_cut_coords(atlas_img)
pos = {'rr': aal_coords, 'nn': aal_coords}
src = mne.setup_volume_source_space(subject='sample', pos=pos, verbose=True)

vertices = [np.arange(len(aal_coords))]
stc = mne.VolSourceEstimate(ts.T, vertices, tmin=0.0, tstep=1.0, subject='sample')
stc.plot(src)

I got "ValueError: Source space must contain volume type, got discrete" when I tried to plot the source with "stc.plot(src)". While the VolSourceEstimate cannot be plotted with a discrete source space, what can a discrete source space, created by mne.setup_volume_source_space, be used for?

what can a discrete source space, created by mne.setup_volume_source_space, be used for?

Other operations of *SourceEstimate classes are supported, like cropping and such. And you have access to data and vertices. But indeed discrete source spaces are in generaly a bit limiting.
What I would suggest perhaps you could do instead is figure out how to map the AAL values into a volumetric source space. Basically all values within a given parcel could have the same value. Then you'd be able to plot the data.
Long-term in theory this would be a "label-ized" (or really "atlas-ized") source estimate data that we'd support plotting directly. It's on our roadmap but will be a bit of work. So in the meantime, upsampling the AAL atlas values to a VolSourceEstimate might be the best way to go.
Briefly, I'd try to get the AAL atlas into MGZ-like / FreeSurfer-compatible format for fsaverage so you can use setup_volume_source_space with the volume_label and mri arguments. This would get you a SourceSpaces where len(src) == 200, i.e., has one volume source space for each of the 200 AAL parcels. If you can get that far, we can work through how to create a VolSourceEstimate where the vertices are taken from the SourceSpaces with the data in the right place.


Stored active plugins to Foundation._activePlugins

Implemented to addition on registerPlugins and removal on unregisterPlugins. Corresponding to issue #7962.

Per @zurbchris's comment here, this is an unused property.


Export issue with 1.37.0, its taking forever to export all

I tried the below config to export all GC Objects and its running for ever and i forcefully killed it after 3 hrs. With version 1.35.0 it takes around 1.5 hrs for full export.
terraform {
    required_version = ">= 1.5.6"
  required_providers {
    genesyscloud = {
      source  = "mypurecloud/genesyscloud"
      version = "1.37.0"
    }
  }
}
resource "genesyscloud_tf_export" "export" {
  directory          = "./genesyscloud"
  split_files_by_resource     = true
  include_state_file = true
  log_permission_errors = true
  export_as_hcl = true
  enable_dependency_resolution  = true
}

If I use below to get the CGR it downloads quickly
terraform {
    required_version = ">= 1.5.6"
  required_providers {
    genesyscloud = {
      source  = "mypurecloud/genesyscloud"
      version = "1.37.0"
    }
  }
}
resource "genesyscloud_tf_export" "export" {
  directory          = "./genesyscloud"
  split_files_by_resource     = true
  include_state_file = true
  log_permission_errors = true
  export_as_hcl = true
  enable_dependency_resolution  = true
  include_filter_resources = ["genesyscloud_routing_queue","genesyscloud_routing_queue_conditional_group_routing"]
}

Please let me know additional details is needed or not.
terraform version 1.5.6

Hi @viniljose,
Thanks for bringing this to our attention, I will open a ticket for us to investigate this.
Regards,
Declan

Hi @viniljose
If you want to export the entire ORG, may be you dont need enable_dependency_resolution  = true , while we check why it is taking more time compared to versions 1.35.0, can you remove this attribute and see if you are still able to export all the GC objects.

Thank You @HemanthDogiparthi12 and @dginty4 for the quick reply
My use case is that I need to move code from one org to other org, I need the dependency for GC Objects so that it will help in order of creation of objects in other org.
I will remove 'enable_dependency_resolution = true' and see whether it helps

It works with out 'enable_dependency_resolution = true'  and ENABLE_STANDALONE_CGR=true
resource "genesyscloud_tf_export" "export" {
  directory          = "./genesyscloud"
  split_files_by_resource     = true
  include_state_file = true
  log_permission_errors = true
  export_as_hcl = true
  }

Hi @viniljose
Glad it worked for you. In order to troubleshoot further on the core problem with 'enable_dependency_resolution = true'
If possible can you help with below details

Can you open a care ticket and provide the logs for export with version 1.35.0 and the one which is long running in it.  Please do mention the forum thread in the details .
Can you try this ignore_cyclic_deps           = false and see if the export process finishes quick. if the process finishes/stops can you provide the export directory in a zip.

Need Both the above two options with 'enable_dependency_resolution = true'
Kind Regards
Hemanth

Sorry for the late reply.
I tried with 1.39.0 it is working without ENABLE_STANDALONE_CGR=true
I made enable_dependency_resolution  = true and downloaded all objects.
I will try with ENABLE_STANDALONE_CGR=true and update here, I feel issue is with this settings

I tried in 1.40.1 version with ENABLE_STANDALONE_CGR=true  and below settings and worked. So closing the issue

resource "genesyscloud_tf_export" "export" {
+ directory                    = "./genesyscloud"
+ enable_dependency_resolution = true
+ export_as_hcl                = true
+ id                           = (known after apply)
+ ignore_cyclic_deps           = true
+ include_state_file           = true
+ log_permission_errors        = true
+ split_files_by_resource      = true
}

@HemanthDogiparthi12 @dginty4


[Bug]: An error occurred while adding the reporter at path "d"

Version
28.0.2
Steps to reproduce
A minimal repo with the bug is available at ext/jest-28-bug-reporter-default:

git clone https://github.com/ext/jest-28-bug-reporter-default.git
npm install
npm test

The repo contains a jest preset which sets reporters: ["default"] and in this case it references itself with "preset": ".".
Expected behavior
Running jest should succeed.
Actual behavior

Error: An error occurred while adding the reporter at path "d".
Cannot find module 'd'

This can also be seen in the logs from Github actions from the above mentioned repo.
Additional context
As a workaround modifying jest-preset.js as following works but is not the way it is documented:
 module.exports = {
-	reporters: ["default"]
+	reporters: [["default"]]
 }

It also works if I don't use a preset at all and hardcode "reporters": ["default"] directly to package.json but that would defeat the purpose of using a preset.
The real preset I have the issue with does of course add additional reporters but as the bug is reproducible without them they are left out.
Environment
System:
    OS: Linux 5.10 Gentoo Linux
    CPU: (24) x64 AMD Ryzen 9 3900X 12-Core Processor
  Binaries:
    Node: 16.14.1 - /usr/bin/node
    Yarn: 1.22.10 - /usr/bin/yarn
    npm: 8.6.0 - /usr/bin/npm
  npmPackages:
    jest: ^28.0.2 => 28.0.2

Thanks for report and reproduction.
Looking at the code one can see that currently reporters option is normalized before merging in options from preset:
https://github.com/facebook/jest/blob/bf88f76864fe98ec45ae5035762a16e2dd03120a/packages/jest-config/src/normalize.ts#L539-L549
Hence a reporter defined in preset is not normalized, but it should be. Easy to fix. I will do.

https://github.com/facebook/jest/releases/tag/v28.0.3


Mini Player Constantly expands.

For some reason every time I open the mini player it enlarges infinitely... making it completely unusable. It used to work great, now it doesn't work at all.

Duplicate of #2269

This happens to me also. What version will this be released in?


Ref graphviz

Pull Request Summary
Graphviz was not included in the environment yaml causing CI to fail
Key changes
Notable points that this PR has either accomplished or will accomplish.

[x] Add graphviz to yaml files

Associated Issue(s)

[x] #272

Pull Request Checklist

[x] Issue(s) raised/addressed and linked
[x] Includes appropriate unit test(s)
[x] Appropriate docstring(s) added/updated
[x] Appropriate .rst doc file(s) added/updated
[ ] PR is ready for review

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 83.93%. Comparing base (385ee66) to head (70a40b0).
Report is 15 commits behind head on main.

Additional details and impacted files

All CI now passes; bypassing reviews to merge.


[bug] Talos is installed to the wrong disk

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior
When adding a machine to an existing cluster which has more than one disk attached, Talos will be installed to the first disk listed in the dropdown even if I select another one.
Expected Behavior
Talos is installed to the disk that I selected in the dropdown
Steps To Reproduce

Boot a host with multiple disks to an omni-enabled image
Create a cluster
After cluster is created, add the new machine using the "Add Machines" button
Select a disk other than the first (default) one
Observe the talos installier picking the first disk as target

What browsers are you seeing the problem on?
Chrome
Anything else?
The issue was observed on a RPI 4b with a sdcard and ssd (over usb) attached. The initial omni image has been written to the sdcard and the RPI is configured to boot from usb first, then sdcard.
The ssd should have been the disk where Talos was installed to, but actually it has been installed to the sdcard, leaving the ssd untouched

dmesg excerpt
14/04/2023 20:02:09 [talos] upgrade request received: "ghcr.io/siderolabs/installer:v1.3.7"
14/04/2023 20:02:09 OK [/machine.MachineService/Upgrade] 10.49661ms unary Success (:authority=[masked]:50000;content-type=application/grpc;grpc-accept-encoding=gzip;runtime=Talos;user-agent=grpc-go/1.53.0)
14/04/2023 20:02:09 [talos] task loadConfig (1/1): failed: failed to receive config via maintenance service: maintenance service failed: context canceled
14/04/2023 20:02:09 [talos] phase config (6/7): failed
14/04/2023 20:02:09 [talos] initialize sequence: failed
14/04/2023 20:02:09 [talos] maintenanceUpgrade sequence: 8 phase(s)
14/04/2023 20:02:09 [talos] phase containerd (1/8): 1 tasks(s)
14/04/2023 20:02:09 [talos] task startContainerd (1/1): starting
14/04/2023 20:02:09 [talos] service[containerd](Preparing): Running pre state
14/04/2023 20:02:09 [talos] service[containerd](Preparing): Creating service runner
14/04/2023 20:02:11 [talos] service[containerd](Running): Process Process(["/bin/containerd" "--address" "/system/run/containerd/containerd.sock" "--state" "/system/run/containerd" "--root" "/system/var/lib/containerd"]) started with PID 1615
14/04/2023 20:02:12 [talos] service[containerd](Running): Health check failed: rpc error: code = DeadlineExceeded desc = context deadline exceeded
14/04/2023 20:02:15 [talos] service[containerd](Running): Health check successful
14/04/2023 20:02:15 [talos] task startContainerd (1/1): done, 6.043656384s
14/04/2023 20:02:15 [talos] phase containerd (1/8): done, 6.059456385s
14/04/2023 20:02:15 [talos] phase verifyDisk (2/8): 1 tasks(s)
14/04/2023 20:02:15 [talos] task verifyDiskAvailability (1/1): starting
14/04/2023 20:02:15 [talos] task verifyDiskAvailability (1/1): done, 7.400927ms
14/04/2023 20:02:15 [talos] phase verifyDisk (2/8): done, 22.068319ms
14/04/2023 20:02:15 [talos] phase upgrade (3/8): 1 tasks(s)
14/04/2023 20:02:15 [talos] task upgrade (1/1): starting
14/04/2023 20:02:15 [talos] task upgrade (1/1): performing upgrade via "ghcr.io/siderolabs/installer:v1.3.7"
14/04/2023 20:02:15 [talos] pulling "ghcr.io/siderolabs/installer:v1.3.7"
14/04/2023 20:02:40 2023/04/14 18:02:40 running Talos installer v1.3.7
14/04/2023 20:02:40 XFS (mmcblk0p3): Mounting V5 Filesystem
14/04/2023 20:02:40 2023/04/14 18:02:40 machine configuration missing, skipping validation
14/04/2023 20:02:41 XFS (mmcblk0p3): Ending clean mount
14/04/2023 20:02:41 XFS (mmcblk0p3): Unmounting Filesystem
14/04/2023 20:02:41 2023/04/14 18:02:41 pre-flight checks disabled, as host Talos version is too old
14/04/2023 20:02:41 XFS (mmcblk0p3): Mounting V5 Filesystem
14/04/2023 20:02:41 XFS (mmcblk0p3): Ending clean mount
14/04/2023 20:04:17 [talos] renew failed {"component": "controller-runtime", "controller": "network.OperatorSpecController", "operator": "dhcp4", "error": "got an error while processing the request: no matching response packet received", "link": "eth0"}
14/04/2023 20:06:11 XFS (mmcblk0p3): Unmounting Filesystem
14/04/2023 20:06:11 2023/04/14 18:06:11 preserved contents of "BOOT": 69912683 bytes
14/04/2023 20:06:11 2023/04/14 18:06:11 preserved contents of "META": 1055 bytes
14/04/2023 20:06:13 2023/04/14 18:06:13 preserved contents of "STATE": 101942 bytes
14/04/2023 20:06:13 2023/04/14 18:06:13 resetting partition table on /dev/mmcblk0
14/04/2023 20:06:13 2023/04/14 18:06:13 partitioning /dev/mmcblk0 - EFI "105 MB"
14/04/2023 20:06:13 2023/04/14 18:06:13 created /dev/mmcblk0p1 (EFI) size 204800 blocks
14/04/2023 20:06:13 2023/04/14 18:06:13 partitioning /dev/mmcblk0 - BIOS "1.0 MB"
14/04/2023 20:06:13 2023/04/14 18:06:13 created /dev/mmcblk0p2 (BIOS) size 2048 blocks
14/04/2023 20:06:13 2023/04/14 18:06:13 partitioning /dev/mmcblk0 - BOOT "1.0 GB"
14/04/2023 20:06:14 2023/04/14 18:06:13 created /dev/mmcblk0p3 (BOOT) size 2048000 blocks
14/04/2023 20:06:14 2023/04/14 18:06:13 partitioning /dev/mmcblk0 - META "1.0 MB"
14/04/2023 20:06:14 2023/04/14 18:06:13 created /dev/mmcblk0p4 (META) size 2048 blocks
14/04/2023 20:06:14 2023/04/14 18:06:13 partitioning /dev/mmcblk0 - STATE "105 MB"
14/04/2023 20:06:14 2023/04/14 18:06:13 created /dev/mmcblk0p5 (STATE) size 204800 blocks
14/04/2023 20:06:14 2023/04/14 18:06:13 partitioning /dev/mmcblk0 - EPHEMERAL "0 B"
14/04/2023 20:06:14 2023/04/14 18:06:13 created /dev/mmcblk0p6 (EPHEMERAL) size 86016 blocks
14/04/2023 20:06:14 2023/04/14 18:06:14 formatting the partition "/dev/mmcblk0p1" as "vfat" with label "EFI"
14/04/2023 20:06:14 2023/04/14 18:06:14 zeroing out "/dev/mmcblk0p2"
14/04/2023 20:06:14 2023/04/14 18:06:14 formatting the partition "/dev/mmcblk0p3" as "xfs" with label "BOOT"
14/04/2023 20:06:16 2023/04/14 18:06:16 zeroing out "/dev/mmcblk0p4"
14/04/2023 20:06:16 2023/04/14 18:06:16 zeroing out "/dev/mmcblk0p5"
14/04/2023 20:06:19 2023/04/14 18:06:19 zeroing out "/dev/mmcblk0p6"
14/04/2023 20:06:19 XFS (mmcblk0p3): Mounting V5 Filesystem
14/04/2023 20:06:19 XFS (mmcblk0p3): Ending clean mount
14/04/2023 20:06:25 XFS (mmcblk0p3): Unmounting Filesystem
14/04/2023 20:06:25 2023/04/14 18:06:25 restored contents of "BOOT"
14/04/2023 20:06:25 2023/04/14 18:06:25 restored contents of "META"
14/04/2023 20:06:28 2023/04/14 18:06:28 restored contents of "STATE"
14/04/2023 20:06:28 XFS (mmcblk0p3): Mounting V5 Filesystem
14/04/2023 20:06:28 XFS (mmcblk0p3): Ending clean mount
14/04/2023 20:06:28 2023/04/14 18:06:28 copying /usr/install/arm64/vmlinuz to /boot/B/vmlinuz
14/04/2023 20:06:28 2023/04/14 18:06:28 copying /usr/install/arm64/initramfs.xz to /boot/B/initramfs.xz
14/04/2023 20:06:29 2023/04/14 18:06:29 writing /boot/grub/grub.cfg to disk
14/04/2023 20:06:29 2023/04/14 18:06:29 executing: grub-install --boot-directory=/boot --efi-directory=/boot/EFI --removable --target=arm64-efi /dev/mmcblk0
14/04/2023 20:06:29 Installing for arm64-efi platform.
14/04/2023 20:06:33 Installation finished.  This is my cluster.experimental.yaml:
kind: Cluster
name: experimental-2023-04-10
kubernetes:
  version: v1.26.4
talos:
  version: v1.3.7
patches:
  - name: kubelet-tls-bootstrap
    file: patches/kubelet-tls-bootstrap.yaml
  - name: allow-scheduling-on-controlplanes
    file: patches/allow-scheduling-on-controlplanes.yaml
---
kind: ControlPlane
machines:
  - 77902500-68a6-0706-0025-9077a6680e0f
---
kind: Workers
machines: []
---
kind: Machine
name: 77902500-68a6-0706-0025-9077a6680e0f
install:
  disk: /dev/sdb

I suppose, you've used an iso to create the cluster, correct?
From my observations, it is not necessarily the first disk in the dropdown (as opposed to my original post), but rather the one where the installation media lives as long as it is not an iso.
It seems the installation process for img (not iso) installation media is broken in Omni.
I have an sd card and a usb ssd.
requirements:

Talos is installed to ssd
System extension drbd is installed and loaded on my RPI 4 workers.

sd card:

flashed with the omni image for a Raspberry Pi 4b (omnictl download rpi_4)
reported as /dev/mmcblk0

usb ssd:

is zeroed (diskutil zeroDisk short /dev/diskX)
is reported as /dev/sda
is set to be the install disk

Upon cluster creation, Omni + Talos "installs" the cluster talos version (actually same version number) to /dev/mmcblk0 but when I detach the usb ssd and reboot the machine, it complains about missing the install disk /dev/sda (usb ssd) even though it clearly is booting from the altered sd card install since the ssd is empty.
To me, it looks like the info about the install disk is lost at some point during installation.
Maybe this all works as expected and it's just me who is confused about the inner workings of Omni + Talos, but it is definitely confusing to me when the specified install disk remains empty and the specified system extensions don't get installed.
My current workaround (on RPI 4):
With the help of https://github.com/pftf/RPi4, I managed to boot the RPI to the arm64 iso and this time the installation succeeded as expected (correct disk). This solution comes with its own drawbacks, but at least the installer installs Talos to the correct disk and what's more import: also installs the desired system extension drbd which is the entire reason behind this exercise.
I'd rather install the dedicated image meant for the respective platform instead of running this frankenstein-like setup, but it looks like this is currently not possible otherwise, with a Raspberry Pi at least: https://github.com/siderolabs/omni-feedback/issues/1#issuecomment-1434442259

Hi,
The behavior you see is the details of how Talos works.
It was always like that: if Talos boots from the disk image it won't even run installation flow and so it will ignore the install config completely, not picking the right disk.
ISO works because in that case Talos is not installed anywhere.
I agree that it is not a great UX we have here. I think we had some discussions around that, we might address that eventually.
Right now the only way around it is to use ISO or write Talos disk image to the SSD.

Thanks for the clarification.
I don't know your issue workflow in this repo, but this can be closed from my point of view.

In my example above, I have two disks:

/dev/sdb - the SD card
/dev/sda - the SSD disk

I install Talos OS Generic image (amd64) to /dev/sdb SD card via Balena Etcher on macOS. The Linux equivalent is:
wget https://<PUBLIC_URL>/metal-amd64-v1.3.6-omni-<ORG>.tar.gz
tar zxvf metal-amd64-v1.3.6-omni-<ORG>.tar.gz
dd if=disk.raw of=/dev/sdb conv=fdatasync

The host is configured to boot from /dev/sdb by default. Everything stored on /dev/sdb is Talos-related - I consider it semi-ephemeral. FWIW: https://www.talos.dev/v1.4/introduction/system-requirements/#storage

I ensure /dev/sda is wiped (no partition table & no flags) & then install csi-driver-lvm (I have an upcoming PR that makes it work with Talos). I then let csi-driver-lvm manage /dev/sda for persistent workloads. All data that I want to survive Talos upgrades is kept on /dev/sda.

I am not sure how the above would need to be adapted to RPI & the drbd extension. I am not sure if this is useful - https://www.talos.dev/v1.4/talos-guides/configuration/system-extensions/#authoring-system-extensions - but it reads reasonably well. cc @frezbo re https://github.com/siderolabs/extensions/tree/main/container-runtime/gvisor#readme

Issues which I have opened & have been resolved - e.g. https://github.com/siderolabs/omni-feedback/issues?q=is%3Aissue+author%3Agerhard+is%3Aclosed - I close them myself.

With talos 1.5, there is boot asset generation.
How can we generate a custom omni talos image?

With talos 1.5, there is boot asset generation.
How can we generate a custom omni talos image?

In several weeks we'll offer an integration of Omni with Talos Linux Image Factory which will make things even easier.
You can still generate initial boot image for Omni manually using the documentation on boot asset generation passing the custom args, but Omni doesn't support custom installers yet. Talos Linux Image Factory integration will fix all of that.

Hey @smira
Talos Linux Image Factory (hosted at https://factory.talos.dev) is available and if I understand it correctly, I just need to fill the  form and pass my omni kernel args to be able to obtain the RPi image with drbd enabled. Then, I can flash the image to disk and it should work.
Disclaimer: The below part is just what I'm guessing, and I could be totally off base. Please, keep that in mind.
The unclear part:
Do I need to redo the manual steps on each Talos Linux version upgrade, i.e., flashing the image to disk manually?
Or Can I use omnictl somehow to skip the manual flashing step?
The potentially insecure part:
https://factory.talos.dev is public and does not require authentication. If I pass my omni kernel args, they are only "secured" by the schematic id.
Is there a way make Talos Linux Image Factory more secure?

Talos Linux Image Factory is not yet integrated with Omni.
Yes, you can use disk images generated with Talos Linux Image Factory with Omni, but they will be reverted to "vanilla" Talos after Talos upgrade (Omni kernel args will stay, but system extensions will be wiped).
We expect full integration to be available soon.

The potentially insecure part:
https://factory.talos.dev/ is public and does not require authentication. If I pass my omni kernel args, they are only "secured" by the schematic id.
Is there a way make Talos Linux Image Factory more secure?

Please see https://www.talos.dev/v1.5/learn-more/image-factory/#security

Talos Linux Image Factory is not yet integrated with Omni.

Ok thanks 👍. Any chance you could roughly share how the integration will look like with respect to omnictl?

Please see https://www.talos.dev/v1.5/learn-more/image-factory/#security

So, the schematic ID can only be guessed by brute-forcing which is practically speaking not feasible, but what if the schematic ID get's leaked?
Is there a way to invalidate the id?
Can we upload a slightly different schematic (add a label) to "recreate" the previous schematic just with a new ID?
I know this is slightly off-topic with respect to the original issue, but as I understand it, Talos Linux Image Factory is the solution to generate disk images with system extensions without the need to "install" anything.
On another note:
From https://www.talos.dev/v1.5/learn-more/image-factory/#running-your-own-image-factory

Image Factory performs HTTP redirects to the public registry endpoint for installer images, so the public endpoint should be available to Talos Linux machines to pull the installer images.

With Omni in mind, can we deploy an Image Factory instance in a private network and have the cluster nodes download the installer image from the registry as long as the cluster nodes can reach the private instance?
Oh, and another question: Schematic ID generation is based on the schematic content. Does it mean each Image Factory instance will generate the same ID given the same content or can we provide some sort of "seed key"?


update bateeq-module for quantity & price correction

Coverage increased (+1.2%) to 33.178% when pulling 9c534f5f443f0c78185a3e74ca7d952fddf0cf07 on AchmadSetiaji:dev into 62484d7a595b717f7ab407491d94e7d08435d2ac on danliris:dev.


const copy folding spec + multi.py behavior [pr]

The hack in copy_to_device can't stay. It doesn't belong in ops.
This diff includes the spec for rewriting COPY(CONST) -> CONST, as it exists in ops_folding.
The extra check for "is const" in ops only exists for multi. Sadly multi calls contiguous on all shards:
return MultiLazyBuffer([lb if lb.is_unrealized_unmasked_const() else lb.contiguous(allow_buffer_view=False) for lb in sharded_lbs], axis)

The scheduler respects contiguous and will dutifully store the thing you call contiguous on.
See how if we delete "early const folding" in copy_to_device, this contiguous prevents further folding:

vs if it was just return MultiLazyBuffer(sharded_lbs, axis) all MUL 0s would fold until we end up with a NOOP:

Is the extra is_const check worth keeping around?

Why does multi have to call contiguous?

agree that contiguous has to go, it's way too aggressive.
benchmarks fails when I delete it:
https://github.com/tinygrad/tinygrad/actions/runs/12536417701/job/34959405143#step:20:11
test_multitensor doesn't give a signal for why. The only test that failed was test_shard_memory, expecting a VIEW of a shard (on the same device!) to be realized.
  File "/Users/qazal/code/tinygrad/test/test_multitensor.py", line 698, in test_shard_memory
    assert lb is lb.base, f"{lb} {t.device}"
           ^^^^^^^^^^^^^
AssertionError: UOp(Ops.SHRINK, dtypes.float, arg=((0, 4), (0, 16)), src=(
  UOp(Ops.VIEW, dtypes.float, arg=ShapeTracker(views=(View(shape=(16, 16), strides=(16, 1), offset=0, mask=None, contiguous=True),)), src=(
    UOp(Ops.BUFFER, dtypes.float, arg=(6, 256), src=(
      UOp(Ops.DEVICE, dtypes.void, arg='LLVM', src=()),)),)),)) ('LLVM', 'LLVM:1', 'LLVM:2', 'LLVM:3')

I don't think some of multi's tests are well thought through, neither do they give a comprehensible feedback loop for why benchmarks failed.


Make IServiceLocator use Interlocked.Exchange/Compare etc for threading

https://github.com/reactivemarbles/Locator/blob/9f2f2941107f6d81b0ab77d5e66a2a489357066a/src/ReactiveMarbles.Locator/ServiceLocator.cs#L28

Resolved via #13


feat: Enable to force PIXI_ARCH for installation

On Apple Silicon, one might want to force installing the x86_64 version of pixi. Using the PIXI_ARCH variable, this can now be done using:
export PIXI_ARCH=x86_64 && curl -fsSL https://pixi.sh/install.sh | bash

My use case is to run pixi on GitLab CI saas-macos-medium-m1 runners.
This would make it easier to install pixi for aarch64 or x86_64.

Wouldn't running one simple curl command be easier in your case?

Hmm, I personally think the readme change is a bit too prominent... As if we actually recommend doing this instead of just using the regular build.

Maybe something like
!!! note "Using x86 builds on M1"
    If you really need to use the x86 build on M1 (not recommended), you can also do the following:
    ...

I noticed that https://pixi.sh/install.sh doesn't contain that change yet even if 0.19.0 (and 0.19.1) has been released.
When is it updated?


Görli Launch

Launch Checklist

[x] Acquire 10+ Gorli ETH
[ ] Coordinate with app devs on migration plans to new contract
[x] https://github.com/farcasterxyz/contracts/issues/28
[ ] https://github.com/farcasterxyz/contracts/issues/18
[x] https://github.com/farcasterxyz/contracts/issues/19
[ ] Make contract pause-able with an admin key
[x] Finish contract renaming
[ ] AccountRegistry: allow setting URL
[ ] Deploy new contracts on Görli

Also worth considering for gas savings: a contract call that allows a single transaction to acquire an identity and username

Closed, tracking as milestone instead


Make female/male choice in argparse ed_csv_to_vcf.py

Argument should be choice female/male only, nothing else.
Perhaps also improve if/else statement in code

How to handle VCF naming if refset is the same (VCF name will be similar)


Revert "Use clang's effective llvm triple for IR generation (#10211)"

This reverts commit 6c9977d34e85f445dfdb657df62a3bb20add3c03.
WatchOS debugging is broken due to this change. It seems the jit does not like
thumb relocations ...
rdar://32986409

@swift-ci Please test

Build failed
Jenkins build - Swift Test Linux Platform
Git Commit - a5018b9396c3fd07116eb4d789e75d9cb97f0e4c
Test requested by - @aschwaighofer

Timeout?

@swift-ci Please test linux platform


Datetime notation incorrect

Datetime notation in the main screen is incorrect:

@Krikke99 this is actually a string that shows exactly what the pump has internally. I am working on an update this week that will also show the time in your time zone. The JSON Lib I was using was converting date strings to local time before I ever saw them.  I don't have the raw pump data that I display and I am working to displaying it in your computers native time format and time zone. so you could look at someone's data and it would make sense I am not there yet. If you can tell me what you would like to see there please open another issue or comment on this one.

@paul1956 i just looked at a json file i get from a python program, the timezone is correct. Only the notation is not.
"lastSensorTSAsString": "2022-08-03T14:51:00.000Z"
I don't know how the notation is in other regions, in Belgium it looks like this: 03-08-2022 14:51
These are my windows settings:

That is a string directly from pump. It's not a Date but am thinking it's confusing and will eventually convert all the dates to local culture.

Fixed in CareLinkv<IP_ADDRESS>x64
Please open new issue if the issue persists


PMM Snowfakery (existing Programs and Services) enhancements

What package(s) are you trying to populate with fake data?
This project focuses on products developed and maintained by Salesforce and the Salesforce Open Source Commons.

NPSP (optional)
Program Management Module

What is the scenario you're trying to support with fake data?
I want to demonstrate realistic synthetic data in PMM
What do you think is involved in this recipe?
Do you have a partial recipe to share? What objects or fields do you think are most important?
The proposed PMM recipe file (existing programs and services) does not yet incorporate Service Schedules and Program Cohorts.  Incorporating these objects would be a worthwhile improvement on the MVP version.

[ ] Determine requirements for how Program Cohorts and Service Schedules should be set up
[ ] Determine whether they should be extracted from the org or created programmatically
[ ] Revise existing recipe to incorporate these two objects and their related objects
[ ] Test recipe

Additional context

New recipe request. Need to assess viability of creating service schedules re: PMM flow and determine path forward.


Add TODO lists support for Mmark (*.mmark files)

See #2022
See https://github.com/shurcooL/github_flavored_markdown/commit/2b74a5b

This issue has been automatically marked as stale because it has not been commented on for at least four months.
The resources of the Hugo team are limited, and so we are asking for your help.
If this is a bug and you can still reproduce this error on the master branch, please reply with all of the information you have about it in order to keep the issue open.
If this is a feature request, and you feel that it is still valuable, please open a proposal at https://discuss.gohugo.io/.
This issue will automatically be closed in four months if no further activity occurs. Thank you for all your contributions.

Note/Update: This issue is marked as stale, and I may have said something earlier about "opening a thread on the discussion forum". Please don't.
If this is a bug and you can still reproduce this error on the latest release or the master branch, please reply with all of the information you have about it in order to keep the issue open.
If this is a feature request, and you feel that it is still relevant and valuable, please tell us why.

With Mmark deprecated, is this still necessary?


UI disappears abruptly

The app UI disappears abruptly. Uninstalling and Re-Installing didn't work either.

I am experiencing the same, especially when clicked to download more than one course. It seems it gots stuck on attachment on one of the courses and then immediately fails completely, I had hard time to get rid of the frozen GUI, force quit didn't help, had to restart computer.

I have the same issue, do you guys know how to fix this ?

It was my mistake actually. I had set the download location to an external disk but that very disk got disconnected due to loose connection and I didn't notice it at first. When I fixed that loose connection issue, things were back to normal almost instantly. Turns out the uninstalling and reinstalling wasn't even required. "CHECK YOUR DOWNLOAD LOCATION AND MAKE SURE IT IS ACCESSIBLE BY UDELER" and your problem will be resolved.

It's funny, but I have set my location to my local drive and I have the same issue.


Add ground_speed to AgContext

When merged, we will need to update existing datasets to include this field.


"e" key opens directory tab instead navigation

probably it's a feature, but I use "e" as navigation through long filenames not for opening tabs
how to get back previous behaviour of "e" key ?
Thanks.

Stick this in your vimrc let NERDTreeMapOpenExpl=""

thanks


Add option to change svg render colors

It would be great to have an option to set the background and line render color of the diagrams. The option to set these colors to transparent would also be great, so you can set the background to be transparent. Optimally even a different setting for dark and light mode.
Currently the rendered diagrams look a bit out of place in dark themes, or any theme which doesn't use white as a background color.

Looks great, thanks, this solves the issue!


Issue 219

introduce decodeURLComponent function
fix extraction of scheme and host according to rfc3986
add tests for url's functions
introduce new class StringView as synonym to the std::experimental::string_view.

Also need to test performance in case when most of input strings are empty or short.
(Typical case: LinkURL field in test.visits; or result of extractURLParameter with rare parameter.)
Things could depend on inlining of your functions (your functions are not inlined).

Extra allocations inside loop was removed.


Initialize numpyro NUTS with SVI

Hi there, great initial work wrapping numpyro and pyro into a more user friendly interface!  I'm having an issue with a few simple models where the numpyro backend gives me the following error:
Cannot find valid initial parameters. Please check your model again.
It seems to occur when there are many predictors in the formula.
Pyro sampling and SVI both work fine for this model with the default Cauchy beta priors.  Any thoughts on better initializing numpyro NUTS with SVI or perhaps using maximum a posteriori estimates?
It's tough to figure out what exactly is causing MCMC to immediately fail but I'm assuming it's the initial starting values.  Full traceback:
RuntimeError                              Traceback (most recent call last)
<ipython-input-185-9da937b2eeba> in <module>
----> 1 fit = model.fit(backend=numpyro, seed=8877, iter=1000, warmup=500)

/opt/conda/lib/python3.6/site-packages/brmp/__init__.py in fit(self, algo, **kwargs)
    173         """
    174         assert algo in ['prior', 'nuts', 'svi']
--> 175         return getattr(self, algo)(**kwargs)
    176
    177     def nuts(self, iter=10, warmup=None, num_chains=1, seed=None, backend=numpyro_backend):

/opt/conda/lib/python3.6/site-packages/brmp/__init__.py in nuts(self, iter, warmup, num_chains, seed, backend)
    200         """
    201         warmup = iter // 2 if warmup is None else warmup
--> 202         return self.run_algo('nuts', backend, iter, warmup, num_chains, seed)
    203
    204     def svi(self, iter=10, num_samples=10, seed=None, backend=pyro_backend, **kwargs):

/opt/conda/lib/python3.6/site-packages/brmp/__init__.py in run_algo(self, name, backend, df, *args, **kwargs)
    154         data = self.model.encode(df) if df is not None else self.data
    155         assets_wrapper = self.model.gen(backend)
--> 156         return assets_wrapper.run_algo(name, data_from_numpy(backend, data), *args, **kwargs)
    157
    158     def fit(self, algo='nuts', **kwargs):

/opt/conda/lib/python3.6/site-packages/brmp/__init__.py in run_algo(self, name, data, *args, **kwargs)
     75
     76     def run_algo(self, name, data, *args, **kwargs):
---> 77         samples = getattr(self.backend, name)(data, self.assets, *args, **kwargs)
     78         return Fit(self.model.formula, self.model.metadata,
     79                    self.model.contrasts, data,

/opt/conda/lib/python3.6/site-packages/brmp/numpyro_backend.py in nuts(data, assets, iter, warmup, num_chains, seed)
     86     # `num_chains` > 1 to achieve parallel chains.
     87     mcmc = MCMC(kernel, warmup, iter, num_chains=num_chains)
---> 88     mcmc.run(rng, **data)
     89     samples = mcmc.get_samples(group_by_chain=True)
     90

/opt/conda/lib/python3.6/site-packages/numpyro/infer/mcmc.py in run(self, rng_key, extra_fields, collect_warmup, init_params, *args, **kwargs)
    639         if self.num_chains == 1:
    640             states_flat = self._single_chain_mcmc((rng_key, init_params), collect_fields, collect_warmup,
--> 641                                                   args, kwargs)
    642             states = tree_map(lambda x: x[np.newaxis, ...], states_flat)
    643         else:

/opt/conda/lib/python3.6/site-packages/numpyro/infer/mcmc.py in _single_chain_mcmc(self, init, collect_fields, collect_warmup, args, kwargs)
    582         rng_key, init_params = init
    583         init_state, constrain_fn = self.sampler.init(rng_key, self.num_warmup, init_params,
--> 584                                                      model_args=args, model_kwargs=kwargs)
    585         if self.constrain_fn is None:
    586             constrain_fn = identity if constrain_fn is None else constrain_fn

/opt/conda/lib/python3.6/site-packages/numpyro/infer/mcmc.py in init(self, rng_key, num_warmup, init_params, model_args, model_kwargs)
    409                 rng_key, rng_key_init_model = np.swapaxes(vmap(random.split)(rng_key), 0, 1)
    410             init_params_, self.potential_fn, constrain_fn = initialize_model(
--> 411                 rng_key_init_model, self.model, *model_args, init_strategy=self.init_strategy, **model_kwargs)
    412             if init_params is None:
    413                 init_params = init_params_

/opt/conda/lib/python3.6/site-packages/numpyro/infer/util.py in initialize_model(rng_key, model, init_strategy, *model_args, **model_kwargs)
    413     if not_jax_tracer(is_valid):
    414         if device_get(~np.all(is_valid)):
--> 415             raise RuntimeError("Cannot find valid initial parameters. Please check your model again.")
    416     return init_params, potential_fn, constrain_fun
    417

RuntimeError: Cannot find valid initial parameters. Please check your model again.

Thanks for reporting this. I guess you're correct, and that we maybe we need to think more about initialization strategies at some point. If possible, could you share a simple example that reproduces the problem, so we might check this isn't some other bug. Thanks.

I realized part of the problem here is that brms automatically centers data whereas here we need to either specify more accurate priors or standardize the data before fitting with numpyro. Nevertheless, the pyro backends do work with non-centered columns in the example below.  Agreed that it will be good to think through some initialization strategies.
import brmp
from brmp import brm
from brmp.numpyro_backend import backend as numpyro
from brmp.pyro_backend import backend as pyro
import pandas as pd

df = pd.read_csv('https://stats.idre.ucla.edu/stat/data/hdp.csv')
df = df.apply(lambda x: pd.factorize(x)[0] if np.issubdtype(x.dtype, np.number) is False else x) # factorize some columns
df['remission'] = df['remission'].astype(np.int)
df['DID'] = df['DID'].astype('category')
model = brm('remission ~ IL6 + CRP + CancerStage + LengthofStay + Experience + FamilyHx + SmokingHx + Sex + CancerStage + LengthofStay + WBC + BMI + (1 | DID)', df = df, family = brmp.family.Binomial(num_trials=1))
fit = model.fit(backend=numpyro, seed=8877, iter=1000, warmup=500) # fails
fit = model.fit(backend=pyro, seed=8877, iter=1000, warmup=500) # works
fit = model.fit(algo='svi', seed=8877, iter=10000, num_samples=1000) # works


Fix ocs performance latency recording rules

This PR fixes the typos in the ocs performance recording rules for the cluster latency.
Signed-off-by: Anmol Sachan<EMAIL_ADDRESS>Tested the rules on the cluster:

@umangachapagain @jarrpa Please review.


Black Image returned when cropping large images with higher resolution especially raw camera photos, tried it with a (3456 * 4608) . It doesn't crash though.

Describe the bug
A clear and concise description of what the bug is.
To Reproduce
Steps to reproduce the behavior:

Go to '...'
Click on '....'
Scroll down to '....'
See error

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: [e.g. iOS]
Browser [e.g. chrome, safari]
Version [e.g. 22]

Smartphone (please complete the following information):

Device: [e.g. iPhone6]
OS: [e.g. iOS8.1]
Browser [e.g. stock browser, safari]
Version [e.g. 22]

Additional context
Add any other context about the problem here.

galleryLauncher.launch(
ImagePicker.with(this@Chats)
.crop()
.galleryOnly()
.setMultipleAllowed(true)
.cropFreeStyle()
.galleryMimeTypes( // no gif images at all
mimeTypes = arrayOf(
"image/png",
"image/jpg",
"image/jpeg"
)
)
.createIntent()
)

Same issue appears at my end as well when clicking picture from camera, in crop screen black screen appears for cropping and gives the same as file. Can you suggest wat needs to be done.

@Drjacky When I am taking picture from the camera and going to the crop option it only shows a black screen.

Is it a big picture in size and width/height matters @amitkumartiwaridis.
__
@DevLuke67 please add description and/or edit title

@DevLuke67 It's an issue with the used internal Image Cropper library: https://github.com/Yalantis/uCrop
Please open the ticket there.


Volume plot regression with ParallelPerRank resampling

Describe the bug
Recent volume plot regressions after PR #19642.
Parallel results of the volume_33 test, which is testing ParallelPerRank resampling option on multi_ucd3d.silo.
https://visit-dav.github.io/dashboard/2024-07-12-22:00/pascal_trunk_parallel/volume_33.html
I believe it is showing the per-rank division.
I ran the test with the DUMP option turned on in avtVisItVTKRenderer.C and avtVisItVTKRenderFilter.C of the volume plot, to get intermediate images and image data.
This image shows a different view of the same test, along with the per-rank intermediate image data that was dumped.

I have tried to determine why the results after the PR are showing what appears to be lack of correct compositing between the two ranks.  Best I can determine based on -dump of this particular test before the PR and after: ghost-zone communication isn't happening. Before PR (I have a checkout of develop that I haven't updated in awhile) , I see gdb.xxx.vtk files with CommunicateGhost in the name. After PR, no files with CommunicateGhost in the name get dumped.
I haven't been able to figure out how/why the ghosting is different between the pre-PR and post-PR.
Helpful additional information

Did you get wrong results:  (?)

To Reproduce
Run VisIt with a parallel engine with at least 2 procs.
Create Volume plot of multi_ucd3d.silo, with Parallel rendering type and ParallelPerRank resampling option.
Draw.
You will get different results depending on the number of processors on the engine.
Desktop

OS and version: Linux
VisIt Version:  3.4RC (3.4.2), develop

Will need to remove volume_X from skip list when this is fixed.

ghost zones should help with the resampling operation before raytracing in either case. So if ghosts are missing, we should dig into why.


Request interface overriding already defined interfaces

Hi, I'm not sure if this is an issue with itty-router or just how I'm setting things up. But I'm using itty-router in my typescript project. But I can't get VS Code to recognize all the request properties.
In the example below, VS Code will complain about Property 'query' does not exist on type 'Request'.
import { Router } from 'itty-router'

const router = Router()

router.get('/', (request: Request) => {
  console.log('Cf: ', request.cf)
  console.log('Query: ', request.query)
})

addEventListener('fetch', (event: FetchEvent) => {
  event.respondWith(router.handle(event.request))
})

But if I import the request interface from itty-router. It overrides the already defined request types added to the tsconfig from Cloudflare. The below example will complain that Property 'cf' does not exist on type 'Request'..
import { Router, Request } from 'itty-router'

const router = Router()

router.get('/', (request: Request) => {
  console.log('Cf: ', request.cf)
  console.log('Query: ', request.query)
})

addEventListener('fetch', (event: FetchEvent) => {
  event.respondWith(router.handle(event.request))
})

How can I get VS Code to recognize all properties on the request?

The main reason I didn't want to extend native Request itself is I didn't want any such hard requirement on what's fed into the very agnostic itty.  As long as it has the most basic two request-like attributes: method and url, I'll take any old object.
Happy to do whatever I can to support the much more rules-bound TS community, but I try to keep lightweight libs like itty accessible to the lowest common denominator, which means as few constraints as I can get away with.
With that in mind, what do you folks propose as the best path forward for this without adding hard requirements on a native Request (which also would count as a breaking change)?

Should be considered closed, as I believe this was addressed with the latest TS changes.  Feel free to reopen if that's not the case!


Test HBV before mesh for IO

To improve the performance of ray casting we test the input ray
versus the hierarchical bounding volume before running a ray cast
on the objects mesh.

Code looks good.
 The times for a hit is comparable to the before case.


Dockerfile: wait for postgres

Sometimes pgweb starts before Postgres, and it fails, because Postgres is slower to start, or it has to initialize its database or recover. This makes it try until Postgres is available.
Two commits:

Execute the pgweb command as command instead of entrypoint
Use script as entrypoint which waits for Postgres to be available

What are your thoughts on having the waiting done via a special CLI flag? Having this functionality only tied to Docker is not ideal as it'll need to be documented separately vs a general flag that works the same everywhere. We can detect connection refused errors upon connect and act accordingly (retry N times etc)

It would be nice, actually :)

Currently in WIP at https://github.com/sosedoff/pgweb/pull/695

Im closing this since #695 is already merged


IE8下报错

'eventType' is undefined
ieBetter.js, line 354 character 5

Yes, this is really a bug, I temporarily fixed that by re-writing this function:
global.removeEventListener = function(eventType, funcHandle, useCapture*) {
oDomExtend.removeEventListener.call(global, eventType, funcHandle, useCapture);
};
Notice that "removeEventListener" function ,we need to pass the parameters there. You can open the file and do what I said, however, the final result just waits the owner to fix, maybe he will find a better solution;)

@MaleDong thank you 梅冬，are you a programmer now? and many years ago ,i heard you were a tv newsreporter.

No. I began my experience of a programmer since 2009 for background mainly

@MaleDong thank you


Fixed a scope issue.

Found that my last change was losing the scope for this. Fixed by adding a bind.

Thanks @rob-odil !