hash tags are rendered as Private notes

Please select the area your bug applies to. (Multiple selections are Possible. You can leave blank if you're not sure.)

[ ] Workspace.  VSCode workspace, vaults, Intellisense/autocomplete, Dendron settings
[ ] Lookup.  Dendron's Lookup Command
[ ] Views.  Dendron Preview, Tree View, Side Panels in the UI
[ ] Schema.  Dendron Schemas
[ ] Pod.  Data import from / export to Dendron
[x] Publish.  External Site Publish
[ ] Markdown.  Markdown features, such as syntax support and features

Describe the bug
using a hashtag in this case #test  renders the link marked as private. but as you can see in the screenshot the tag exists.

using [[tags.test]] works.
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 (if with published websites; include version): [e.g. chrome, safari]
Versions (all that apply to bug):

Dendron Extension:
VS Code version:
Dendron CLI:

Additional context
Add any other context about the problem here.
Dendron Log file
Please attach the output of > Dendron:Dev: Open Logs here

@jonathanyeung hunch is that https://github.com/dendronhq/dendron/blob/fe4c475bfc9093e1eafd2e5f4e05805a872e6ff9/packages/unified/src/utilities/getParsingDependencyDicts.ts#L126 points to the problem
needs to be changed from hashtag.value to hashtag.fname.

This issue caused the playwright tests to fail so I disabled the specific test case temporarily here 478ca8e (#3689) until we fix that.


Fail to acquire lease for blobs in one SAS attached blob container

Storage Explorer Version: 1.12.0
Build: 20200305.6
Branch: dev/chuye/beta-blob-extension
Platform/OS: Windows 10/ Linux Ubuntu 16.04
Architecture: ia32/x64
Regression From: Previous release(1.12.0)
Steps to reproduce:

Expand one Non-ADLS Gen2 storage account -> Blob Containers.
Select one blob container -> Attach it using SAS (with full permissions).
Open the SAS attached blob container -> Upload one blob to it.
Try to acquire lease for the blob -> Check the result.

Expect Experience:
Succeed to acquire lease for the blob.
Actual Experience:

Fail to acquire lease for the blob.
Storage Explorer is not responding.

More Info:

This issue also reproduces for break lease action
This issue also reproduces for blobs in one SAS attached account.

This issue has been fixed on build 20200308.1. So close it.


int8 gemm slower than fp16 on A100.

I need a python operator that support int8gemm with pertoken/perchannel quantization. So I wrap the code  https://github.com/NVIDIA/TensorRT-LLM/blob/main/cpp/tensorrt_llm/kernels/cutlass_kernels/int8_gemm/int8_gemm_template.h into something like https://github.com/Guangxuan-Xiao/torch-int/blob/main/torch_int/kernels/linear.cu#L476
Then I test the speed of int8gemm compare with pure fp16 (torch.nn.functional.linear). The time cost only statistic gemm, no quantize. I repeat gemm 1e5 times (1e6 times in small case).

M
N
K
torch cost(s)
trt-llm cost(s)

1024
1024
1024
19.999567985534668
22.63555335998535

2048
2048
2048
8.349320888519287
7.4798314571380615

4096
4096
4096
65.3261570930481
45.53051781654358

8192
4096
4096
125.70239543914795
137.0772671699524

4096
8192
4096
125.74432516098022
117.87490010261536

4096
4096
8192
118.52623224258423
86.75222182273865

test code is something like:
x, alpha = gen_input_tensor([M, K])
y, beta  = gen_input_tensor([N, K])
n = 100000

with cost("int8gemm"):
    for _ in range(n):
        d = mylib.linear_a8_w8_bofp16(x, y, beta, alpha, bias)

x = x * alpha
y = y * beta

with cost("torch"):
    for _ in range(n):
        c = torch.nn.functional.linear(x, y)

At first I think the reason is input tensor too small, so when mnk equals 4096, int8gemm finally faster than torch. But then I try 8192 in just one dim, the int8gemm is slower again. The last three case should have similar computations, the torch result reflact that, but int8gemm cost is quiet unstable. And i expect that int8gemm should be 2x faster than fp16 according to https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/a100/pdf/nvidia-a100-datasheet-us-nvidia-1758950-r4-web.pdf .

I check case [4096, 8192, 4096] with nsys, didn't found anything weird.
I'm confused with these results and try to understand the deep reason. or if it is caused by some compile error, how would I check it ?
Env:
Ubuntu 20.04.6 LTS
NVIDIA A100-SXM4-80GB
base commit: c89653021e66ca78c55f02b366f404455bc12e8d
I build and run code in docker build from docker/Dockerfile.multi .
I build mylib base on scripts/build_wheel.py .

Hi @beegerous , thank you for reporting the issue. When using https://github.com/NVIDIA/TensorRT-LLM/blob/main/cpp/tensorrt_llm/kernels/cutlass_kernels/int8_gemm/int8_gemm_template.h one should specify ThreadblockShape, WarpShape and Stages to configure GEMM. Choice of these parameters can influence the performance by a lot. Meanwhile, torch uses some runtime heuristics (e.g. in cuDNN library) to choose the optimal GEMM shape for the given problem size. Thus, I guess, the performance difference you see comes from comparison of suboptimal int8 GEMM to optimal fp16 GEMM.
In TensorRT-LLM we use profiler to find the best GEMM configuration for int8 given problem size: https://github.com/NVIDIA/TensorRT-LLM/blob/main/cpp/tensorrt_llm/plugins/common/gemmPluginProfiler.cpp. For example, this profiler is used here, could you, please, try it out. Let me know if you have more questions.

Hi @beegerous , thank you for reporting the issue. When using https://github.com/NVIDIA/TensorRT-LLM/blob/main/cpp/tensorrt_llm/kernels/cutlass_kernels/int8_gemm/int8_gemm_template.h one should specify ThreadblockShape, WarpShape and Stages to configure GEMM. Choice of these parameters can influence the performance by a lot. Meanwhile, torch uses some runtime heuristics (e.g. in cuDNN library) to choose the optimal GEMM shape for the given problem size. Thus, I guess, the performance difference you see comes from the comparison of suboptimal int8 GEMM to the optimal fp16 GEMM.
In TensorRT-LLM we use profiler to find the best GEMM configuration for int8 given problem size: https://github.com/NVIDIA/TensorRT-LLM/blob/main/cpp/tensorrt_llm/plugins/common/gemmPluginProfiler.cpp. For example, this profiler is used here, could you, please, try it out. Let me know if you have more questions.

@nekorobov  Thanks for reply.
sorry I miss some information. Before I calculate gemm, I use this function (https://github.com/NVIDIA/TensorRT-LLM/blob/main/cpp/tensorrt_llm/kernels/cutlass_kernels/cutlass_heuristic.cpp#L196) to get the best tile config, and make sure it only run one time for specific [m,n,k].
Is there difference between cutlass_heuristic and gemmPluginProfiler ?  From io variable I think they are both for get best CutlassGemmConfig.
By the way, the code here (https://github.com/NVIDIA/TensorRT-LLM/blob/main/cpp/tensorrt_llm/kernels/cutlass_kernels/int8_gemm/int8_gemm_template.h#L268) is a little bit confused. It is the only one shape that diff with case variable name tells. But I change it into 64 and re-run those cases, get no difference performance.

I use this function (https://github.com/NVIDIA/TensorRT-LLM/blob/main/cpp/tensorrt_llm/kernels/cutlass_kernels/cutlass_heuristic.cpp#L196) to get the best tile config, and make sure it only run one time for specific [m,n,k].

Do you include this function into your time calculations? This might take significant amount of time. Which candidate_configs do you provide?

Is there difference between cutlass_heuristic and gemmPluginProfiler ? From io variable I think they are both for get best CutlassGemmConfig.

Yes, cutlass_heuristic uses some heruistics to estimate the best config, which is not always accurate. gemmPluginProfiler simply profiles each GEMM config to choose the fastest. gemmPluginProfiler should be executed offline, but it gives more accurate results.

It is the only one shape that diff with case variable name tells. But I change it into 64 and re-run those cases, get no difference performance.

Indeed, this mismatch is a bug. Thank you for reporting this. I believe that it makes difference, just not on the cases you've profiled.

@nekorobov
thanks for your advise. I change cutlass_heuristic into profiler, and int8 gemm on a100 become much faster.
here is the latest result. (trt-llm cost does not contain profiler time.)

m
n
k
torch cost(s)
trt-llm cost(s)

1024
1024
1024
19.89363145828247
20.7686026096344

2048
2048
2048
8.329726219177246
7.037260055541992

4096
4096
4096
63.426324129104614
44.36107349395752

8192
4096
4096
125.48689246177673
96.80497765541077

4096
8192
4096
126.33650040626526
85.49396276473999

4096
4096
8192
118.56665873527527
86.97948837280273

@nekorobov thanks for your advise. I change cutlass_heuristic into profiler, and int8 gemm on a100 become much faster. here is the latest result. (trt-llm cost does not contain profiler time.)
m	n	k	torch cost(s)	trt-llm cost(s)
1024	1024	1024	19.89363145828247	20.7686026096344
2048	2048	2048	8.329726219177246	7.037260055541992
4096	4096	4096	63.426324129104614	44.36107349395752
8192	4096	4096<PHONE_NUMBER>6177673	96.80497765541077
4096	8192	4096<PHONE_NUMBER>0626526	85.49396276473999
4096	4096	8192<PHONE_NUMBER>3527527	86.97948837280273

Have you misstaken the unit? us not seconds?

@nekorobov Hi, I also tested this int8 kernel and has some problems:
From my benchmark, I compared this int8 gemm kenel with w8a16 mixed gemm kernel and got:

[M,N,K]
W8A16/ms
W8A8/ms
Boost/ %

[M:16, N:6144, K:4096]
0.02534
0.01514
40.244

[M:16, N:4096, K:4096]
0.02431
0.01454
40.1752

[M:16, N:28672, K:4096]
0.11408
0.09675
15.1917

[M:16, N:4096, K:14336]
0.06912
0.05302
23.2827

As you can see, this kernel is indeed faster for this four case. But when I use this kernel in real models, for the first two shape, the perf will dropped a lot:
[M:16, N:6144, K:4096] : 24us
[M:16, N:4096, K:4096]: 20 us
But for the last two shapes, the perf won't drop.
Could you please give me some clues to get the perf back?
TIPS: I have done some experiments, I found if I call 10 times of the kernel in the model, not just 1 time, the calling's perf after the first time will be good. If this is a cache/warmup issue, why the last two cases won't have this problem.


Ansible aws ubuntu instance Deploy etcd fails

I have a Ubuntu EC2 instance and it fails
PLAY [Deploy etcd] *************************************************************
18:03:20
18:03:20 TASK [setup] *******************************************************************
18:03:21 fatal: [<IP_ADDRESS>]: FAILED! => {"changed": false, "failed": true, "module_stderr": "/bin/sh: 1: /usr/bin/python: not found\n", "module_stdout": "", "msg": "MODULE FAILURE", "parsed": false}

What Ubuntu version?

This fails every time the aws creates ubuntu instance without python. I would recommend to either choose different image (if it is available) or run pre-ansible  scripts that can install python into the ubuntu instance.


Export for high quality 3d printing?

Hi, wondering how to export better mesh instead of rasterized results? The render from 'Colorized Volume' looks pretty amazing, but I guess its not for export?

If you have a color raster 3D printer then you can print the colorized volume as is (see https://github.com/SlicerFab/SlicerFab).
If your printer can only accept a colored mesh as input then there is not much you can do. A surface mesh only contains information about an infinitely thin layer, no subsurface information, so you will not be able to see the same thing as with volume rendering.

If you have a color raster 3D printer then you can print the colorized volume as is (see https://github.com/SlicerFab/SlicerFab).
If your printer can only accept a colored mesh as input then there is not much you can do. A surface mesh only contains information about an infinitely thin layer, no subsurface information, so you will not be able to see the same thing as with volume rendering.

I was actually hoping for a way or a semi auto way to refine the AI segmented result, It could be really helpful..


Swapilar patch 3

Description
These improvements are part of the Cryptoversidad grant proposal.

Hey, I'm going to close this PR as it's just rewording an existing sentence.


Multiplex notifications about chain head updates

Currently, we have one ChainHeadUpdateListener for each ethereum network; each listener requires its own database connection where it runs LISTEN chain_head_updates, and discards messages about all but the one network it is interested in.
Instead, we should have just one ChainHeadUpdateListener that maintains a map of subscribers by network name and passes notifications on to the ones for the network in the message.

This has been address in PR #1693


docs: Automated Changelog Update for v5.0.0-beta5.monitor.3

copilot:all
Automated changes by create-pull-request GitHub action

🤖 Generated by lychee action
Summary

Status
Count

🔍 Total
1258

✅ Successful
378

⏳ Timeouts
0

🔀 Redirected
0

👻 Excluded
879

❓ Unknown
0

🚫 Errors
0

Full action output
Full Github Actions output


msys2 compile error: how to fix it?

i come to the dir of crown,then run  make tools-linux-release64,then it happens:
make -j1 -R -C 3rdparty/luajit/src CC="gcc -m64" CCOPT="-O2 -fomit-frame-pointer -msse2" TARGET_SYS=Linux BUILDMODE=static
make[1]: come to “/crown-master/3rdparty/luajit/src”
HOSTCC    host/minilua.o
HOSTLINK  host/minilua
DYNASM    host/buildvm_arch.h
HOSTCC    host/buildvm.o
HOSTCC    host/buildvm_asm.o
HOSTCC    host/buildvm_peobj.o
HOSTCC    host/buildvm_lib.o
HOSTCC    host/buildvm_fold.o
HOSTLINK  host/buildvm
BUILDVM   lj_vm.S
ASM       lj_vm.o
buildvm_x86.dasc: Assembler messages:
buildvm_x86.dasc:6: error：unknown pseudo-op: .hidden' buildvm_x86.dasc:7: warnning：.type pseudo-op used outside of .def/.endef ignored. buildvm_x86.dasc:7: error：junk at end of line, first unrecognized character is l'
buildvm_x86.dasc:8: warnning：.size pseudo-op used outside of .def/.endef ignored.
buildvm_x86.dasc:8: error：junk at end of line, first unrecognized character is l' buildvm_x86.dasc:13: error：unknown pseudo-op: .hidden'
buildvm_x86.dasc:14: warnning：.type pseudo-op used outside of .def/.endef ignored.
buildvm_x86.dasc:14: error：junk at end of line, first unrecognized character is l' .........there are many errors like this "junk at end of line, first unrecognized character is l' ”,how to fix it?

$ export MINGW=/mingw64
$ export PATH=$PATH:/mingw64/bin
$ make mingw-debug64

@dbartolini  thanks, it works..


Update fields on dynamic field added to ngx-formly

Is there any way we can update formly component when we add a dynamic field to the fields list?
I have a requirement, where users can add and remove field, but field is not referencing form, and throwing error.
export class AppComponent {
  form = new FormGroup({});
  model = {};
  fields: FormlyFieldConfig[] = [
    {
      key: 'name',
      type: 'input',
      templateOptions: {
        label: 'Field 1',
        placeholder: 'Formly is terrific!',
      },
    },
  ];

  fn() {
    debugger;
    this.fields.push({
      key: 'name1',
      type: 'input',
      templateOptions: {
        label: 'Field 1',
        placeholder: 'Formly is terrific!',
      },
    })
  }

  submit(model) {
    console.log(model);
  }
}

No problem :) Which reference has to be updated?


inter-ui: 3.1 -> 3.3

Motivation for this change
FWIW new name but not sure worth renaming attribute
(to 'inter' or maybe 'inter-font'?)
https://github.com/rsms/inter/releases/tag/v3.3
https://github.com/rsms/inter/releases/tag/v3.2
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[ ] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[ ] Assured whether relevant documentation is up to date
[ ] Fits CONTRIBUTING.md.

Don't think it's worth the hassle of renaming the attribute.

I don't think fonts should be bumped like this when the name of the font changes. It breaks existing font configuration (using "Inter UI" instead of the new "Inter"), and Emacs even fails to start up. If the last "Inter UI" was 3.2, maybe inter-ui could have been left at 3.2 and removed at some point in the future. Sorry to jump in 15 days too late.


Sc debug improvements

What current issue(s) does this address, or what feature is it adding?
The following was discussed on discord, this implements the first 2 items, and I can push the 3rd item to this PR once we agree on the implementation of 1+2.

During the dApp competition i made some local changes to make debugging smart contracts easier and I'm thinking about what can/should flow back. Would love some input on the following ideas;

add instruction counter to the error message/stacktrace.
Rationale: it allows for setting a conditional breakpoint exactly on the instruction that's going to fail next. The counter also gives some indication whether it failed early during execution or later on (giving a feel how deep the error lays).

add a debug toggle to emit Notify events even if smart contracts fail.
Rationale: right now Notify events are only emitted when the SC execution is successful, which makes sense from an execution and operational standpoint, but not from developing. It drops a lot of potential useful information emitted in your Notify events that could help solve the problem.

add instruction logging
rationale; having a historical log of all calls executed gave me nearly all the information needed to exactly pin point which code line of my SC the VM was executing (by looking at function calls, DROP/RET statements etc).

add additional error messages to ExecutionEngine.
rationale; there's a lot of error feedback we can simply give that we're not doing leading to guess work or a lot of stepping through the VM internals.

localhuman - Yesterday at 2:55 PM
I like all of those things :smiley:

How did you solve this problem?
implement 1 + 2
How did you make sure your solution works?
manual testing
Are there any special changes in the code that we should be aware of?
no
Please check the following, if applicable:

[ ] Did you add any tests?
[X] Did you run make lint?
[X] Did you run make test?
[X] Are you making a PR to a feature branch or development rather than master?
[ ] Did you add an entry to CHANGELOG.rst? (if not, please do)

Will update changelog.rst after it's clear which changes will all be approved. If I check it now, I/we might forget to add all changes.

Coverage decreased (-0.02%) to 78.133% when pulling 420bc09700e9e6370a6b094982f1425b511020d8 on ixje:sc_debug into 6a661cbf5be71844d8d8d64c643fbf74b85710b5 on CityOfZion:development.

You can use the new TestBuild command to add some tests for new notification functionality and error messaging :)
This test build catches the notifications https://github.com/CityOfZion/neo-boa/blob/master/boa_test/tests/test_event.py


nested range with different path is not possible

Using confd 0.12.0-dev with template file like this (it's a crude and useless example i know):
{{range $firstloop := ls "/registry/namespaces"}}
{{range $secondloop := ls "/registry/services/spaces"}}
"found it"
{{end}}
{{end}}

I never see the message "found it" in the resulting file.
If i change the secondloop ls path to be the same/sub of firstloop path i.e.
{{range $firstloop := ls "/registry/namespaces"}}
{{range $secondloop := ls "/registry/namespaces/something"}}
"found it"
{{end}}
{{end}}

i do see the message "found it"
safe to say all the keys in paths involved exist. also note that using just "/registry" in secondloop ls also seems to work. i.e.
{{range $secondloop := ls "/registry"}}

So it's as if while we are in firstloop range, you can not do range on different path.
To put it in context, i wanted to use the above logic to first look for namespaces and then check if a service exist for that given namespace (for kubernetes related work i am doing)

You can't read Kubernetes data from Etcd since 1.6, closing this for now.


Font rendering issues when built with Qt 6

Checklist

[X] I'm reporting a problem with Chatterino
[X] I've verified that I'm running the most recent nightly build or stable release
[X] I've looked for my problem on the wiki
[X] I've searched the issues and pull requests for similar looking reports

Describe your issue
Weird font rendering (left Qt 6.5.0, right Qt 5.15.2) Font used: FantasqueSansMono-NoLoopK (1.8.0)

- windeployqt says Cannot open .: Access is denied., it still works, just odd error, this did not happen with Qt 5.15.2 (maybe related? not sure, not sure even if anything could be done for something like this, just reporting findings)
While these screenshots are for dankerino, the same issues occurred with c2
I used the dankerino screenshots, as it made the differences clearer with Gray-out recent messages disabled
cmake flags used: cmake -B build -DCMAKE_BUILD_TYPE=Release -DBUILD_WITH_QT6=ON -DQT_DEBUG_FIND_PACKAGE=ON -DCMAKE_DISABLE_FIND_PACKAGE_WrapVulkanHeaders=TRUE -DCHATTERINO_LTO=ON
OS and Chatterino Version
Chatterino 2.4.2 (commit 7b609490) built with Qt 6.5.0, Windows SDK, MSVC 193532215 Running on Windows 10, kernel: 10.0.20152

windeployqt says Cannot open .: Access is denied., it still works, just odd error, this did not happen with Qt 5.15.2 (maybe related? not sure, not sure even if anything could be done for something like this, just reporting findings)
[...]

❯ windeployqt chatterino.exe

You're running incorrectly for chatterino (take a look at how it's done in CI and the official documentation).
For chatterino, you want to disable translations (--no-translations, the feature causing your invocation to fail). CI also doesn't include the software rasterization library (--no-opengl-sw) and omits deploying the VC runtime (--no-compiler-runtime).

@Nerixyz Ty that works, however the font rendering issue still exists, I'll update the post accordingly
❯ & "$env:Qt6_DIR\bin\windeployqt.exe" bin/chatterino.exe --no-translations --no-opengl-sw --no-compiler-runtime
QCommandLineParser: already having an option named "no-virtualkeyboard"
C:\Users\brian\Documents\GitHub\dankerino\build\bin\chatterino.exe 64 bit, release executable
Adding Qt6Svg for qsvgicon.dll
Adding Qt6Pdf for qpdf.dll
Skipping plugin qtvirtualkeyboardplugin.dll due to disabled dependencies (Qt6Qml Qt6Quick).
Direct dependencies: Qt6Core Qt6Core5Compat Qt6Gui Qt6Network Qt6Widgets
All dependencies   : Qt6Core Qt6Core5Compat Qt6Gui Qt6Network Qt6Widgets
To be deployed     : Qt6Core Qt6Core5Compat Qt6Gui Qt6Network Qt6Pdf Qt6Svg Qt6Widgets
Updating Qt6Core.dll.
Updating Qt6Core5Compat.dll.
Updating Qt6Gui.dll.
Updating Qt6Network.dll.
Updating Qt6Pdf.dll.
Updating Qt6Svg.dll.
Updating Qt6Widgets.dll.
Updating d3dcompiler_47.dll.
Creating directory ~/Documents/GitHub/dankerino/build/bin/generic.
Updating qtuiotouchplugin.dll.
Creating directory ~/Documents/GitHub/dankerino/build/bin/iconengines.
Updating qsvgicon.dll.
Creating directory ~/Documents/GitHub/dankerino/build/bin/imageformats.
Updating qgif.dll.
Updating qicns.dll.
Updating qico.dll.
Updating qjpeg.dll.
Updating qpdf.dll.
Updating qsvg.dll.
Updating qtga.dll.
Updating qtiff.dll.
Updating qwbmp.dll.
Updating qwebp.dll.
Creating directory ~/Documents/GitHub/dankerino/build/bin/networkinformation.
Updating qnetworklistmanager.dll.
Creating directory ~/Documents/GitHub/dankerino/build/bin/platforms.
Updating qwindows.dll.
Creating directory ~/Documents/GitHub/dankerino/build/bin/styles.
Updating qwindowsvistastyle.dll.
Creating directory ~/Documents/GitHub/dankerino/build/bin/tls.
Updating qcertonlybackend.dll.
Updating qopensslbackend.dll.
Updating qschannelbackend.dll.

Post PR (left Qt 6.5.0, right Qt 5.15.2):

It is a bit different, but much better than before


Resolve switch covers known cases, but 'Enum' may have additional unknown values warnings

When building with CMake during the Swift compiler build, the libraries in this package are built with library evolution enabled. That causes the compiler to emit diagnostics that encourage use of @unknown default to handle unknown cases that might be added in the future. Silence these warnings by adding @unknown default cases where they are missing. Guard these with the RESILIENT_LIBRARIES compilation condition to avoid triggering a Default will never be executed diagnostic during the package build.

@swift-ci please test

@swift-ci please smoke test

@swift-ci please test macOS

@swift-ci please test Windows


New package: Tuplers v0.5.3

Registering package: Tuplers
Repository: https://github.com/alkan/Tuplers.jl
Created by: @alkan
Version: v0.5.3
Commit: 66d6404248f1ec19b318f2ab61b2937554865061
Git reference: 0.5.3
Description: A tiny utility to build tuples incrementally
Release notes:

https://github.com/alkan/Tuplers.jl/README.md

Hey @alkan, I have some concerns about the implementation of the package. Because this builds up an expression, and then eval's that expression, some surprising things can happen for instance if someone push!es a Symbol or an Expr to a Tupler. For instance:
julia> let t = Tupler()
           push!(t, :hi)
           build(t)
       end
ERROR: UndefVarError: hi not defined
[...]

julia> let t = Tupler()
           push!(t, :(1 + 1))
           build(t)
       end
(2,)

julia> let t = Tupler()
           push!(t, Expr(:call, :pwd))
           build(t)
       end
("/Users/mason",)

which I would say is not good behaviour, and potentially dangerous. Besides this, using eval in this way is going to be rather slow.
Instead, I'd probably just have the Tupler store an Array{Any} and push! to that array and then convert it to a Tuple at the end. E.g.
julia> Tuple(Any[:hi, :(1 + 1), Expr(:call, :pwd)])
(:hi, :(1 + 1), :(pwd()))

This will also be pretty slow due to the array, and the dynamic dispatch, but it'll be strictly faster than the current implementation, and more correct / safe.

Thank you Mason, very helpful review.  I realised yor concerns, and I
admit.  The simple Tuple construction method you depicted makes
unnecessary such a utility.  Then what about named Tuples?  Would you
please shaw me a way to represent a named Tuple element w/o using Expr?


Adding agentVersion  clientPlatform to OpenTelemetryService

We have agent version and ClientPlatform in OpenTelemetryService
Test plan
Tested locally with an otel collector

Changelog

@dominiccooney So I talked to @abeatrix and turns out that the package.json for the insiders-release and proper release is automatically adjusted and that writes the value of agentExtensionVersion and you can see that in the cody settings too

See related code
NOTE: We already have these being emitted in Webviewopentelemetry service so we have this in honeycomb


PSUseCmdletCorrectly fails to detect when mandatory parameters are supplied in a splatted hashtable

Today it seems that PSUseCmdletCorrectly fails to detect when mandatory parameters are supplied to a cmdlet via a splatted hashtable.
Since determining the contents of the hashtable is a runtime activity (and looking at my script it would be difficult if not impossible to do so without running it), I would prefer if this warning wouldn't be generated at all when splatting.  Knowing how I use splatting, it is often because building the required parameter set is complicated, in which case this warning shouldn't appear at all.
But, isn't this yet another case where PSScriptAnalyzer is overstepping its bounds?  Checking to see if mandatory parameters are used, unless it is obvious (with pipeline support - I noticed there is another bug logged about that) should be something that happens from unit testing, not from analysis IMHO.  These types of errors are very easy to understand when they do occur, they tend to occur quickly and be identified through simple testing, and this rule is just generating noise for me right now.

I am also having this fail when just using the Add-Member cmdlet, something as simple as this:
$array = @([PSObject]'MyFirstObject', [PSObject]'MySecondObject')
$array | ForEach-Object {
     $_ | Add-Member -NotePropertyName 'MyNoteProperty' -Value 'MyNotePropertyValue'
}

I'm not sure what 'Mandatory' property im missing, or how this example is using the Add-Member Cmdlet incorrectly.

This is a known bug (https://github.com/PowerShell/PSScriptAnalyzer/issues/71). We are working on fixing it.

Fixed with https://github.com/PowerShell/PSScriptAnalyzer/pull/240


Added support for Bill's Tomato Game, Diamenty, Rallye Master

@keirf Here is the update to the amigados for custom syncs we discussed a week ago.  Please have a look and merge it if it is ok.

Why is STD_SYNC introduced? It doesn't appear to be used. Apart from that okay and you can merge it.

I forgot to remove it.  I was going to approach it differently at first and get rid of the array of syncs, but I mentioned in the email I wasn't sure what other games used the syncs already that were already supported.  I will merge it as is an will remove it in the next update.


Codemod - missing comma before v.check on v.intersect

const FormSchema = v.pipe(v.intersect([CommonSchema, NationalitiesSchema])v.check((inputs) => { (...)

Thanks! I fixed it.


Create a struct to store configuration and ignore old events.

Ignore old events.
Create a struct that store configuration including workflow file, schedule file, etc to ensure that when the configuration changes, this does not cause tests to fail.

Resolved comments from code review.


Use ComponentDetection 4.9.6

Update Microsoft.ComponentDetection.* packages from 4.8.9 to 4.9.6. This is centrally managed via Directory.Packages.props. We're picking up this version at the suggestion of the ComponentDetection team.

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

Project coverage is 66.38%. Comparing base (08ba73d) to head (4c1914e).

Additional details and impacted files
@@            Coverage Diff             @@
##             main     #700      +/-   ##
==========================================
- Coverage   69.66%   66.38%   -3.28%
==========================================
  Files         277      277
  Lines        8629     8629
  Branches     1004     1004
==========================================
- Hits         6011     5728     -283
- Misses       2101     2392     +291
+ Partials      517      509       -8

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


Drop diag_logs_filter.php in 18.1

With https://github.com/opnsense/core/issues/1788 stacked for 18.1 I would like to suggest the removal of the old "Normal" view (diag_logs_filter.php).
The codebase is pretty old and messy, doesn't really bring more functionality to the table then the new live view and the feature to quickly add firewall rules based on log output isn't very solid anyway.

Sounds good. Maybe we can merge both by slapping the current normal log filter behaviour on top. It’s really time to rework this plumbing internally as well, i was thinking syslog-ng usage for exported streams to finally support TCP and proper host name write but keep clog/syslogd combo a bit longer for internal use. 😊


Cache Events

Add cache events to Event Listener, mainly to avoid confusing CallStart>CallEnd or CallStart>CallFailed responses due to Cache strategy.

@swankjesse I tried to implement a cacheFallback test but didn't succeed. e.g. instead of a 304, are there any situations where we should fallback to the cache response with either a Etag, or max-age but we hit the network for heuristic reasons?

Thanks for driving this. But I’d like to propose perhaps changing which events we publish.

Amen, happy to use this to work out the right events.


Compilation error when use -DETL_BLAS_MODE

Hello.
When I use -DETL_BLAS_MODE flag to compile, I get these error. I have already installed liblapack.
clang++-4.0 -DETL_PARALLEL -DETL_VECTORIZE_FUL -DETL_BLAS_MODE -std=c++1z -lpthread -llapack -lblas  main.cpp
In file included from main.cpp:8:
In file included from dll/neural/conv_layer.hpp:11:
In file included from dll/neural/dyn_conv_layer.hpp:10:
In file included from dll/neural/dyn_conv_layer_impl.hpp:11:
In file included from dll/neural_layer.hpp:15:
In file included from dll/etl/etl.hpp:108:
In file included from dll/etl/expr/gemm_expr.hpp:15:
dll/etl/impl/blas/gemm.hpp:952:32: error: use of undeclared identifier 'mkl_get_max_threads'
            auto mkl_threads = mkl_get_max_threads();
                               ^
dll/etl/impl/blas/gemm.hpp:954:13: error: use of undeclared identifier 'mkl_set_num_threads'
            mkl_set_num_threads(1);
            ^
dll/etl/impl/blas/gemm.hpp:1250:32: error: use of undeclared identifier 'mkl_get_max_threads'
            auto mkl_threads = mkl_get_max_threads();
                               ^
dll/etl/impl/blas/gemm.hpp:1252:13: error: use of undeclared identifier 'mkl_set_num_threads'
            mkl_set_num_threads(1);
            ^
4 errors generated.

any solutions?

Hello qipx,
This is a bug of mine. I will fix it tomorrow. It should be an easy fix.
Sorry about that

Thanks.
I commented out error lines and the program works well.
This library is very cool.

This should be fixed with 1f451ea
I'm glad you could fix it yourself. And glad you like :)
Tell me if you still have issues.


Drop 32-bit support.

As Windows 11 is only 64-bit and Windows 10 support ends October 2025, I think it's time to end 32-bit support once and for all.

Closed as it's removed.


Create authorizer

This resolves #729

Hi @alldroll , thank you so much for working on this cool feature! Please also address code climate's comments.

Replaced by https://github.com/short-d/short/pull/757


Work on scoring mechanism

Right now highscore basically sums up destroyed asteroids, which isn't helpful. We need a scoring mechanism which fulfills two goals:

It's limited by the page's performance (a well build site should in general be able to yield a higher score)
It still reflects the player's game (bad player lower score, good player higher score)

After the last discussion it seems we keep the scoring, but don't save it. So we'll just show the score in the end, and let people share it with a link to the game. This will make it easier with respect to security/privacy stuff, we can also skip the db etc. We can still add real leaderboards in a later step, if people seem to like the game. So this ticket is rather about removing the old scoring stuff, and adapting the endscreen to the new model (show game score, show lighthouse score, link out to lighthouse report if possible, big sharing button in center)

The longer I think about it I'm tempted to completely rip out the scoring. This will give more highlight to the lighthouse scores, which are more important anyway. So the game itself would only be about winning or dying. Any thoughts?

My 2 cents: I do think a game needs a score. Without score it's no game, but just a different, interactive  "view" of the lighthouse report :-)
But I could understand the decision to remove the scoring to keep the whole project simpler for the moment.

In general I feel the same. Let's leave the score in as-is for now (removing would also add work). We can still extend (or rip out) later. Closing this for now.


Feature add: the bot will delete the musicard/player message when track ends

^^
The bot will delete the player message + button instead of disabling it

@Elitex07, do you Need this in this Repo? I wanted to keep it simple as it represents Riffy's ability.

yay


Installation problem

Hi! I tried installing this on python but when I run the setup script I get this:
/usr/bin/ld: /home/marco/srilm/lib/i686-m64/liboolm.a(Vocab.o): relocation R_X86_64_32 against `_ZSt4cerr' can not be used when making a shared object; recompile with -fPIC
/home/marco/srilm/lib/i686-m64/liboolm.a: error adding symbols: Bad value
collect2: error: ld returned 1 exit status
error: command 'c++' failed with exit status 1
Do you know how to fix this?

Thanks a lot! Had the same issue, your solution worked for me!

Solved my problem as well. Thanks.


Upgrade Husky to v6 and add lint on stage using prettier

Husky v6 wasn't working properly because .huskyrc is deprecated. So setup the config according to the new guide: https://typicode.github.io/husky/#/
Also added lint-staged as a husky pre-commit hook, so that it automatically lints using prettier and stages the files linted

Hey @DakshMiglani! This is great, thanks for your PR. I didn't know that Husky v4 was deprecated.
A friendly note for future contributions: it would be great if you let me push commits to your PR branch :). It looks like you disabled changes on this one:
 ! [remote rejected] main -> DakshMiglani-main (permission denied)

Awesome!
Will keep that in mind when making the PR next time!


Flesh out tags

Expose more use cases via the ipc system. provide some atoms.

[X] Tags work and you can spawn windows on different tags

Has there been any progress on this? I'm more interested in the "view more than one tag at a time"

I've never worked on it since I've never really needed it to be honest but it's a very simple change, I'll try to implement it soon :)

I've never really needed it

Once it's done I highly recommend trying it, it's very useful :D


Creating a signed transaction not work

Version of EOSJS
^16.0.9
I was trying to sign the transaction without broadcasting like the follow:
`
async createAccount(headers, creator, creatorPrvKey, account, activePub, ownerPub){
let options = {
  httpEndpoint:httpEndpoint,
  keyProvider: creatorPrvKey,
  transactionHeaders:headers,
  verbose: false,
  sign: true,
  chainId: chainId,
};

let eos = await Eos(options);
let transaction = await eos.transaction(tr => {
  tr.newaccount({
    creator: creator,
    name: account,
    owner: ownerPub,
    active: activePub
  })
  tr.buyrambytes({
    payer: creator,
    receiver: account,
    bytes: 0
  })
  tr.delegatebw({
    from: creator,
    receiver: account,
    stake_net_quantity: '0.1000 EOS',
    stake_cpu_quantity: '0.1000 EOS',
    transfer: 0
  })
},{broadcast: false,sign:true});
return {transaction: transaction.transaction};
 }

`
and I passed the return value from createAccount to this function:
`
async pushTransactions(transaction){
let options = {
  httpEndpoint: httpEndpoint,
  chainId: chainId,
  verbose: false
};
let eos = Eos(options);
let transfer = await eos.pushTransaction(transaction);
console.log("pushing transaction Done!");
console.log(transfer);

}
`
But now I got this error:
Error","error":{"code":3010010,"name":"packed_transaction_type_exception","what":"Invalid packed transaction","details":[{"message":"Missing signatures","file":"abi_serializer.hpp","line_number":578,"method":"extract"},{"message":"Failed to deserialize variant","file":"abi_serializer.hpp","line_number":679,"method":"from_variant"},{"message":"Invalid packed transaction","file":"chain_plugin.cpp","line_number":1545,"method":"push_transaction"}]}}
It works perfectly when I make the broadcast:true option for eos.transaction in createAccount(), however when I try to separate the signing and broadcasting, it creates an error. The returned transaction from createAccount() looks valid and actually has a signature and which contradicts the error msg as well.
Your help will be very much appreciated!! Thanks

if I return transaction.transaction instead of {transaction:transaction.transaction} it works fine in createAccount


Fix Production order pdf

Coverage decreased (-0.3%) to 61.175% when pulling 58fb3d2d16afa3578c0e6e0d1c1639799236f297 on achensetyawati:dev into 92383d0667a32e97e76125d447274bfcfa930a8f on danliris:dev.


Latest Razor tooling source link not working in VS

Describe the bug
We did a VS insertion yesterday (12/10) which had new Razor tooling bits from our AspNetCore-Tooling repo. I tried debugging those bits and found that I could download symbols for the binary and upon doing so would be prompted to download the source file. In VS after clickign "Download source and continue" it attempts to do it multiple times and then fails.
To Reproduce
Steps to reproduce the behavior:

Open d16.0stg
Open a web project
Open a Razor file
Add a function breakpoint for RazorDirectiveCompletionProvider.ProvideCompletionsAsync.
At the top of the Razor file type @p
Your breakpoint will hit, at which point it will attempt to load the sources.

Expected behavior
Source file is properly downloaded

This worked for me just now on another part of the razor tooling code. I'm going to close this.


[pending] Add conda package

The build is failing because TensorFlow 2.4 is not available on conda for now, only the v2.3 is, which is not compatible with mplc v0.3.1. I suggest we keep this PR as pending unless someone manage to make a conda build with pypi dependencies.

[ ] First build test
[x] Update contributing.md
[x] Config conda channel
[ ] Publish under Substra umbrella

Close #212

Codecov Report

Merging #267 (fc62a45) into master (2e28840) will decrease coverage by 0.23%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master     #267      +/-   ##
==========================================
- Coverage   82.63%   82.39%   -0.24%
==========================================
  Files          13       13
  Lines        2637     2602      -35
==========================================
- Hits         2179     2144      -35
  Misses        458      458

Impacted Files
Coverage Δ

mplc/partner.py
89.74% <0.00%> (-1.47%)
:arrow_down:

mplc/corruption.py
79.67% <0.00%> (-0.74%)
:arrow_down:

mplc/models.py
78.08% <0.00%> (-0.30%)
:arrow_down:

mplc/dataset.py
85.79% <0.00%> (-0.25%)
:arrow_down:

mplc/multi_partner_learning.py
85.18% <0.00%> (-0.13%)
:arrow_down:

mplc/scenario.py
82.96% <0.00%> (-0.13%)
:arrow_down:

mplc/mpl_utils.py
84.09% <0.00%> (-0.12%)
:arrow_down:

mplc/splitter.py
96.25% <0.00%> (-0.05%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 2e28840...fc62a45. Read the comment docs.

Codecov Report

Merging #267 (fc62a45) into master (2e28840) will decrease coverage by 0.23%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master     #267      +/-   ##
==========================================
- Coverage   82.63%   82.39%   -0.24%
==========================================
  Files          13       13
  Lines        2637     2602      -35
==========================================
- Hits         2179     2144      -35
  Misses        458      458

Impacted Files
Coverage Δ

mplc/partner.py
89.74% <0.00%> (-1.47%)
:arrow_down:

mplc/corruption.py
79.67% <0.00%> (-0.74%)
:arrow_down:

mplc/models.py
78.08% <0.00%> (-0.30%)
:arrow_down:

mplc/dataset.py
85.79% <0.00%> (-0.25%)
:arrow_down:

mplc/multi_partner_learning.py
85.18% <0.00%> (-0.13%)
:arrow_down:

mplc/scenario.py
82.96% <0.00%> (-0.13%)
:arrow_down:

mplc/mpl_utils.py
84.09% <0.00%> (-0.12%)
:arrow_down:

mplc/splitter.py
96.25% <0.00%> (-0.05%)
:arrow_down:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 2e28840...fc62a45. Read the comment docs.

No updates as of january 26th
conda search tensorflow==2.4
Loading channels: done
No match found for: tensorflow==2.4. Search: *tensorflow*==2.4

No updates as of january 26th
conda search tensorflow==2.4
Loading channels: done
No match found for: tensorflow==2.4. Search: *tensorflow*==2.4

Closing this for now

Closing this for now


textDocumet/formatting fails with Stylus and SASS

using style elements with stylus or sass breaks formatting for the entire file.
error messages
stylus
[Trace - 5:47:54 PM] Received response 'textDocument/formatting - (134)' in 10ms. Request failed: Request textDocument/formatting failed with message: Couldn't resolve parser "stylus" (-32603).
[Error - 5:47:54 PM] Request textDocument/formatting failed.
  Message: Request textDocument/formatting failed with message: Couldn't resolve parser "stylus"
  Code: -32603

sass
[Trace - 5:47:16 PM] Received response 'textDocument/formatting - (126)' in 10ms. Request failed: Request textDocument/formatting failed with message: Couldn't resolve parser "sass" (-32603).
[Error - 5:47:16 PM] Request textDocument/formatting failed.
  Message: Request textDocument/formatting failed with message: Couldn't resolve parser "sass"
  Code: -32603

fixed in 0.21.19, thanks for report!


consume values from cluster values secret in capv and capvcd

This PR:

Configures HTTP proxy CNP from the values fed by the cluster-values secret.

Checklist

[ ] Update changelog in CHANGELOG.md.

@kopiczko
Towards https://github.com/giantswarm/roadmap/issues/3238
Not ideal but this works with https://github.com/giantswarm/cluster-cloud-director/pull/330
WDYT?

@vxav I checked https://github.com/giantswarm/cluster-cloud-director/pull/330. Won't targetPath work there?
$ k explain helmrelease.spec.valuesFrom.targetPath
GROUP:      helm.toolkit.fluxcd.io
KIND:       HelmRelease
VERSION:    v2beta1

FIELD: targetPath <string>

DESCRIPTION:
    TargetPath is the YAML dot notation path the value should be merged at. When
    set, the ValuesKey is expected to be a single flat value. Defaults to
    'None', which results in the values getting merged at the root.

Ignore the above. It won't work as the keys are different (snake case vs camelcase)

How about using Helm's lookup and then pass the Secret.data.values trough fromYaml and store it as a variable and then use in the HelmRelease.spec.values directly.
Some untested code:
{{- $proxySecret := lookup "v1" "Secret" .Release.Namespace (include "resource.default.name" $ )-cluster-values -}}
values:
  allowEgressToProxy:
    httpProxy: {{ $proxySecret.http_proxy | quote }}
    httpsProxy: {{ $proxySecret.https_proxy | quote }}


No revoke possible

I try to revoke a grant but always get the following error:
Failed to broadcast: Error when broadcasting tx 1DF81D94E1D8D706D7DB5564DC2977C325E02EAFFFC2FC64FBDAFC404577C09C at height 0. Code: 4; Raw log: signature verification failed; please verify account number (4049466), sequence (740) and chain-id (columbus-5): unauthorized
Restake is also not working with stakebin. My lunc Address: terra1qvw6vv7my8ule8u4ughxjsw96x3zdnywmdtdm8

Hi. Is this project still alive?

@gmt-it Terra Classic does not support ledger and Authz fully currently. There is an issue here with more information: https://github.com/eco-stake/restake-ui/issues/89
You should be able to revoke any grants manually using the CLI, but there's not really any other way around it unfortunately. I've raised an issue with Terra.js directly, but I've not had a response so far (see linked issue above).


Module Not Updated

Hello MHProDev,
How are you, we got some problem using your awesome tools. The problem i mean was about your tools still using out date python module. Hope you will update your tools soon :)

ok :)


Fix deconz allow_clip_sensor and allow_deconz_groups options

Description:
I found that options allow_clip_sensor and allow_deconz_groups in core.config_entries don't work.
It started from PR and async_populate_options function that moved these values from config_entry.data to config_entry.options.
According to this comment there is no way to change this options via UI.
But now they works and i can change them in core.config_entries.
Related issue (if applicable): fixes #
Pull request with documentation for home-assistant.io (if applicable): home-assistant/home-assistant.io#<home-assistant.io PR number goes here>
Example entry for configuration.yaml (if applicable):

Checklist:

[x] The code change is tested and works locally.
[x] Local tests pass with tox. Your PR cannot be merged unless tests pass
[x] There is no commented out code in this PR.
[x] I have followed the development checklist

If user exposed functionality or configuration variables are added/changed:

[ ] Documentation added/updated in home-assistant.io

If the code communicates with devices, web services, or third-party tools:

[ ] The manifest file has all fields filled out correctly. Update and include derived files by running python3 -m script.hassfest.
[ ] New or updated dependencies have been added to requirements_all.txt by running python3 -m script.gen_requirements_all.
[ ] Untested files have been added to .coveragerc.

If the code does not interact with devices:

[ ] Tests have been added to verify that the new code works.

How could I have missed this? Thanks!

@Kane610 @balloob Please merge this PR to master if it's possible


grass recipe for conda-forge

Hi,
I see you have quite a good knowledge of both grass (configure/build system) and conda (build environment) - it will be great if we could work on making a conda-forge recipe for GRASS. I do have little experience with the conda-build system I can try to help in testing/debugging reporting logs about builds on both Linux and mac platforms. Would this be of interest to you?
BTW, thank you for this repository, it made my life on mac easier and happier ... reminds me of the great efforts made by kingchaos to provide grass on mac!

Hi,

I see you have quite a good knowledge of both grass (configure/build system) and conda (build environment) - it will be great if we could work on making a conda-forge recipe for GRASS. I do have little experience with the conda-build system I can try to help in testing/debugging reporting logs about builds on both Linux and mac platforms. Would this be of interest to you?

In fact, my knowledge on conda is quite rudimentary – but of course, I'll help out with what I can.

BTW, thank you for this repository, it made my life on mac easier and happier ... reminds me of the great efforts made by kingchaos to provide grass on mac!

I'm really glad it comes to use! In fact the unpredictable state of GRASS for Mac (since Kyngesburye inactivated himself from GRASS), made me embark on this little project.

@epifanio I finally started out with a recipe for conda-forge. It is still WIP and only tested so far on Mac. I’d much appreciate if you could give it a try.
https://github.com/nilason/staged-recipes/tree/add-grass

Cool!
I'm copying Eric on this too. Can I try it and not mess up my existing binary apps?
Michael

C. Michael Barton

On Mar 9, 2022, at 4:41 PM, Nicklas Larsson @.***> wrote:
@epifanio https://github.com/epifanio I finally started out with a recipe for conda-forge. It is still WIP and only tested so far on Mac. I’d much appreciate if you could give it a try.
https://github.com/nilason/staged-recipes/tree/add-grass https://github.com/nilason/staged-recipes/tree/add-grass
—
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Below are the steps I use to build this. Note this is only tested on a machine with no previously installed conda, using only a fresh installed Mambaforge.
# download or fork https://github.com/nilason/staged-recipes/tree/add-grass
# and set GRASS_RECIPES_DIR to that location
GRASS_RECIPES_DIR=/path/to/staged-recipes/recipes/grass
# download platform specific miniforge/mambaforge from
# https://github.com/conda-forge/miniforge and set
# CONDA_FILE accordingly
CONDA_FILE=Mambaforge-MacOSX-xxxx.sh

# install miniconda/miniforge/mambaforge
bash "${CONDA_FILE}"
# (open new shell and continue with:)
conda config --add channels conda-forge
conda config --set channel_priority strict
conda install conda-build
conda install conda-forge-pinning

# build the recipe
cd ./mambaforge
conda build -c conda-forge "${GRASS_RECIPES_DIR}"

# test installing grass in a new environment
conda create --name grasstest --clone base
conda activate grasstest
conda install -c local grass

@nilason This is is amazing! Thank you for getting this going again! 🎉
Please let me know if you need any help with this.

@nilason This is is amazing! Thank you for getting this going again! 🎉

I'm glad I can contribute in any way :-)

Please let me know if you need any help with this.

There are two things that I cannot test right now:

wxPython for Apple arm64 platform is broken so I cannot test the GUI, only CLI. Would be good to confirm if GUI works (guess it should on x86_64).
Absolutely untested on Linux, the patches are inherited. So this is a big one, for anyone interested to dig in.

Once it works for both Mac and Linux, I plan to make a PR of this recipe to conda-forge/staged-recipes.

I tested with a continuumio/miniconda3 Docker image. It stopped at:
conda build -c conda-forge "${GRASS_RECIPES_DIR}"

which fails with:
WARNING: No numpy version specified in conda_build_config.yaml.  Falling back to default numpy value of 1.22
...
warning  libmamba Problem type not implemented SOLVER_RULE_STRICT_REPO_PRIORITY
...
│  ├─ numpy [1.22.3|1.22.4] would require
│  │  └─ python_abi 3.9 *_pypy39_pp73, which can be installed;
│  └─ numpy 1.22.3 conflicts with any installable versions previously reported;
└─ python 3.11.*  is not installable because it conflicts with any installable versions previously reported.
...

I added NumPy version to staged-recipes/recipes/grass/meta.yaml but it was not taken into account. The complain is about conda_build_config.yaml but I don't know where to find that file (the container has many files of this name).
Something special about the cd ./mambaforge step? I just replaced that with mkdir test; cd test.
A pure Ubuntu image like this:
docker ubuntu
apt update
apt install wget git nano
wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh
git clone https://github.com/nilason/staged-recipes/ --branch add-grass
GRASS_RECIPES_DIR=/staged-recipes/recipes/grass/
CONDA_FILE=Miniforge3-Linux-x86_64.sh
bash "${CONDA_FILE}"
bash
conda config --add channels conda-forge
conda config --set channel_priority strict
conda install conda-build conda-forge-pinning
mkdir ./mambaforge
cd ./mambaforge
conda build -c conda-forge "${GRASS_RECIPES_DIR}"

also ends with an error, but a different one:
...
    Traceback (most recent call last):
      File "/root/miniforge3/lib/python3.10/site-packages/conda/exceptions.py", line 1132, in __call__
        return func(*args, **kwargs)
      File "/root/miniforge3/lib/python3.10/site-packages/conda/cli/main.py", line 69, in main_subshell
        exit_code = do_call(args, p)
      File "/root/miniforge3/lib/python3.10/site-packages/conda/cli/conda_argparse.py", line 115, in do_call
        return args.plugin_subcommand.action(sys.argv[2:])
      File "/root/miniforge3/lib/python3.10/site-packages/conda_build/plugin.py", line 10, in build
        execute(*args, **kwargs)
      File "/root/miniforge3/lib/python3.10/site-packages/conda_build/cli/main_build.py", line 520, in execute
        _parser, args = parse_args(args)
      File "/root/miniforge3/lib/python3.10/site-packages/conda_build/cli/main_build.py", line 474, in parse_args
        check_recipe(args.recipe)
    AttributeError: 'Namespace' object has no attribute 'recipe'
...

I tried updating https://github.com/nilason/staged-recipes/tree/add-grass from upstream main, but it didn't make any difference (the update seemed to go well).
Any thoughts?

@wenzeslaus It was quite a while since I worked on this, I’ll need to refresh my memory on this and try again.

Re: the docker image, I can't tell much on that one.
With the ubuntu image, you hit a AttributeError: 'Namespace' object has no attribute 'recipe' error, which I could reproduce and only hardly workaround. Now, it seems to me be caused by a bug in conda (at least up till) version 23.3.1. I can't update conda (conda update -n base conda) due to missing support for my machine, but a small patch to /root/miniforge3/lib/python3.10/site-packages/conda/cli/conda_argparse.py (taken from changes to that file in https://github.com/conda/conda/commit/330fa91282d9b5e3cc07be795f0aaad23b4f5882) did the work. That change is present with conda 23.5.0.

Something special about the cd ./mambaforge step? I just replaced that with mkdir test; cd test.

You can skip that part (mkdir and cd), not needed.
I rebased and updated the recipe, so that shouldn't be a big problem. It will for sure need more work, but now it builds GRASS 8.3.1 on Mac at least.

Below are the steps I use to build this. Note this is only tested on a machine with no previously installed conda, using only a fresh installed Mambaforge.
# download or fork https://github.com/nilason/staged-recipes/tree/add-grass
# and set GRASS_RECIPES_DIR to that location
GRASS_RECIPES_DIR=/path/to/staged-recipes/recipes/grass
# download platform specific miniforge/mambaforge from
# https://github.com/conda-forge/miniforge and set
# CONDA_FILE accordingly
CONDA_FILE=Mambaforge-MacOSX-xxxx.sh

# install miniconda/miniforge/mambaforge
bash "${CONDA_FILE}"
# (open new shell and continue with:)
conda config --add channels conda-forge
conda config --set channel_priority strict
conda install conda-build
conda install conda-forge-pinning

# build the recipe
cd ./mambaforge
conda build -c conda-forge "${GRASS_RECIPES_DIR}"

# test installing grass in a new environment
conda create --name grasstest --clone base
conda activate grasstest
conda install -c local grass

Are these still the correct instructions to testing the WIP GRASS conda build? Are there different (or any) instructions for windows?

I just tried this out on an M2 MacBook running Mac OS 14.5. It got partway through before it failed with the following error:
(base) cmbarton@OKED3863 miniforge3 % conda build -c conda-forge "${GRASS_RECIPES_DIR}"
WARNING: No numpy version specified in conda_build_config.yaml.  Falling back to default numpy value of 1.23
Adding in variants from internal_defaults
Attempting to finalize metadata for simplejson
Reloading output folder: ...working... done
Getting pinned dependencies: ...working... done
Reloading output folder: ...working... done
Getting pinned dependencies: ...working... done
Reloading output folder: ...working... done
Getting pinned dependencies: ...working... done
BUILD START: ['simplejson-3.8.2-py311h8a0c2ca_0.tar.bz2']
Reloading output folder: ...working... done
Solving environment (_h_env): ...working... done

## Package Plan ##

  environment location: /Applications/anaconda3/conda-bld/simplejson_1718654966466/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold

The following NEW packages will be INSTALLED:

    bzip2:           1.0.8-h93a5062_5          conda-forge
    ca-certificates: 2024.6.2-hf0a4a13_0       conda-forge
    libexpat:        2.6.2-hebf3989_0          conda-forge
    libffi:          3.4.2-h3422bc3_5          conda-forge
    libsqlite:       3.46.0-hfb93653_0         conda-forge
    libzlib:         1.3.1-hfb2fe0b_1          conda-forge
    ncurses:         6.5-hb89a1cb_0            conda-forge
    openssl:         3.3.1-hfb2fe0b_0          conda-forge
    pip:             24.0-pyhd8ed1ab_0         conda-forge
    python:          3.11.9-h932a869_0_cpython conda-forge
    readline:        8.2-h92ec313_1            conda-forge
    setuptools:      70.0.0-pyhd8ed1ab_0       conda-forge
    tk:              8.6.13-h5083fa2_1         conda-forge
    tzdata:          2024a-h0c530f3_0          conda-forge
    wheel:           0.43.0-pyhd8ed1ab_1       conda-forge
    xz:              5.2.6-h57fd34a_0          conda-forge

Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done
Reloading output folder: ...working... done
Solving environment (_build_env): ...working... done
Reloading output folder: ...working... done
Solving environment (_test_env): ...working... done

## Package Plan ##

  environment location: /Applications/anaconda3/conda-bld/simplejson_1718654966466/_build_env

The following NEW packages will be INSTALLED:

    ca-certificates:       2024.6.2-hf0a4a13_0       conda-forge
    cctools_osx-arm64:     986-hd11630f_0            conda-forge
    clang:                 18.1.7-default_h095aff0_0 conda-forge
    clang-18:              18.1.7-default_hb63da90_0 conda-forge
    clang_impl_osx-arm64:  18.1.7-had71ce8_16        conda-forge
    clang_osx-arm64:       18.1.7-h54d7cd3_16        conda-forge
    clangxx:               18.1.7-default_h095aff0_0 conda-forge
    compiler-rt:           18.1.7-h28df8ea_0         conda-forge
    compiler-rt_osx-arm64: 18.1.7-h56c4e69_0         conda-forge
    icu:                   73.2-hc8870d7_0           conda-forge
    ld64_osx-arm64:        711-h5e7191b_0            conda-forge
    libclang-cpp18.1:      18.1.7-default_hb63da90_0 conda-forge
    libcxx:                17.0.6-h5f092b4_0         conda-forge
    libiconv:              1.17-h0d3ecfb_2           conda-forge
    libllvm18:             18.1.7-h5090b49_1         conda-forge
    libxml2:               2.12.7-ha661575_1         conda-forge
    libzlib:               1.3.1-hfb2fe0b_1          conda-forge
    llvm-tools:            18.1.7-h5090b49_1         conda-forge
    openssl:               3.3.1-hfb2fe0b_0          conda-forge
    sigtool:               0.1.3-h44b9a77_0          conda-forge
    tapi:                  1100.0.11-he4954df_0      conda-forge
    xz:                    5.2.6-h57fd34a_0          conda-forge
    zstd:                  1.5.6-hb46c0d2_0          conda-forge

Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done
Source cache directory is: /Applications/anaconda3/conda-bld/src_cache
Downloading source to cache: simplejson-3.8.2_2b3a0c466f.tar.gz
Downloading https://pypi.io/packages/source/s/simplejson/simplejson-3.8.2.tar.gz
Success

# >>>>>>>>>>>>>>>>>>>>>> ERROR REPORT <<<<<<<<<<<<<<<<<<<<<<

    Traceback (most recent call last):
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda/exception_handler.py", line 18, in __call__
        return func(*args, **kwargs)
               ^^^^^^^^^^^^^^^^^^^^^
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda/cli/main.py", line 84, in main_subshell
        exit_code = do_call(args, parser)
                    ^^^^^^^^^^^^^^^^^^^^^
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda/cli/conda_argparse.py", line 176, in do_call
        result = plugin_subcommand.action(getattr(args, "_args", args))
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/plugin.py", line 17, in build
        return execute(args)
               ^^^^^^^^^^^^^
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/cli/main_build.py", line 590, in execute
        api.build(
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/api.py", line 250, in build
        return build_tree(
               ^^^^^^^^^^^
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/build.py", line 3638, in build_tree
        packages_from_this = build(
                             ^^^^^^
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/build.py", line 2419, in build
        try_download(m, no_download_source=False, raise_error=True)
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/render.py", line 762, in try_download
        source.provide(metadata)
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/source.py", line 1035, in provide
        unpack(
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/source.py", line 169, in unpack
        src_path, unhashed_fn = download_to_cache(
                                ^^^^^^^^^^^^^^^^^^
      File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/source.py", line 125, in download_to_cache
        raise RuntimeError(
    RuntimeError: SHA256 mismatch: 'd58439c548433adcda98e695be53e526ba940a4b9c44fb9a05d92cd495cdd47f' != '2b3a0c466fb4a1014ea131c2b8ea7c519f9278eba73d6fcb361b7bdb4fd494e9'

`$ /Applications/anaconda3/bin/conda build -c conda-forge /Users/cmbarton/Dropbox (ASU)/GitHub/staged-recipes`

  environment variables:
                 CIO_TEST=<not set>
    CONDA_ALLOW_SOFTLINKS=false
        CONDA_DEFAULT_ENV=base
                CONDA_EXE=/Applications/anaconda3/bin/conda
             CONDA_PREFIX=/Applications/anaconda3
    CONDA_PROMPT_MODIFIER=(base)
         CONDA_PYTHON_EXE=/Applications/anaconda3/bin/python
               CONDA_ROOT=/Applications/anaconda3
              CONDA_SHLVL=1
           CURL_CA_BUNDLE=<not set>
               LD_PRELOAD=<not set>
                     PATH=/Applications/anaconda3/bin:/Applications/anaconda3/condabin:/usr/loca
                          l/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin:/usr
                          /texbin:/opt/X11/bin:/Library/Apple/usr/bin:/var/run/com.apple.securit
                          y.cryptexd/codex.system/bootstrap/usr/local/bin:/var/run/com.apple.sec
                          urity.cryptexd/codex.system/bootstrap/usr/bin:/var/run/com.apple.secur
                          ity.cryptexd/codex.system/bootstrap/usr/appleinternal/bin
       REQUESTS_CA_BUNDLE=<not set>
            SSL_CERT_FILE=<not set>

     active environment : base
    active env location : /Applications/anaconda3
            shell level : 1
       user config file : /Users/cmbarton/.condarc
 populated config files : /Users/cmbarton/.condarc
          conda version : 24.5.0
    conda-build version : 24.5.1
         python version : 3.11.6.final.0
                 solver : libmamba (default)
       virtual packages : __archspec=1=m2
                          __conda=24.5.0=0
                          __osx=14.5=0
                          __unix=0=0
       base environment : /Applications/anaconda3  (writable)
      conda av data dir : /Applications/anaconda3/etc/conda
  conda av metadata url : None
           channel URLs : https://conda.anaconda.org/conda-forge/osx-arm64
                          https://conda.anaconda.org/conda-forge/noarch
                          https://repo.anaconda.com/pkgs/main/osx-arm64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/osx-arm64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /Applications/anaconda3/pkgs
                          /Users/cmbarton/.conda/pkgs
       envs directories : /Applications/anaconda3/envs
                          /Users/cmbarton/.conda/envs
               platform : osx-arm64
             user-agent : conda/24.5.0 requests/2.31.0 CPython/3.11.6 Darwin/23.5.0 OSX/14.5 solver/libmamba conda-libmamba-solver/23.11.1 libmambapy/1.5.3
                UID:GID : 503:505
             netrc file : /Users/cmbarton/.netrc
           offline mode : False

An unexpected error has occurred. Conda has prepared the above report.
If you suspect this error is being caused by a malfunctioning plugin,
consider using the --no-plugins option to turn off plugins.

Thanks Nicklaus. I’m traveling but will try this again when I get back.Michael Barton...Sent from my iPadOn Aug 12, 2024, at 8:01 AM, Nicklas Larsson @.***> wrote:
I just tried this out on an M2 MacBook running Mac OS 14.5. It got partway through before it failed with the following error:
I have now updated the recipe, please download again. I managed to get some similar error message after re-trying a failed attempt (You may try conda purge after failed attempts).
As I don't have MacOSX11.sdk in conda standard location, I had to set CONDA_BUILD_SYSROOT (see https://docs.conda.io/projects/conda-build/en/stable/resources/compiler-tools.html#macos-sdk and https://docs.conda.io/projects/conda-build/en/stable/resources/variants.html#conda-build-variant-config-files).
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you commented.Message ID: @.***>

This is still not building. Here is what I am doing. Am I doing something wrong? I've got mambaforge installed
Add path to sdk to conda_build_config.yaml in staged recipes
CONDA_BUILD_SYSROOT:
- /Library/Developer/CommandLineTools/SDKs/MacOSX11.0.sdk

Then in terminal:
GRASS_RECIPES_DIR=/Users/cmbarton/staged-recipes/recipes/grass
CONDA_FILE=/Users/cmbarton/grass_source/Miniforge3-MacOSX-arm64.sh
conda config --add channels conda-forge
conda config --set channel_priority strict
cd /Users/cmbarton/miniforge3
conda build -c conda-forge "${GRASS_RECIPES_DIR}"
conda create --name grasstest --clone base
conda activate grasstest
conda install -c local grass

It doesn't get past the build part. Below is the error report.
(base) cmbarton@OKED3863 miniforge3 % conda build -c conda-forge "${GRASS_RECIPES_DIR}"# test installing grass in a new environment
ERROR: Glob /Users/cmbarton/staged-recipes/recipes/grass# did not match in root_dir /Users/cmbarton/miniforge3
ERROR: Glob /Users/cmbarton/miniforge3/test did not match in root_dir /Users/cmbarton/miniforge3
ERROR: Glob /Users/cmbarton/miniforge3/installing did not match in root_dir /Users/cmbarton/miniforge3
ERROR: Glob /Users/cmbarton/miniforge3/grass did not match in root_dir /Users/cmbarton/miniforge3
ERROR: Glob /Users/cmbarton/miniforge3/in did not match in root_dir /Users/cmbarton/miniforge3
ERROR: Glob /Users/cmbarton/miniforge3/a did not match in root_dir /Users/cmbarton/miniforge3
ERROR: Glob /Users/cmbarton/miniforge3/new did not match in root_dir /Users/cmbarton/miniforge3
ERROR: Glob /Users/cmbarton/miniforge3/environment did not match in root_dir /Users/cmbarton/miniforge3
>>>>>>>>>>>>>>>>>>>>>> ERROR REPORT <<<<<<<<<<<<<<<<<<<<<<
Traceback (most recent call last):
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda/exception_handler.py", line 18, in __call__
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda/cli/main.py", line 84, in main_subshell
    exit_code = do_call(args, parser)
                ^^^^^^^^^^^^^^^^^^^^^
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda/cli/conda_argparse.py", line 176, in do_call
    result = plugin_subcommand.action(getattr(args, "_args", args))
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/plugin.py", line 17, in build
    return execute(args)
           ^^^^^^^^^^^^^
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/cli/main_build.py", line 589, in execute
    api.build(
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/api.py", line 205, in build
    raise ValueError(
ValueError: No valid recipes found for input: ['/Users/cmbarton/staged-recipes/recipes/grass#', 'test', 'installing', 'grass', 'in', 'a', 'new', 'environment']

$ /Applications/anaconda3/bin/conda build -c conda-forge /Users/cmbarton/staged-recipes/recipes/grass# test installing grass in a new environment
environment variables:
CIO_TEST=
CONDA_ALLOW_SOFTLINKS=false
CONDA_DEFAULT_ENV=base
CONDA_EXE=/Applications/anaconda3/bin/conda
CONDA_PREFIX=/Applications/anaconda3
CONDA_PROMPT_MODIFIER=(base)
CONDA_PYTHON_EXE=/Applications/anaconda3/bin/python
CONDA_ROOT=/Applications/anaconda3
CONDA_SHLVL=1
CURL_CA_BUNDLE=
LD_PRELOAD=
PATH=/Applications/anaconda3/bin:/Applications/anaconda3/condabin:/usr/loca
l/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin:/usr
/texbin:/opt/X11/bin:/Library/Apple/usr/bin:/var/run/com.apple.securit
y.cryptexd/codex.system/bootstrap/usr/local/bin:/var/run/com.apple.sec
urity.cryptexd/codex.system/bootstrap/usr/bin:/var/run/com.apple.secur
ity.cryptexd/codex.system/bootstrap/usr/appleinternal/bin
REQUESTS_CA_BUNDLE=
SSL_CERT_FILE=
 active environment : base
active env location : /Applications/anaconda3
        shell level : 1
   user config file : /Users/cmbarton/.condarc

populated config files : /Users/cmbarton/.condarc
conda version : 24.7.1
conda-build version : 24.7.1
python version : 3.11.6.final.0
solver : libmamba (default)
virtual packages : __archspec=1=m2
__conda=24.7.1=0
__osx=14.5=0
__unix=0=0
base environment : /Applications/anaconda3  (writable)
conda av data dir : /Applications/anaconda3/etc/conda
conda av metadata url : None
channel URLs : https://conda.anaconda.org/conda-forge/osx-arm64
https://conda.anaconda.org/conda-forge/noarch
https://repo.anaconda.com/pkgs/main/osx-arm64
https://repo.anaconda.com/pkgs/main/noarch
https://repo.anaconda.com/pkgs/r/osx-arm64
https://repo.anaconda.com/pkgs/r/noarch
package cache : /Applications/anaconda3/pkgs
/Users/cmbarton/.conda/pkgs
envs directories : /Applications/anaconda3/envs
/Users/cmbarton/.conda/envs
platform : osx-arm64
user-agent : conda/24.7.1 requests/2.32.3 CPython/3.11.6 Darwin/23.5.0 OSX/14.5 solver/libmamba conda-libmamba-solver/23.12.0 libmambapy/1.5.4
UID:GID : 503:505
netrc file : /Users/cmbarton/.netrc
offline mode : False

I see you have anaconda installed. My procedure assumes a "clean" environment to build with miniforge. But it should of course work with a pre-installed anaconda as well. I'd try from the conda build -c conda-forge "${GRASS_RECIPES_DIR}" step (just make sure you remove the ~/miniforge3 dir).

My first attempt did not work. But it did show me a problem. When I clone your staged-recipes repository, it does not include the grass recipe. However, if I download the zip file I get "staged-recipes-add-grass", which does include the grass recipe. My initial tries with the latter have failed and I'll try a couple more things.

Now I find that the zip file (staged-recipes-add-grass) is missing conda_build_config.yaml (where I can specify the location of the SDK) but it has much more info in the conda-forge.yml than the cloned repository (staged-recipes), which only lists windows.  I cloned and downloaded the zip from the add-grass branch of the staged-recipes repository. But I am confused as to which set of files to use.

There are some possible variations for conda_build_config.yaml, see https://docs.conda.io/projects/conda-build/en/stable/resources/variants.html#conda-build-variant-config-files.

There are some possible variations for conda_build_config.yaml, see https://docs.conda.io/projects/conda-build/en/stable/resources/variants.html#conda-build-variant-config-files.

The 4th point is perhaps the most convenient.

I'm using a conda_build_config.yaml that looks like this:
MACOSX_DEPLOYMENT_TARGET:  # [osx]
  - 11.0                   # [osx]
CONDA_BUILD_SYSROOT:
  - /Library/Developer/CommandLineTools/SDKs/MacOSX11.0.sdk

The conda-forge.yml in the cloned staged-recipes repository looks like this:
channel_priority: strict
azure:
  settings_win:
    pool:
      vmImage: windows-2022

And the same file in the downloaded zip file repository staged-recipes-add-grass looks like this:
build_platform:
  linux_aarch64: linux_64
  linux_ppc64le: linux_64
  osx_arm64: osx_64
conda_forge_output_validation: true
provider:
  linux: azure
  linux_aarch64: azure
  linux_ppc64le: azure
  osx: azure
  win: azure
test_on_native_only: true
os_version:
  linux_64: cos7

channel_priority: strict
# azure:
#   settings_win:
#     pool:
#       vmImage: windows-2022

Without miniforge, here is what happens. It says that there are no valid recipes, even though the grass folder is indeed inside the recipes folder. I wonder if there is something somewhere that is hard-coded to your environment that we are missing.
(base) cmbarton@OKED3863 ~ % GRASS_RECIPES_DIR=/Users/cmbarton/staged-recipes-add-grass/recipes/grass
(base) cmbarton@OKED3863 ~ % conda build -c conda-forge "${GRASS_RECIPES_DIR}"# test installing grass in a new environment

ERROR: Glob /Users/cmbarton/staged-recipes-add-grass/recipes/grass# did not match in root_dir /Users/cmbarton
ERROR: Glob /Users/cmbarton/test did not match in root_dir /Users/cmbarton
ERROR: Glob /Users/cmbarton/installing did not match in root_dir /Users/cmbarton
ERROR: Glob /Users/cmbarton/grass did not match in root_dir /Users/cmbarton
ERROR: Glob /Users/cmbarton/in did not match in root_dir /Users/cmbarton
ERROR: Glob /Users/cmbarton/a did not match in root_dir /Users/cmbarton
ERROR: Glob /Users/cmbarton/new did not match in root_dir /Users/cmbarton
ERROR: Glob /Users/cmbarton/environment did not match in root_dir /Users/cmbarton
>>>>>>>>>>>>>>>>>>>>>> ERROR REPORT <<<<<<<<<<<<<<<<<<<<<<
Traceback (most recent call last):
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda/exception_handler.py", line 18, in __call__
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda/cli/main.py", line 84, in main_subshell
    exit_code = do_call(args, parser)
                ^^^^^^^^^^^^^^^^^^^^^
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda/cli/conda_argparse.py", line 176, in do_call
    result = plugin_subcommand.action(getattr(args, "_args", args))
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/plugin.py", line 17, in build
    return execute(args)
           ^^^^^^^^^^^^^
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/cli/main_build.py", line 589, in execute
    api.build(
  File "/Applications/anaconda3/lib/python3.11/site-packages/conda_build/api.py", line 205, in build
    raise ValueError(
ValueError: No valid recipes found for input: ['/Users/cmbarton/staged-recipes-add-grass/recipes/grass#', 'test', 'installing', 'grass', 'in', 'a', 'new', 'environment']

$ /Applications/anaconda3/bin/conda build -c conda-forge /Users/cmbarton/staged-recipes-add-grass/recipes/grass# test installing grass in a new environment

conda build -c conda-forge "${GRASS_RECIPES_DIR}"# test installing grass in a new environment

You must delete the “# test installing grass in a new environment” part from the command.

Thought I clipped that out. Tried again without the comment and have a different error. Could this have to do with the conda-forge.yml file referenced a couple comments above (with build_platform: line "osx_arm64: osx_64")?
(base) cmbarton@OKED3863 ~ % GRASS_RECIPES_DIR=/Users/cmbarton/staged-recipes-add-grass/recipes/grass
(base) cmbarton@OKED3863 ~ % conda build -c conda-forge "${GRASS_RECIPES_DIR}"

WARNING: No numpy version specified in conda_build_config.yaml.  Falling back to default numpy value of 1.23
Adding in variants from internal_defaults
Attempting to finalize metadata for grass
Reloading output folder: ...working... done
Getting pinned dependencies: ...working... failed
WARNING: failed to get package records, retrying.  exception was: Unsatisfiable dependencies for platform osx-arm64: {MatchSpec("c_osx-arm64")}
Encountered problems while solving:

nothing provides requested c_osx-arm64

Could not solve for environment specs
The following package could not be installed
└─ c_osx-arm64 does not exist (perhaps a typo or a missing channel).
Reloading output folder: ...working... done
Getting pinned dependencies: ...working... failed
Reloading output folder: ...working... done
Getting pinned dependencies: ...working... failed
Reloading output folder: ...working... done
Getting pinned dependencies: ...working... failed
ERROR: Failed to get package records, max retries exceeded.
Leaving build/test directories:
Work:
/Applications/anaconda3/conda-bld/work
Test:
/Applications/anaconda3/conda-bld/test_tmp
Leaving build/test environments:
Test:
source activate  /Applications/anaconda3/conda-bld/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold
Build:
source activate  /Applications/anaconda3/conda-bld/_build_env
ExplainedDependencyNeedsBuildingError: Unsatisfiable dependencies for platform osx-arm64: {MatchSpec("c_osx-arm64")}
Encountered problems while solving:

nothing provides requested c_osx-arm64

Could not solve for environment specs
The following package could not be installed
└─ c_osx-arm64 does not exist (perhaps a typo or a missing channel).

in staged-recipes-add-grass/.ci_support/osx64.yaml, targets are set to 10.13 and that won't work with an ARM processor. Unfortunately when I changed them to:
c_stdlib_version:
  - 11
MACOSX_DEPLOYMENT_TARGET:
  - 11

it still is giving the same └─ c_osx-arm64 does not exist does not exist error. So far, I have not found any reference to this.


File Paste

When we file paste. Not asking to overwrite confirmation. And create new file with copy name.
That is really needed to ask and overwrite existing file.

Duplicate of #1893
@testiwm007 Please follow the original issue above. Thanks!


build deps

why is

"toml-0.10.1"
"tree-format-0.1.2"
not listed in setup.py?

It is not necessary when installing via nix, since the python envoronment is defined in python.nix.
But for correctness it should probably also be added to the setup.py

Requirements are added in version 2.3.0


Error during Docker installation

Hello,
I tried installing MeloTTS using the Docker installation and I got this issue:
audio-books-project % git clone https://github.com/myshell-ai/MeloTTS.git
cd MeloTTS
docker build -t melotts .
Cloning into 'MeloTTS'...
remote: Enumerating objects: 400, done.
remote: Counting objects: 100% (115/115), done.
remote: Compressing objects: 100% (41/41), done.
remote: Total 400 (delta 95), reused 82 (delta 72), pack-reused 285
Receiving objects: 100% (400/400), 6.04 MiB | 12.01 MiB/s, done.
Resolving deltas: 100% (196/196), done.
[+] Building 828.3s (12/12) FINISHED                                                                                docker:desktop-linux
 => [internal] load build definition from Dockerfile                                                                                0.0s
 => => transferring dockerfile: 355B                                                                                0.0s
 => [internal] load metadata for docker.io/library/python:3.9-slim                                                                                1.0s
 => [auth] library/python:pull token for registry-1.docker.io                                                                                0.0s
 => [internal] load .dockerignore                                                                                0.0s
 => => transferring context: 2B                                                                                0.0s
 => [1/7] FROM docker.io/library/python:3.9-slim@sha256:fd8693fc6115345452a19654c1388bc9a1029cda7b98e1bce45ede67e74190f0                                         0.0s
 => [internal] load build context                                                                                0.4s
 => => transferring context: 28.95MB                                                                                0.4s
 => CACHED [2/7] WORKDIR /app                                                                                0.0s
 => [3/7] COPY . /app                                                                                0.1s
 => [4/7] RUN apt-get update && apt-get install -y     build-essential libsndfile1     && rm -rf /var/lib/apt/lists/*                                           10.7s
 => [5/7] RUN pip install -e .                                                                                573.2s
 => [6/7] RUN python -m unidic download                                                                                228.5s
 => ERROR [7/7] RUN python melo/init_downloads.py                                                                                14.3s
------
 > [7/7] RUN python melo/init_downloads.py:
3.633 [nltk_data] Downloading package averaged_perceptron_tagger to
3.633 [nltk_data]     /root/nltk_data...
3.841 [nltk_data]   Unzipping taggers/averaged_perceptron_tagger.zip.
3.885 [nltk_data] Downloading package cmudict to /root/nltk_data...
4.130 [nltk_data]   Unzipping corpora/cmudict.zip.
13.24 Traceback (most recent call last):
13.24   File "/app/melo/init_downloads.py", line 5, in <module>
13.24     from melo.api import TTS
13.24   File "/app/melo/api.py", line 18, in <module>
13.24     from .download_utils import load_or_download_config, load_or_download_model
13.24   File "/app/melo/download_utils.py", line 4, in <module>
13.24     from cached_path import cached_path
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/__init__.py", line 13, in <module>
13.24     from ._cached_path import cached_path
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/_cached_path.py", line 15, in <module>
13.24     from .schemes import (
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/schemes/__init__.py", line 6, in <module>
13.24     from .s3 import S3Client
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/schemes/s3.py", line 16, in <module>
13.24     class S3Client(SchemeClient):
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/schemes/s3.py", line 18, in S3Client
13.24     botocore.exceptions.HTTPClientError,
13.24 AttributeError: module 'botocore.exceptions' has no attribute 'HTTPClientError'
------
Dockerfile:11
--------------------
   9 |     RUN pip install -e .
  10 |     RUN python -m unidic download
  11 | >>> RUN python melo/init_downloads.py
  12 |
  13 |     CMD ["python", "./melo/app.py", "--host", "<IP_ADDRESS>", "--port", "8888"]
--------------------
ERROR: failed to solve: process "/bin/sh -c python melo/init_downloads.py" did not complete successfully: exit code: 1

The botocore and boto3 libraries took a lot of time to be installed because it was searching for good version.
Any idea about the issue ?
Thanks.

Hello,
I tried installing MeloTTS using the Docker installation and I got this issue:
audio-books-project % git clone https://github.com/myshell-ai/MeloTTS.git
cd MeloTTS
docker build -t melotts .
Cloning into 'MeloTTS'...
remote: Enumerating objects: 400, done.
remote: Counting objects: 100% (115/115), done.
remote: Compressing objects: 100% (41/41), done.
remote: Total 400 (delta 95), reused 82 (delta 72), pack-reused 285
Receiving objects: 100% (400/400), 6.04 MiB | 12.01 MiB/s, done.
Resolving deltas: 100% (196/196), done.
[+] Building 828.3s (12/12) FINISHED                                                                                docker:desktop-linux
 => [internal] load build definition from Dockerfile                                                                                0.0s
 => => transferring dockerfile: 355B                                                                                0.0s
 => [internal] load metadata for docker.io/library/python:3.9-slim                                                                                1.0s
 => [auth] library/python:pull token for registry-1.docker.io                                                                                0.0s
 => [internal] load .dockerignore                                                                                0.0s
 => => transferring context: 2B                                                                                0.0s
 => [1/7] FROM docker.io/library/python:3.9-slim@sha256:fd8693fc6115345452a19654c1388bc9a1029cda7b98e1bce45ede67e74190f0                                         0.0s
 => [internal] load build context                                                                                0.4s
 => => transferring context: 28.95MB                                                                                0.4s
 => CACHED [2/7] WORKDIR /app                                                                                0.0s
 => [3/7] COPY . /app                                                                                0.1s
 => [4/7] RUN apt-get update && apt-get install -y     build-essential libsndfile1     && rm -rf /var/lib/apt/lists/*                                           10.7s
 => [5/7] RUN pip install -e .                                                                                573.2s
 => [6/7] RUN python -m unidic download                                                                                228.5s
 => ERROR [7/7] RUN python melo/init_downloads.py                                                                                14.3s
------
 > [7/7] RUN python melo/init_downloads.py:
3.633 [nltk_data] Downloading package averaged_perceptron_tagger to
3.633 [nltk_data]     /root/nltk_data...
3.841 [nltk_data]   Unzipping taggers/averaged_perceptron_tagger.zip.
3.885 [nltk_data] Downloading package cmudict to /root/nltk_data...
4.130 [nltk_data]   Unzipping corpora/cmudict.zip.
13.24 Traceback (most recent call last):
13.24   File "/app/melo/init_downloads.py", line 5, in <module>
13.24     from melo.api import TTS
13.24   File "/app/melo/api.py", line 18, in <module>
13.24     from .download_utils import load_or_download_config, load_or_download_model
13.24   File "/app/melo/download_utils.py", line 4, in <module>
13.24     from cached_path import cached_path
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/__init__.py", line 13, in <module>
13.24     from ._cached_path import cached_path
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/_cached_path.py", line 15, in <module>
13.24     from .schemes import (
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/schemes/__init__.py", line 6, in <module>
13.24     from .s3 import S3Client
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/schemes/s3.py", line 16, in <module>
13.24     class S3Client(SchemeClient):
13.24   File "/usr/local/lib/python3.9/site-packages/cached_path/schemes/s3.py", line 18, in S3Client
13.24     botocore.exceptions.HTTPClientError,
13.24 AttributeError: module 'botocore.exceptions' has no attribute 'HTTPClientError'
------
Dockerfile:11
--------------------
   9 |     RUN pip install -e .
  10 |     RUN python -m unidic download
  11 | >>> RUN python melo/init_downloads.py
  12 |
  13 |     CMD ["python", "./melo/app.py", "--host", "<IP_ADDRESS>", "--port", "8888"]
--------------------
ERROR: failed to solve: process "/bin/sh -c python melo/init_downloads.py" did not complete successfully: exit code: 1

The botocore and boto3 libraries took a lot of time to be installed because it was searching for good version.
Any idea about the issue ? Thanks.

Try modifying the requirements.txt file to include
botocore==1.34.88cached_path==1.6.2

This solved the issue thanks.


Training is slow for Norman perturbation prediction benchmark

Hi,
I am currently trying to reproduce the results from the perturbation prediction benchmark for the Norman data. I am able to run the run_singlecell_maeautobin-0.1B-res0-norman.sh script on our NVIDIA L40S graphics card. However, the training takes quite long: I was able to complete one epoch in ~8h. If I run GEARS (without scfoundation) on the same data, I can complete 20 epochs in half the time. Is this expected? How long did the training for the Norman benchmark take for you?
Best,
Constantin

It depends on the card you used, in our case, we used the A100, and it took hours to finish one epoch.

Thanks, that is useful. I was worried that I was doing something wrong, but I guess that my experience is not unusual then. Just as another data point, I now managed to complete 5 epochs in 72 hours on a L40S.


Update router5 to 8.x

We are currently on 7.0.2 - looks like 8.0 was released 23 days ago, although as of today (Mar 24) the CHANGELOG does not appear to be fully updated.  Worse, the docs on https://router5.js.org/migration/migrating-from-6.x-to-7.x have a migration link from 7 > 8 but it's just the 6 > 7 content at the moment...
Not entirely sure what the breaking changes might be, or how much of an update this represents, but worth staying on top of this core library.

Just checked and docs are still out of date.  Filed this:
https://github.com/router5/router5/issues/461

Closing as we have not had any issues with or needs from Router5, and docs still remain outdated


Plot/export from parameters combination

Add a JSON field with the parameters plot, like (time, n_proc). Specific cases will always require the user to manipulate the pkl file manually, but generic case should be easy enough.

Sufficiently done by #18


Feature Requests:  Rules ❤ Schemas In Launch Server Side

Expected Behaviour
Within Launch SSF:  allow users to reference schema elements directly as they do now with Data Elements.

Actual Behaviour
Reproduce Scenario (including but not limited to)
Steps to Reproduce
Platform and Version
Sample Code that illustrates the problem
Logs taken while reproducing problem

@RudiShumpert Here are the JIRA tickets that are tracking this effort:
https://jira.corp.adobe.com/browse/CORE-54152
https://jira.corp.adobe.com/browse/CORE-54153
https://jira.corp.adobe.com/browse/CORE-54154


Additional animation configuration

this is a great tool. very useful for css animation noobs like me :+1:
this tool would be a lot more awesome if we can have additional animation configuration such as animation-delay, animation-duration, etc.

Hi, we launched AniJS Studio on KickStarter, that allow to designers and programmers add animations and interactions for Web pages in an easy and intuitive way. Please, take a look at the project and if you find it interesting or simply want to help us, you can make a small donation. I would be grateful, Greetings Dariel


Fixing retrospective code for specialisation constants

This was a weird on but it caused the vulkan mobile renderer to fail rendering lights for ages.
When parsing the compiled shader to obtain the default values for our specialization constants, when assigning a bool it failed if the previous values was a floating point value. It may also fail with ints but I didn't test all edge cases.
My theory here is that because any non-zero value is true, setting the bool was getting confused. The fix was really simple, just reset it's current value before the boolean is assigned.
I also added SpvReflectSpecializationConstant *spc = spec_constants[j]; because it made debugging easier though debugging this is a pain because this code is threaded.
The real fix is just the onliner sconst.int_value = 0.0; // clear previous value JIC before the case statement :)

Thanks!


Polish and refine all Skeleton features

To prep for v1 I'd like to do one more all-encompassing pass to prepare and polish our various features for launch. This may include, but is not limited to the following:

Code review, code cleanup, finalize the API/props
Improve the styling, ensure consistency
Add or improve animations (where relevant)
Improved and expanded interactive examples (where relevant)

We'll break this into sub-tasks to ensure we cover the entire project. But the three main areas of focus will include:

https://github.com/skeletonlabs/skeleton/issues/837
https://github.com/skeletonlabs/skeleton/issues/857
Utility Features (coming soon)
Do a FIXME pass to find issues documented inline within the codebase

Selection animation: https://play.tailwindcss.com/Qd98eMhkxy

Forms: cover additional selectors such as readonly:
https://tailwindcss.com/docs/hover-focus-and-other-states#read-only

Typogrphy.css - consider dropping paragraph styles. Allow them to inherit form the base text color by default:

https://github.com/skeletonlabs/skeleton/issues/825

Buttons: click effect stays in pressed state if you click and drag off.

Form components: test binding and use:enhance features for non-standard inputs. Ensure stores work with these.

Dropzone:

Move the SvgIcon to the /docs directory and remove it from the package index.ts

@JustBarnt I've migrated your component issue here: https://github.com/skeletonlabs/skeleton/issues/857

NOTE: for utility overlays (modals, drawers, toasts, etc) make sure to indicate these should reside ABOVE the app shell, not within it.

Since ak4zh didn't do it:

We might want to see if we can find a way to move the modal when keyboards reduce the screen space.
Not sure how to go about that though

@ak4zh @Sarenor
This is one of those annoying mobile web issue that I've never found a good solution for. The mobile browsers will try and scroll to keep the selected input on the screen, but if there's not enough room to scroll it won't "reach" it. The best part is browsers give zero means to know when the onscreen keyboard is active, so really there's nothing that can be done in the current iteration of the modal system.
What I'll need to do is set a particular breakpoint where modals auto-position near the top rather than remaining in the center. It won't fix every use case (especially large modals) but it'll be a step in the right direction.

Abstract tooltip type out to external file for use by end users:
https://github.com/skeletonlabs/skeleton/blob/dev/src/lib/utilities/Tooltip/tooltip.ts#L3

https://captaincodeman.github.io/svelte-headlessui/popover/
Daniel_hayes on Discord switched to this to be able to open a popover/menu from 2 different buttons

https://www.scottohara.me/blog/2023/01/26/use-the-dialog-element.html

@riziles suggested a method to improve the modal scrollbars here. We'll investigate this when we get to Modals:
https://github.com/skeletonlabs/skeleton/issues/890

Reminder: toast buttons need a named selector wrapping class.

All reported Utility improvement comments have been noted on the new Utilities polish pass ticket here:
https://github.com/skeletonlabs/skeleton/issues/922
Those respective comments have been removed from this thread.

Given that all child tickets have now been created, I'm going to go ahead and close this out. This ticket has served it's purpose and is now redundant.