No full config list in README

There's all config properties list and command examples before in README and now under flank_java branch, but not under master branch, need command line examples and config list in README.

The master branch readme contains a full listing of all options.

Ok, could you help confirm a few things?

Any old options that not listed, e.g. debug-prints or name changed means either it's no longer supported or new version applies to new option names?
On Android side, will it support config.properties now?
Any command line arguments support as before? e.g. https://github.com/TestArmada/flank/tree/flank_java#run-tests

3. Any command line arguments support as before? e.g.

Most command line arguments have been removed in favor of a yaml based file format.

Any old options that not listed, e.g. debug-prints or name changed means either it's no longer supported or new version applies to new option names?
On Android side, does it support config.properties now?

We standardized on the official gcloud yaml. This means the same config works with both flank and gcloud:

gcloud firebase test android run flank.yml:gcloud
flank firebase test android run

If gcloud supports an option and Flank doesn't then that's typically a feature we'd want to add.

https://cloud.google.com/sdk/gcloud/reference/firebase/test/android/run

The legacy options from Flank Java (debug-prints) are not supported. The code base has completely been rewritten in Kotlin + APIs instead of Java + gcloud.
There's a #flank channel on https://firebase.community if you have more general usage questions.

Thanks, that's clear to me, will close the issue.


Add Readme file to the Drum-Kit project

Adding a README file to a GitHub project is crucial for providing essential information about the project to potential users and contributors. It  will enhance the project visibility, fosters collaboration, and ensures a smoother onboarding process for newcomers.
Please assign me with this issue.

@AtharvaShinde253 Thank you for providing your insight but it is not required as of now.


command for rewriting import paths

It would be nice if I could rewrite all dependencies of my package to the corresponding nut-version.
Something similar to running godep save -r github.com/fredr/mypackage/... that will rewrite all import paths in github.com/fredr/mypackage.
This would be to make sure I haven't imported locked packages form the GOPATH instead of the nut vendor dir. (i.e goimports probably chooses the GOPATH path)
And if it also could report any non-vendored packages would be nice (maybe that should be it's own command)
Makes sense?

Makes sense?

:+1:

I'm thinking of providing a flag that users could choose to fix import paths for source

cool, are you thinking a global flag, or a flag to the install command?

I'm thinking a flag to the install command since that's the only command for now related to rewriting import paths.

If you add this please consider a corresponding command that will change the import paths back to the unvendored packages. This would make path rewriting more or less feature equivalent to tools that  mess with the GOPATH.

If you add this please consider a corresponding command that will change the import paths back to the unvendored packages.

This shouldn't be hard to implement. But rewriting import paths and vendoring dependencies are the whole point of nut. I'd need to understand more why people would choose to vendor dependencies with nut but want to migrate away later.

I can think of one thing, and that is "unvendoring" a package when developing and testing new code in that package. Other package managers like npm and bower use a link command for that though https://docs.npmjs.com/cli/link

Actually replacing the vendored package with a symlink and keeping the importing code in the parent app using the vendored path seems like a nice idea.

I wonder how this will work out. All your source's import paths are referring to the vendored dependencies, e.g., github/jingweno/nut/internal/github.com/foo/bar. Unvendoring dependencies will cause the build to fail.

@jingweno let's take your case. "unvendoring" does the following:

rmdir github.com/jingweno/nut/internal/github.com/foo/bar
if $GOPATH/github.com/foo/bar does not exist - go get github.com/foo/bar
ln -s $GOPATH/github.com/foo/bar github.com/jingweno/nut/internal/github.com/fo/bar

that's about it.

I may not make myself clear. Dependencies are vendored and in the source, we're referring to dependencies like:
package main

import(
  "github.com/jingweno/nut/internal/github.com/foo/bar"
)

func main() {
  ...
}

If we unvendor the dependencies into $GOPATH/github.com/foo/bar without rewriting their import paths as well, the build will fail for main. That's why I want to understand more why people would want this.

the way I see it, unvendoring means checking out a pristine copy of those packages with the manifest's current revision, into GOPATH, not copying the vendored copy back there.
It's mostly useful IMO for first-party dependencies, i.e. stuff you're still actively working on (something like pip install -e). Personally I don't want to vendor those at all, if they're in my control, I want to directly import them from my own git repo.

Personally I don't want to vendor those at all, if they're in my control, I want to directly import them from my own git repo.

nut doesn't enforce a project to vendor all dependencies. There could be some dependencies outside of ./internal/.... Just refer to those dependencies like you usually do without nut. Am I missing anything here?

No, that's precisely why I prefer nut to godep :) to me the issue discussed here is not important, I was just commenting on the technical aspects of how to implement it.

I was only talking about the import paths. That if you provide a command to rewrite them to use the vendored package, you provide a corresponding command to rewrite them back to the non-vendored versions. It wouldn't affect what packages were in the vendored area (the internal directory).
My main use case is being able to switch to the versions of packages you have installed on your GOPATH and back. This can be useful when testing new versions and the like. I do this with godep currently by using its path manipulation method (using the godep command). Given the communities leaning toward rewriting as the long term solution I'd like to see the ability to switch back and forth maintained.

I've added rewriting as a separate command (nut vendor) in my own fork if anyone wants it. I don't think it should be a separate command so I didn't make a PR of it. https://github.com/EverythingMe/nut/commit/f10e84ac3a74a8588523a3a9d323803207b55a02


ImageGeometry and AcquisitionGeometry should be able to create (empty) instance of ImageData or AcquisitionData

See this thread on SIRF repository.

I guess we should create a Factory for this in the *Geometry classes

Currently in SIRF there is a method in the PET ImageData called create_uniform_copy that handles this. There is not equivalent for MR.
In SIRF there is nothing like ImageGeometry or AcquisitionGeometry, there is the concept of template: a ImageData template is somewhat just the description of the ImageData without the associated array.
It might be worth thinking to move in that direction at some point.

This note is basically for me. I'm thinking that we'll have to use tricks like this factory  to make things behave properly.
Such factory can change methods and add methods to existing classes. This is relevant for #194 .
class cilPluginToSIRFFactory(object):
    '''Factory to create SIRF wrappers for CCPi CIL plugins'''
    @staticmethod
    def getInstance(thetype, **kwargs):
        '''Returns an instance of a CCPi CIL plugin wrapped to work on SIRF DataContainers'''
        obj = thetype(**kwargs)
        orig_prox = obj.prox
        obj.prox = cilPluginToSIRFFactory.prox(orig_prox,
                                               obj.__class__.__name__)
        return obj
    @staticmethod
    def prox(method, classname):
        def wrapped(x, sigma):
            '''Wrapped method'''
            print("calling ", classname)
            if isinstance(x, sirf.Gadgetron.ImageData):
                # if the data is MR => complex we operate the regulariser
                # only on the real part
                X = x.as_array()
                out = method(cilDataContainer(X.real), sigma)
                X.real = out.as_array()[:]
                y = x.copy()
                y.fill(X)
            else:
                out = method(x, sigma)
                y = x.copy()
                y.fill(out)
            print("done")

            return y
        return wrapped


Installation stuck

Hi
I am facing a error it may be a bug https://prnt.sc/t5pqxk. It stuck with the installation and moving forward or finishing up the installation.
Regards
saju

Hi @wontone18
you may add the database credentials .env file then run php artisan migrate with fresh DB
If any error attempts while executing migration then show the screenshot.
Thanks.

lol  let me try that way to.


Configure some indexer parameters via envvars

No changes are required, but @luarx just pinging you to be aware of this


Need support for namespaces other than quay-enterprise

This turns out to be a hardcoded quay-enterprise namespace. We need a way to customize the namespace that quay is deployed (e.g. quay-aaaa, quay-bbbb, ....) for multiple Quay Deployments on one OCP Cluster.
Related to #28

Fixed.


Toggling between JsonApi and Laravel Exceptions

Hi there,
I'm curious about the way you handle Exceptions in development so that:

they are not catched by JsonApi (without commenting the Handler each and every time)
they are not formatted as Json even if Accept JSON is defined in header

The key here is to easily be able to toggle between all options, as in development you might want to check if the error is correctly catched and displayed in JsonApi as well as rendering the full error in a Laravel way for full debugging purposes.
Did I miss something obvious?
Thanx

I'm going to close this because the question was answered... feel free to re-open or open a different issue if you think there's anything else to answer!


Fix failing tests

This is both locally and on Travis CI.

Still need to check it out on Travis and get it fixed there.


Client side translations

add client side translations using minetest.translate

It seems that my minetest copy is the problem why it doesn't work...

it is done...


Mark the stack as noexec in asm files

A missing .note.GNU-stack section implicitly marks the stack as PROT_EXEC:
warning: ProbeCtl.o: missing .note.GNU-stack section implies executable stack
NOTE: This behaviour is deprecated and will be removed in a future version of the linker

AFAICT, Xpedite doesn't rely on an executable stack, so we can explicitly mark it as noexec.

@octurion Thank you for spotting the issue and we are glad to receive the PR.
Since this is the first time you are contributing, we need the PR to include a DCO document.
Can you please take a look at the instructions here?
Please let me know if you need any details / clarification.
Regards
Mani

Please let me know if you need any details / clarification.

Just a quick question: Is it okay if I e.g. obfuscate my email address in my DCO so that it can't be easily scraped?

Please let me know if you need any details / clarification.

Just a quick question: Given that the DCO document is going to be public, is it okay if I e.g. obfuscate my email address in my DCO so that it can't be easily scraped?

yes, of course.

DCO added :+1:

DCO added 👍

Excellent. Thank you !


RHEL7 service name for nfs is nfs-service.

The service name for nfs in RehHat-7 is now nfs-service.  line 113 of params.pp.

fixed in https://github.com/derdanne/puppet-nfs/tree/fix_rhel7_issues

confirmed good..


Error: Direct kernel connection broken

Issue Type: Bug
Open any file.ipynb and attempt to run a cell.
print('hello')
expect output : hello
receive:  'Error: Direct kernel connection broken'instead with the following details.
Error: Direct kernel connection broken
at getDisposedError (c:\Users\forresr2.vscode\extensions\ms-python.python-2020.8.103604\out\client\extension.js:24:684530)
at f.P.handleCodeRequest (c:\Users\forresr2.vscode\extensions\ms-python.python-2020.8.103604\out\client\extension.js:48:467398)
at c:\Users\forresr2.vscode\extensions\ms-python.python-2020.8.103604\out\client\extension.js:48:480019
at runMicrotasks ()
at processTicksAndRejections (internal/process/task_queues.js:85:5)
Extension version: 2020.8.103604
VS Code version: Code 1.48.2 (a0479759d6e9ea56afa657e454193f72aef85bd0, 2020-08-25T10:13:11.295Z)
OS version: Windows_NT x64 10.0.17134

System Info

Item
Value

CPUs
Intel(R) Core(TM) i5-6300U CPU @ 2.40GHz (4 x 2496)

GPU Status
2d_canvas: enabledflash_3d: enabledflash_stage3d: enabledflash_stage3d_baseline: enabledgpu_compositing: enabledmultiple_raster_threads: enabled_onoop_rasterization: disabled_offprotected_video_decode: unavailable_offrasterization: enabledskia_renderer: disabled_off_okvideo_decode: enabledviz_display_compositor: enabled_onviz_hit_test_surface_layer: disabled_off_okwebgl: enabledwebgl2: enabled

Load (avg)
undefined

Memory (System)
7.88GB (3.46GB free)

Process Argv

Screen Reader
no

VM
0%

It seems that after an exception occurs in the underlying python process, the connection is "lost".
I also have the same issue requiring to restart vscode.
Would be nice if the "Error: Direct kernel connection broken" situation could be detected and the "kernel" be restarted without having to quit vscode

@jeanga @fedmag @kmcmearty @JManuel-industrialist @GitForrest @valueforlife @ashutoshIITK
I'm sorry you are all coming across this issue & thank you for reporting this here.
We would like to address this problem.
In order to help you and get to the bottom of this issue, please could you try the following:

Please change the VS Code setting Jupyter->Logging->Level to debug
Restart VSC Code & continue working

You might get prompts to disable this (please ignore this for now)

If you do come across the issue once again,

Go into your Jupyter output panel & copy the contents from there & paste it here (or save it to a text file & upload it here)

Other information

What is your OS
What version of Python are you on
Is this a local or remote Jupyter server?
Are you using VS Code remote over SSH?

thank you.

yes

And I use the neweset version of vscode on Windows 10 (1909), python3.9

Same issue here.

I have the same bug when I read a huge .csv, some Idea?
My laptop has:
Ubuntu 20.04
python 3.8
local Jupyter server and VSC

@oaa2020 @seedergy @DLesmes
Please provide the information requested here https://github.com/microsoft/vscode-jupyter/issues/1706#issuecomment-729085096

@DonJayamanne
for me it happens when i try to instance and fit a facebook prophet predictor.
What is your OS: windows
What version of Python are you on: 3.7.9
Is this a local or remote Jupyter server?: local
Are you using VS Code remote over SSH?: local
jypyter output:
Info 2020-12-01 16:56:16: Submitting code for 59996e2f-d7f1-4a3c-b66e-509629ee5dfe Info 2020-12-01 16:56:16: Wait for sys info for 59996e2f-d7f1-4a3c-b66e-509629ee5dfe 0 Info 2020-12-01 16:56:16: Adding hash for 8 = 7bda92cab60d with 2 lines Error 2020-12-01 16:56:16: Error executing a cell:  [Error: Direct kernel connection broken 	at y.getDisposedError (c:\Users\n.symeou\.vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:32:674512) 	at f.D.handleCodeRequest (c:\Users\n.symeou\.vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:49:532850) 	at c:\Users\n.symeou\.vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:49:546279 	at runMicrotasks (<anonymous>) 	at processTicksAndRejections (internal/process/task_queues.js:94:5)] Info 2020-12-01 16:56:16: Finished execution for 319915de-ab8b-4f00-aae1-1a076da598f4
hope this helps.

@NSymeou
Please could you provide the rest of the logs. I'd like to see what's going on before the error occurs.

@DonJayamanne
oh sorry, that was all it showed.
I restarted vscode and here is the full log:
Info 2020-12-02 08:44:33: Loading web panel. Panel is notset
Info 2020-12-02 08:44:33: Loading web view...
Info 2020-12-02 08:44:33: Web view created.
Info 2020-12-02 08:44:33: Waiting for jupyter server and web panel ...
Info 2020-12-02 08:44:33: Creating raw notebook for history://bfa335fe-2253-4553-a179-63c3526e5fbd
Info 2020-12-02 08:44:33: Getting preferred kernel for history://bfa335fe-2253-4553-a179-63c3526e5fbd
Info 2020-12-02 08:44:33: Searching for kernel based on {} for ...\Documents\ML\Predictive Planning\prophet_testing.py
Info 2020-12-02 08:44:33: Find kernel spec, Class name = C, completed in 260ms, has a falsy return value, Arg 1: Uri:...\prophet_testing.py, Arg 2: undefined, Arg 3: undefined, Return Value: undefined
Info 2020-12-02 08:44:33: installMissingDependencies ...\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe
Info 2020-12-02 08:44:33: > ~\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\pythonFiles\pyvsc-run-isolated.py -c "import ipykernel"

~\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\pythonFiles\pyvsc-run-isolated.py -c "import ipykernel"
Info 2020-12-02 08:44:34: Install Missing Dependencies, Class name = f, completed in 922ms, has a falsy return value, Return Value: 0
Info 2020-12-02 08:44:34: Find kernel spec, Class name = T, completed in 1199ms, has a truthy return value, Arg 1: <Uri:...\Documents\ML\Predictive Planning\prophet_testing.py>, Arg 2: undefined, Arg 3: undefined, Arg 4: undefined, Return Value: {"kind":"startUsingPythonInterpreter","interpreter":{"architecture":3,"path":"...\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe","version":{"options":{"loose":false,"includePrerelease":false},"loose":false,"raw":"3.7.9-final","major":3,"minor":7,"patch":9,"prerelease":["final"],"build":[],"version":"3.7.9-final"},"sysVersion":"3.7.9 (default, Aug 31 2020, 17:10:11) [MSC v.1916 64 bit (AMD64)]","sysPrefix":"...\AppData\Local\Continuum\anaconda3\envs\ML2","fileHash":"378d4f66a4d7f74880d9bbd33490e70ec83f93bf182797b2a162b65d67ae65085ecf5271a1ecb2d78dcce3a45c869e5076a810b7d3ae5754bb2327f6edfa3ed1","companyDisplayName":"Anaconda, Inc.","envType":"Conda","envPath":"...\AppData\Local\Continuum\anaconda3\envs\ML2","envName":"ML2","displayName":"Python 3.7.9 64-bit ('ML2': conda)"}}
Error 2020-12-02 08:44:34: Jupyter Kernel Spec not found for a local connection
Info 2020-12-02 08:44:34: Computing working directory history://bfa335fe-2253-4553-a179-63c3526e5fbd
Info 2020-12-02 08:44:34: Connecting to raw session for history://bfa335fe-2253-4553-a179-63c3526e5fbd
Info 2020-12-02 08:44:34: > ~\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\pythonFiles\pyvsc-run-isolated.py -c "import ipykernel"
~\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\pythonFiles\pyvsc-run-isolated.py -c "import ipykernel"
Info 2020-12-02 08:44:34: Python Daemon (pid: 1552): Execute rpc method start_prewarmed_kernel in DS Daemon
Info 2020-12-02 08:44:34: Python Daemon (pid: 1552): Execute rpc method start_prewarmed_kernel from ...\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe
Info 2020-12-02 08:44:34: Python Daemon (pid: 1552): Start pre-warmed Kernel in DS Kernel Launcher Daemon 12652 with args ['ipykernel_launcher', '--ip=<IP_ADDRESS>', '--stdin=9003', '--control=9001', '--hb=9000', '--Session.signature_scheme="hmac-sha256"', '--Session.key=b"584de360-1a95-4120-bd1d-262efbaff14e"', '--shell=9002', '--transport="tcp"', '--iopub=9004', '--f=...\AppData\Local\Temp\tmp-108721ll1o1c67tuS.json']
Info 2020-12-02 08:44:35: Web view react rendered
Info 2020-12-02 08:44:35: Request for onigasm file at ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\node_modules\onigasm\lib\onigasm.wasm
Info 2020-12-02 08:44:35: Request for tmlanguage file.
Info 2020-12-02 08:44:35: Searching for token colors ...
Info 2020-12-02 08:44:35: Attempting search for colors ...
Info 2020-12-02 08:44:35: Searching for token colors ...
Info 2020-12-02 08:44:35: Attempting search for colors ...
Info 2020-12-02 08:44:35: Searching for token colors ...
Info 2020-12-02 08:44:35: Attempting search for colors ...
Info 2020-12-02 08:44:35: Searching for token colors ...
Info 2020-12-02 08:44:35: Attempting search for colors ...
Info 2020-12-02 08:44:35: Raw session started and connected
Started kernel Python 3.7.9 64-bit ('ML2': conda)
Info 2020-12-02 08:44:35: Initial setup for history://bfa335fe-2253-4553-a179-63c3526e5fbd starting ...

Info 2020-12-02 08:44:36: Searching for token colors ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading base colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Loading colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Searching for token colors ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Searching for token colors ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading base colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Loading colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Loading colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Searching for token colors ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Loading colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Using colors to generate CSS ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading base colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Loading base colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Using colors to generate CSS ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading base colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading base colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Loading base colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Attempting search for colors ...
Info 2020-12-02 08:44:36: Loading base colors from ...\AppData\Local\Programs\Microsoft VS Code\resources\app\extensions\theme-monokai\themes\monokai-color-theme.json ...
Info 2020-12-02 08:44:36: Using colors to generate CSS ...
Info 2020-12-02 08:44:36: Using colors to generate CSS ...
Info 2020-12-02 08:44:36: Using colors to generate CSS ...
Info 2020-12-02 08:44:36: Using colors to generate CSS ...
Info 2020-12-02 08:44:36: Using colors to generate CSS ...
Info 2020-12-02 08:44:36: Using colors to generate CSS ...
Info 2020-12-02 08:44:37: Submitting code for 58368e1f-3936-4806-9fba-8a2171cb23ec
Info 2020-12-02 08:44:37: Wait for sys info for 58368e1f-3936-4806-9fba-8a2171cb23ec 0
Info 2020-12-02 08:44:37: Kernel switching to busy
Info 2020-12-02 08:44:37: Kernel switching to idle
Info 2020-12-02 08:44:37: Kernel switching to busy
Info 2020-12-02 08:44:37: Kernel switching to idle
Info 2020-12-02 08:44:37: Adding hash for 1 = 7bda92cab60d with 2 lines
Info 2020-12-02 08:44:37: Kernel switching to busy
Info 2020-12-02 08:44:39: Submitting code for 58368e1f-3936-4806-9fba-8a2171cb23ec
Info 2020-12-02 08:44:39: Wait for sys info for 58368e1f-3936-4806-9fba-8a2171cb23ec 0
Info 2020-12-02 08:44:39: Adding hash for 2 = 04fa6300e882 with 5 lines
Info 2020-12-02 08:44:40: Kernel switching to idle
Info 2020-12-02 08:44:40: Finished execution for fb087967-6670-42db-ace7-68eff2055e30
Info 2020-12-02 08:44:40: Kernel switching to busy
Info 2020-12-02 08:44:41: Kernel switching to idle
Info 2020-12-02 08:44:41: Finished execution for 5e60b61d-fdda-43e2-9d81-760a72797d70
Info 2020-12-02 08:44:41: Submitting code for 58368e1f-3936-4806-9fba-8a2171cb23ec
Info 2020-12-02 08:44:41: Wait for sys info for 58368e1f-3936-4806-9fba-8a2171cb23ec 0
Info 2020-12-02 08:44:41: Adding hash for 3 = 1ab3c9387252 with 2 lines
Info 2020-12-02 08:44:41: Kernel switching to busy
Info 2020-12-02 08:44:51: KernelProcess output: Content-Length: 136
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc": "2.0", "method": "log", "params": {"level": "WARNING", "msg": "Kernel has exited with exit code<PHONE_NUMBER>, ", "pid": 1552}}
Warn 2020-12-02 08:44:51: Python Daemon (pid: 1552): Kernel has exited with exit code<PHONE_NUMBER>,
Info 2020-12-02 08:44:51: KernelProcess output: Content-Length: 94
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "method": "kernel_died", "params": {"exit_code":<PHONE_NUMBER>, "reason": ""}}
Error 2020-12-02 08:44:51: Kernel died [r [Error]: Kernel died with exit code<PHONE_NUMBER>.
at ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:47:767567
at ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:47:432664
at ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:47:432882
at Immediate._onImmediate (....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:47:434447)
at processImmediate (internal/timers.js:439:21)] {
exitCode:<PHONE_NUMBER>,
reason: ''
}
Error 2020-12-02 08:44:51: KernelProcess Exit Exit -<PHONE_NUMBER>,  [r [Error]: Kernel died with exit code<PHONE_NUMBER>.
at ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:47:767567
at ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:47:432664
at ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:47:432882
at Immediate._onImmediate (....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:47:434447)
at processImmediate (internal/timers.js:439:21)] {
exitCode:<PHONE_NUMBER>,
reason: ''
}
Error 2020-12-02 08:44:51: Disposing session as kernel process died ExitCode:<PHONE_NUMBER>, Reason: Kernel died with exit code<PHONE_NUMBER>.
Error 2020-12-02 08:44:51: Raw kernel process exited code: [object Object]
Info 2020-12-02 08:44:51: Shutdown session - current session
Info 2020-12-02 08:44:51: shutdownSession 85c370b8-7a17-4e69-8c1f-e6fff7152380 - start
Info 2020-12-02 08:44:51: Finished execution for 1fffbd23-8b06-407c-872b-2df8aae93a9d
Info 2020-12-02 08:44:51: shutdownSession 85c370b8-7a17-4e69-8c1f-e6fff7152380 - shutdown complete
Info 2020-12-02 08:44:51: Shutdown session - get restart session
Info 2020-12-02 08:44:51: Shutdown session - shutdown restart session
Info 2020-12-02 08:44:51: shutdownSession 72ad82b0-2643-4a0a-8950-7f5e3aee8010 - start
Info 2020-12-02 08:44:51: KernelProcess output: Content-Length: 131
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "method": "log", "params": {"level": "INFO", "msg": "Execute rpc method kill_kernel in DS Daemon", "pid": 1552}}Content-Length: 204
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "method": "log", "params": {"level": "INFO", "msg": "Execute rpc method kill_kernel from ...\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe", "pid": 1552}}
Info 2020-12-02 08:44:51: KernelProcess output: Content-Length: 131
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "method": "log", "params": {"level": "INFO", "msg": "Execute rpc method kill_kernel in DS Daemon", "pid": 4296}}Content-Length: 204
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "method": "log", "params": {"level": "INFO", "msg": "Execute rpc method kill_kernel from ...\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe", "pid": 4296}}Content-Length: 128
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "method": "log", "params": {"level": "INFO", "msg": "Kill kernel in DS Kernel Launcher Daemon", "pid": 4296}}Content-Length: 43
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "id": 2, "result": null}
Info 2020-12-02 08:44:51: Python Daemon (pid: 1552): Execute rpc method kill_kernel in DS Daemon
Info 2020-12-02 08:44:51: Python Daemon (pid: 4296): Execute rpc method kill_kernel in DS Daemon
Info 2020-12-02 08:44:51: KernelProcess output: Content-Length: 128
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "method": "log", "params": {"level": "INFO", "msg": "Kill kernel in DS Kernel Launcher Daemon", "pid": 1552}}Content-Length: 43
Content-Type: application/vscode-jsonrpc; charset=utf8
{"jsonrpc": "2.0", "id": 3, "result": null}
Info 2020-12-02 08:44:51: Python Daemon (pid: 1552): Execute rpc method kill_kernel from ...\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe
Info 2020-12-02 08:44:51: Python Daemon (pid: 4296): Execute rpc method kill_kernel from ...\AppData\Local\Continuum\anaconda3\envs\ML2\python.exe
Info 2020-12-02 08:44:51: Python Daemon (pid: 1552): Kill kernel in DS Kernel Launcher Daemon
Info 2020-12-02 08:44:51: Python Daemon (pid: 4296): Kill kernel in DS Kernel Launcher Daemon
Info 2020-12-02 08:44:51: shutdownSession 72ad82b0-2643-4a0a-8950-7f5e3aee8010 - shutdown complete
Info 2020-12-02 08:44:51: Shutdown session -- complete
Info 2020-12-02 08:44:51: KernelProcess Exit Exit - null
Info 2020-12-02 08:44:51: KernelProcess Exit Exit - null
Info 2020-12-02 08:44:58: Submitting code for 58368e1f-3936-4806-9fba-8a2171cb23ec
Info 2020-12-02 08:44:58: Wait for sys info for 58368e1f-3936-4806-9fba-8a2171cb23ec 0
Info 2020-12-02 08:44:58: Adding hash for 4 = dbc02d682846 with 2 lines
Error 2020-12-02 08:44:58: Error executing a cell:  [Error: Direct kernel connection broken
at y.getDisposedError (....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:32:674512)
at f.D.handleCodeRequest (....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:49:532850)
at ....vscode\extensions\ms-toolsai.jupyter-2020.11.392013122\out\client\extension.js:49:546279
at processTicksAndRejections (internal/process/task_queues.js:94:5)]
Info 2020-12-02 08:44:58: Finished execution for a9a3306e-594c-4131-984c-fe0fd057f158

@DonJayamanne
i tried my code in jupyter lab and it kills the kernel there too. so it's not a vscode issue. sorry about that :/

@DonJayamanne
I have the same problem. I suspect this is due to some  memory issue, since I found this often occurs when playing with large arrays. Specifically, re-executing scripts that generating these large arrays will also produce this issue.
Below is my info:

OS:

Linux Red-Hat 7.6

What version of Python are you on

Python 3.8.5, via Anaconda

Is this a local or remote Jupyter server?

Yes

Are you using VS Code remote over SSH?

yes

Logging

Info 2020-12-08 00:05:25: Kernel switching to busy
Info 2020-12-08 00:05:26: KernelProcess output: Content-Length: 118
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","method":"log","params":{"level":"WARNING","msg":"Kernel has exited with exit code -9, ","pid":6225}}
Warn 2020-12-08 00:05:26: Python Daemon (pid: 6225): Kernel has exited with exit code -9,
Info 2020-12-08 00:05:26: KernelProcess output: Content-Length: 78
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","method":"kernel_died","params":{"exit_code":-9,"reason":""}}
Error 2020-12-08 00:05:26: Kernel died [r [Error]: Kernel died with exit code -9.
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:47:767560
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:47:432657
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:47:432875
  at Immediate._onImmediate (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:47:434440)
  at processImmediate (internal/timers.js:439:21)] {
  exitCode: -9,
  reason: ''
}
Error 2020-12-08 00:05:26: KernelProcess Exit Exit - -9,  [r [Error]: Kernel died with exit code -9.
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:47:767560
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:47:432657
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:47:432875
  at Immediate._onImmediate (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:47:434440)
  at processImmediate (internal/timers.js:439:21)] {
  exitCode: -9,
  reason: ''
}
Error 2020-12-08 00:05:26: Disposing session as kernel process died ExitCode: -9, Reason: Kernel died with exit code -9.
Error 2020-12-08 00:05:26: Raw kernel process exited code: [object Object]
Info 2020-12-08 00:05:26: Shutdown session - current session
Info 2020-12-08 00:05:26: shutdownSession 60b961d7-e280-4b65-917b-2533045c6971 - start
Info 2020-12-08 00:05:26: Finished execution for 6e0d2e3c-bfd8-4c9e-91f7-96773da81fe8
Info 2020-12-08 00:05:26: shutdownSession 60b961d7-e280-4b65-917b-2533045c6971 - shutdown complete
Info 2020-12-08 00:05:26: Finished executing cell 6e0d2e3c-bfd8-4c9e-91f7-96773da81fe8
Info 2020-12-08 00:05:26: Shutdown session - get restart session
Info 2020-12-08 00:05:26: Shutdown session - shutdown restart session
Info 2020-12-08 00:05:26: shutdownSession 415ecd96-5579-4b1d-b06b-b762a5c21c0e - start
Info 2020-12-08 00:05:26: KernelProcess output: Content-Length: 121
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Execute rpc method kill_kernel in DS Daemon","pid":6225}}Content-Length: 185
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Execute rpc method kill_kernel from \/ccs\/home\/hzfmer\/file_back\/programs\/andes\/anaconda3\/bin\/python","pid":6225}}Content-Length: 118
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Kill kernel in DS Kernel Launcher Daemon","pid":6225}}Content-Length: 38
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","id":2,"result":null}
Info 2020-12-08 00:05:26: Python Daemon (pid: 6225): Execute rpc method kill_kernel in DS Daemon
Info 2020-12-08 00:05:26: KernelProcess output: Content-Length: 121
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Execute rpc method kill_kernel in DS Daemon","pid":6224}}Content-Length: 185
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Execute rpc method kill_kernel from \/ccs\/home\/hzfmer\/file_back\/programs\/andes\/anaconda3\/bin\/python","pid":6224}}Content-Length: 118
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","method":"log","params":{"level":"INFO","msg":"Kill kernel in DS Kernel Launcher Daemon","pid":6224}}Content-Length: 38
Content-Type: application/vscode-jsonrpc; charset=utf8

{"jsonrpc":"2.0","id":3,"result":null}
Info 2020-12-08 00:05:26: Python Daemon (pid: 6225): Execute rpc method kill_kernel from /ccs/home/hzfmer/file_back/programs/andes/anaconda3/bin/python
Info 2020-12-08 00:05:26: Python Daemon (pid: 6224): Execute rpc method kill_kernel in DS Daemon
Info 2020-12-08 00:05:26: Python Daemon (pid: 6225): Kill kernel in DS Kernel Launcher Daemon
Info 2020-12-08 00:05:26: Python Daemon (pid: 6224): Execute rpc method kill_kernel from /ccs/home/hzfmer/file_back/programs/andes/anaconda3/bin/python
Info 2020-12-08 00:05:26: Python Daemon (pid: 6224): Kill kernel in DS Kernel Launcher Daemon
Info 2020-12-08 00:05:26: shutdownSession 415ecd96-5579-4b1d-b06b-b762a5c21c0e - shutdown complete
Info 2020-12-08 00:05:26: Shutdown session -- complete
Info 2020-12-08 00:05:26: KernelProcess Exit Exit - null
Info 2020-12-08 00:05:26: KernelProcess Exit Exit - null
Error 2020-12-08 00:05:30: Exception attempting to retrieve hover for variables [Error: Direct kernel connection broken
  at y.getDisposedError (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:32:674486)
  at f.D.handleCodeRequest (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:532850)
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:546279
  at runMicrotasks (<anonymous>)
  at processTicksAndRejections (internal/process/task_queues.js:94:5)]
Error 2020-12-08 00:05:37: Exception attempting to retrieve hover for variables [Error: Direct kernel connection broken
  at y.getDisposedError (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:32:674486)
  at f.D.handleCodeRequest (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:532850)
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:546279
  at processTicksAndRejections (internal/process/task_queues.js:94:5)]
Error 2020-12-08 00:05:38: Exception attempting to retrieve hover for variables [Error: Direct kernel connection broken
  at y.getDisposedError (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:32:674486)
  at f.D.handleCodeRequest (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:532850)
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:546279
  at processTicksAndRejections (internal/process/task_queues.js:94:5)]
Info 2020-12-08 00:05:41: Executing cell 6e0d2e3c-bfd8-4c9e-91f7-96773da81fe8
Info 2020-12-08 00:05:41: Submitting code for befe511b-645d-4dc1-bc1b-f9d9f8f4e545
Error 2020-12-08 00:05:41: Error executing a cell:  [Error: Direct kernel connection broken
  at y.getDisposedError (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:32:674486)
  at f.D.handleCodeRequest (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:532850)
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:546279
  at processTicksAndRejections (internal/process/task_queues.js:94:5)]
Info 2020-12-08 00:05:41: Finished execution for 6e0d2e3c-bfd8-4c9e-91f7-96773da81fe8
Info 2020-12-08 00:05:41: Finished executing cell 6e0d2e3c-bfd8-4c9e-91f7-96773da81fe8
Error 2020-12-08 00:05:43: Exception attempting to retrieve hover for variables [Error: Direct kernel connection broken
  at y.getDisposedError (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:32:674486)
  at f.D.handleCodeRequest (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:532850)
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:546279
  at processTicksAndRejections (internal/process/task_queues.js:94:5)]
Error 2020-12-08 00:06:09: Exception attempting to retrieve hover for variables [Error: Direct kernel connection broken
  at y.getDisposedError (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:32:674486)
  at f.D.handleCodeRequest (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:532850)
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:546279
  at processTicksAndRejections (internal/process/task_queues.js:94:5)]
Error 2020-12-08 00:07:40: Exception attempting to retrieve hover for variables [Error: Direct kernel connection broken
  at y.getDisposedError (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:32:674486)
  at f.D.handleCodeRequest (User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:532850)
  at User//.vscode-server/extensions/ms-toolsai.jupyter-2020.11.399280825/out/client/extension.js:49:546279
  at processTicksAndRejections (internal/process/task_queues.js:94:5)]

"""from scipy.cluster import hierarchy
from scipy.spatial.distance import pdist
import plotly.figure_factory as ff
distance_mat = pdist(data)
Z = hierarchy.linkage(distance_mat, 'single')
plt.figure(figsize=(10, 5))
dn = hierarchy.dendrogram(Z, color_threshold=0.5)
dn"""
Get the problem with this block of code using simple dataset (about 20x40000). Used file as jupyter notebook. No output for cell.
Python 3.8.3 , windows 10.

Same here, I am also facing the same issue.

Same here, I am also facing the same issue.

Same issue here.No fixes available yet?

Same issue here.No fixes available yet?

Can anybody on this issue, provide a repro scenario for this?

Can anybody on this issue, provide a repro scenario for this?

  Anyway, this post fixed things for me (as I could see I was getting some mkl fatal error):
https://stackoverflow.com/questions/36659453/intel-mkl-fatal-error-cannot-load-libmkl-avx2-so-or-libmkl-def-so, which boils down to:
conda install nomkl numpy scipy scikit-learn numexpr
conda remove mkl mkl-service

Looks like it might be related to matplotlib?  Anyway, this post fixed things for me (as I could see I was getting some mkl fatal error):
https://stackoverflow.com/questions/36659453/intel-mkl-fatal-error-cannot-load-libmkl-avx2-so-or-libmkl-def-so, which boils down to:
conda install nomkl numpy scipy scikit-learn numexpr
conda remove mkl mkl-service

The diverse contexts of the reports more likely indicate an unhandled exception in the underlying python process that is 'detected' (via the "Direct kernel connection broken" message) but the extension is unable to recover from it (start a new instance od python.exe).

The diverse contexts of the reports more likely indicate an unhandled exception in the underlying python process that is 'detected' (via the "Direct kernel connection broken" message) but the extension is unable to recover from it (start a new instance od python.exe).

If this is any help, I have been able to reproduce the error from cmd prompt also, so I question whether this is a VSCode issue or python issue. For me it happens running the pygmt mapping package when trying to visualize large datasets of data on a map (topography, shape files, etc.). Before I saw this thread, I manually entered my code line by line into the command prompt in a python session (>>>) and when I got to the visualization step, the command prompt simply booted me from python (no more >>>, all stored variables cleared upon re-opening a python session). This happened at the same command as when I see the kernel disconnect error in VSCode.  Here is the logging level debug information from my last VSCode
20210131_kernel_disconnect_logginglevel-debug_output.txt

I think the problem is from tornado , i used
pip install tornado==5.1.1
and it work normally no error now.

Hi folks, facing same issue, is this still a WIP? Thanks for your awesome work

As far as I can tell, the latest insider build of VSCode & extension fixed the issue for me.

@jeanga thanks for replying! I tried latest versions, but error still occurs! Please tell me what versions of insiders and extension work for you

Here is what I currently use:
VSCode Insider: 1.54
Python extension: v2021.2.582707922
Jupyter: v2021.3.593162453
HTH!
Jean

@jeanga Thanks!! I checked my versions, and I have the same! But I still have the error, hmmmm.... anyone have a solution here?

Is vscode able to reconnect to the kernel? Because this issue is not about the underlying problem in the python process... But rather vscode being unable to restart it.

@jeanga Please see my comment above. I was able to reproduce the pygmt error in cmd prompt. When I got to the step that trips it up in VSCode/Jupyter Notebook, it simply booted me from python within the cmd terminal. So, I recorded the logging-level debugging output from VSCode and posted it above. It does not seem to be strictly related to VSCode.

Is vscode able to reconnect to the kernel? Because this issue is not about the underlying problem in the python process... But rather vscode being unable to restart it.

Well, once the error occurs (cell running indefinitely), the kernel does not reconnect automatically, I then have to restart VSCode

@DonJayamanne

Go into your Jupyter output panel & copy the contents from there & paste it here (or save it to a text file & upload it here):

Other information

What is your OS: Windows10
What version of Python are you on: Python 3.8.8
Is this a local or remote Jupyter server? local
Are you using VS Code remote over SSH? local
VSCode Insiders Version: 1.54.0-insider (commit: 93c941bef8958021ede8fd7a28314af28ad85233; Date: 2021-02-25T05:15:20.021Z) - latest at time of post
Jupyter Extension Version: 2021.3.593162453 - latest at time of post

@MJimitater

Please could you upload the ipynb here (I'd like to see what is in cell 16 & 17)
Does this problem occur when you are using Jupyter classic?
Please could you enable logging as follows:

Open settings & go into Jupyter->Logging
Change the value to debug
Reload VS Code,
Attempt to repro the issue & then copy the output from the Jupyter output panel.

@DonJayamanne  Thanks for taking a look!!

Here is my ipynb notebook and my debug file debug.zip
Note that the error occurs after executing cell 12; if I comment that cell out however, it works.
This problem occurs in Jupyter classic as well as in insiders

I noticed how the kernel always throws this broken kernel connection error, when trying to enumerate through a Tensorflow Dataset holding close to 1 Million (1x1000) arrays. However, if I go down in size, then it works! Perhaps the error is linked to huge tf datasets?!

Note that this isn't just for TF.  In my case, I was using the Hand detector (MediaPipe) and having it detect hands from webcam using the code they provide at the link I shared.  When I forcibly exited the cv2 rendering window, it threw some error and disconnected the kernel.  Requires restarting VS code to get it back, restarting the kernel does nothing.  It seems that once Windows kills it, there is no way to bring it back without restarting VS code, which is unfortunate.
OS: Windows 10  Build 19042.804
Python 3.8.0
Local server, local VS Code
Jupyter Extension: v2021.3.619093157

Hey,
just wanted to let you know: fitting a model onto a large-ish data set produced the same error for me (LocalOS: MacOS, remote OS (using SSH extension): Ubuntu).
Turns out my remote machine runs out of memory and is purged by the cloud provider.
Does not explain the problems with local instances, but might be the error source for some.

@MJimitater

This problem occurs in Jupyter classic as well as in insiders

Can you confirm this issue occurs in Jupyter Classic, as in the Jupyter notebooks (outside VS Code).
@moritzwilksch

Turns out my remote machine runs out of memory and is purged by the cloud provider.

Does this issue exist when not using VS Code & you use Jupyter Notebooks in the browser (outside VS Code)

Hi there! Just chiming in on what I hope is a relevant thread. I am loading a very large matrix with GEOparse (version 2.0.3) and when I try to pivot the values in my matrix I get the "Error: direct kernel connection broken" message. Maybe python is throwing a memory error and this is somehow severing the connection? Insights into this much appreciated.

I found that this happens because I had a infinitely recursive function in my code and Jupyter didn't detect it. Try running your code in a normal python script to see if that's the case.

Maybe python is throwing a memory error and this is somehow severing the connection? Insights into this much appreciated.

Would it be possible for someone to share all the necessary files so we can replicate this at our end.
Seems like a few users are running into this and I'd like to ensure we get this fixed.
Please email large matrix or *.mat files to @.com
Or please feel free to upload files to github issue, thanks & I'm sorry for the inconvenience caused.

@DonJayamanne, the following code triggers for me:
from sklearn.datasets import fetch_openml
import numpy as np
from sklearn.decomposition import KernelPCA

mnist = fetch_openml('mnist_784', version=1)
X, y = mnist["data"], mnist["target"]

rbf_pca = KernelPCA(n_components= 2, kernel="rbf", gamma=0.04)

rbf_pca.fit(X)

X_reduced = rbf_pca.transform(X)
# run the following line in the next cell to reproduce error
X_reduced.shape

Brilliant, thanks. Though it still fails in Jupyter.
Moving back to triage to discuss this further.

As a first step, let's add this to our wiki that describes common problems users can run into.

FYI I noticed that I run into this problem, if I've got notebook_1 running a kernel with GPU usage, and then I start notebook_2 with a different kernel but also with GPU usage.

@MJimitater
Does the issue repro in classic  Jupyter?

@DonJayamanne yes, I can reproduce in classic Jupyter in the browser. The error message changes to "Kernel Restarting
The kernel appears to have died. It will restart automatically."

@DonJayamanne Thanks for taking a look!!

Here is my ipynb notebook and my debug file (zip)
Note that the error occurs after executing cell 12; if I comment that cell out however, it works.
This problem occurs in Jupyter classic as well as in insiders

I noticed how the kernel always throws this broken kernel connection error, when trying to enumerate through a Tensorflow Dataset holding close to 1 Million (1x1000) arrays. However, if I go down in size, then it works! Perhaps the error is linked to huge tf datasets?!
EDIT: From the last line of the debug output, I think my error is linked to this tensorflow issue.
EDIT 2: So I found out that my kernel always breaks if I run out of memory (see link to other tensorflow issue above). This was caused due to a massive tf dataset, that I enumerated through (in cell 12). Once this dataset held more than a certain amount of samples (in my case 2 million), then my kernel always broke. But once I reduced the size, it worked. Did anyone observe a similar reason?

I always kept running into this issue after training for many epochs in VSCode (Classic and Insiders). E.g. the issue always occured after epoch 112, 114, 144 (or something similar) when training for 200 epochs. BUT: running the code in Jupyter Notebook Classic didn't throw the error during training.

Thanks, will try this at our end.

Moving back to Triage, we should probably restart the kernels automatically like Jupyter.
(probably needs to be done only if we've successfully executed a user cell, else we could end up going in a loop re-starting kernels that fail to start)

I encountered this same error. For me I believe it was caused by an out-of-memory error. Whenever I reproduce it and monitor system memory, RAM runs out right before the error.
As such I don't think the failure itself is a VS Code bug per se, at least in my use case. But it might be nice quality of life feature if VS Code could detect the OOM error and give a more informative error message.
To those who avoid this bug by running the same code outside VS Code... do you think it might be because VS Code takes up more RAM, leaving less available for your program?
FWIW I am running interactive python REPL in container.

I had this issue and restarting didn't help. I tapped the kernel button in the top-right and noticed that it was using the system Python. I switch to my virtualenv Python and now it works as expected.

Just wondering any solution to this yet?
I've been having the same issue while trying to load a massive image dataset with landmarks(lazylist) into a numpy array.
Also i noticed something interesting.
I tried splitting my dataset and saving half into a numpy array in one cell and then doing the same for the other half in a different cell into a different numpy array, so as to see if the kernel stops even when i'm not loading all of it into one array.
The total images are 2000 in number.
When i was loading into one array it was stopping at around the 1300 mark.
when i split the dataset, the first executed and loaded 1050 images completely into an array, but then the second cell stopped at around 170 and the kernel connection broke and didn't fill the second array fully.
Any help would be appreciated

@pranshuub thanks for reaching out, and I'm sorry you're running into this issue.
Please could you test this in Jupyter as well, most  have confirmed that this problem persists in Jupyter as well (though the memory restrictions are slightly different).
Basically at this stage is a problem in classic Jupyter as well, and we're looking at providing better error messages.

I encountered an issue shows this error while using matplotlib.pyplot.imshow for numpy.ndarray.
In this case, the problem was caused by "Initializing libiomp5md.dll, but found libiomp5md.dll already initialized." and
I temporary solved it by adding
 import os
 os.environ['KMP_DUPLICATE_LIB_OK']='True'

Same issue

I was facing this issue, but was not loading a large dataset. Following #778, I had an "exit()" call which was causing the crash. Removing it fixed the issue.

Should be fixed now. Anybody else still hitting this problem, please comment/reopen.


help with config sonoff pow in home assistant

Hello,
I installed home assistant 0.98.4 on raspberrypi 2. I configured the mqtt service in the raspberry pi and then I configured the configuration.yaml file.
It's the config of the mqtt:
mqtt:

broker: <IP_ADDRESS>

username: or94

password:

discovery: true

discovery_prefix: homeassistant

I configured shelly switch and yeelight in the same file and everthing works great. Yesterday I flashed tasmota for the sonoff pow R2 switch. I configured the mqtt service in the web interface:

I enabled the mqtt in the configure other option in the sonoff web inteface and I wrote friendly name.
Then I tried to config the sonoff in the configuration.yaml:

switch:

platform: mqtt

name: "Boiler"
state_topic: "stat/sonoff/power"
command_topic: "cmnd/sonoff/POWER"
qos: 1
payload_on: "ON"
payload_off: "OFF"
retain: true

I restarted the Home assistant server but nothing happened and I don't have a switch. I saw in the console in the web interface of the sonoff switch and it connected to the wifi and to the mqtt server.
What I am doing wrong?
Thanks

Have you tried this command in the tasmota console for this device?:
setoption19 1

Thank you for reaching out.  We use GitHub for tracking issues, not for providing support.
If you are in need of support, you should try our Community Forum or join our Discord chat server.
You are more likely to get the answer you are looking for in those places.
Thanks! 👍


Update hot-module-replacement.md

the command not is:
npm run hmr
not
npm run hot
as per the package.json

?

In a default laravel install, "hot" is the script that is defined. It works perfectly. Very confused by this pr.

hot is the recommended name. Thanks, though. :)


Buffer: migrate new Buffer() to Buffer.alloc, Buffer.from, etc.

$ node -v
v10.13.0
...
$ t2 run index.js
INFO Looking for your Tessel...
(node:27867) [DEP0005] DeprecationWarning: Buffer() is deprecated due to security and usability issues. Please use the Buffer.alloc(), Buffer.allocUnsafe(), or Buffer.from() methods instead.

After migrating these warnings disappear.

Coverage decreased (-0.03%) to 85.94% when pulling 332f5d191539b5345e5b82887e648abdb6f512b9 on buffer-migrate into d8b040a000d45fd7c054a9a288f0bf5f0fe84b13 on master.


HPC Tools for Julia: Inspecting, Monitoring, and Tuning Performance | Carsten Bauer | JuliaCon 2023

Hi, here is another contribution, tell me if I should modify something :)
References:
Speaker: Carsten Bauer
Video title: HPC Tools for Julia: Inspecting, Monitoring, and Tuning Performance | Carsten Bauer | JuliaCon 2023
Link: https://www.youtube.com/watch?v=ksh-CNM2YJU&t=7s
Contents
0:00 Welcome
0:06 Introduction
0:32 HPC tools and Julia
2:10 LIKWID - hardware performances monitoring
3:57 LIKWID - alternatives: LinuxPerf.jl and PAPI.jl
4:22 ThreadPinning - pin Julia threads
6:20 ScoreP - MPI profiling and tracing
8:44 ScoreP - alternative: NVTX.jl
9:11 ScoreP - open trace formats
10:37 MPITape - MPI call visualization
12:10 Outlook and conclusion
12:42 Questions
Edit: fixed the link

I made few minor changes to your work.
Contents
00:00 Opening and introduction
00:32 HPC tools and Julia
02:10 LIKWID - hardware performances monitoring
03:57 LIKWID - alternatives: LinuxPerf.jl and PAPI.jl
04:22 ThreadPinning - pin Julia threads
06:20 ScoreP - MPI profiling and tracing
08:44 ScoreP - alternative: NVTX.jl
09:11 ScoreP - open trace formats
10:37 MPITape - MPI call visualization
12:10 Outlook and conclusion
12:42 Questions

Everything seems to be ok, so we are closing the issue.


Remove empty path segments when joining paths

[ ] The purpose of this PR is explained in this or a referenced issue.
[ ] The PR does not update generated files.

These files are managed by the codegen framework at Azure/autorest.go.

[ ] Tests are included and/or updated for code changes.
[ ] Updates to CHANGELOG.md are included.
[ ] MIT license headers are included in each file.

I noticed this while working with Key Vault clients but let it lie because empty path segments are legal. Does this change fix a particular scenario?

/azp run go - azkeys

No particular scenario is broken, it's just something that's bugged me for a while and might end up being exposed to customers when faking (depending on what direction we go).
I didn't realize that empty path segments are legal.  Is there a reference for that in the RFC?  If so, then leaving them is actually advantageous for faking.

Ah found it.  This is great and fixes part of problem with fakes.
https://stackoverflow.com/questions/20569958/url-format-empty-path
https://www.rfc-editor.org/rfc/rfc3986#section-3.3


Update readme, remove static assets

https://github.com/ttytm/go-webui/tree/docs/update-readme

Thank you for the new look. I understand that you suppose that users already know the main WebUI repo. But I think many users test/read only the wrapper repo and they never seen the main WebUI repo. So, probably we should keep the sections:

Documentation
CppCon 2019 Presentation
UI & The Web Technologies
Why Use Web Browser?
How does it work?
Runtime Dependencies Comparison
Stargazers

The added commit adds the section to have a merge of the main repository with the current readme and a new look. Let me know if further changes are preferred 👍

LGTM


New Scope: Logged in

Consider adding a new metadata scope level.
This level is data that should only be visible by users that are logged in. Thus, it means it's important for any cached nodes to be discarded after logging in.
The data is still considered public, but it's omitted when serving data to bots and spiders.
Uses: Promo codes. It makes sense for this data to be attached to users, but in some rare cases a single code is shared across several users. It's sensible for these to be attached to the promo's node itself, and not the users.

Partially implemented this in my build. It doesn't actually do anything, but there is now a Scope value (2) for it.
That said, unless the server-side node caching gets reimplemented in such a way that protected data is cached and filtered out before sending to the client (plus the client actually disposes of its data immediately after logging in or out), this is going to be a somewhat buggy feature.
Note to self: Consider abandoning this. For now, I'm going to move this to a later milestone.


Compiler warning on Ubuntu 20.04

On Ubuntu 20.04, building 8.2.1931, I get the following warning that I wasn't getting several patchlevels ago IIRC:
gcc -c -I. -Iproto -DHAVE_CONFIG_H -DFEAT_GUI_ATHENA     -g -O2 -U_FORTIFY_SOURCE -D_FORTIFY_SOURCE=1     -I/usr/include/x86_64-linux-gnu    -o objects/gui_at_fs.o gui_at_fs.c
In file included from /usr/include/string.h:495,
                 from os_unix.h:473,
                 from vim.h:228,
                 from gui_at_fs.c:44:
In function ‘strncat’,
    inlined from ‘SFreplaceText.isra.0’ at gui_at_fs.c:288:9:
/usr/include/x86_64-linux-gnu/bits/string_fortified.h:136:10: warning: ‘__builtin___strncat_chk’ specified bound depends on the length of the source argument [-Wstringop-overflow=]
  136 |   return __builtin___strncat_chk (__dest, __src, __len, __bos (__dest));
      |          ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
gui_at_fs.c: In function ‘SFreplaceText.isra.0’:
gui_at_fs.c:284:11: note: length computed here
  284 |     len = strlen(str);
      |           ^~~~~~~~~~~

On Ubuntu 20.04, building 8.2.1931, I get the following warning that I wasn't getting several patchlevels ago IIRC:
gcc -c -I. -Iproto -DHAVE_CONFIG_H -DFEAT_GUI_ATHENA     -g -O2 -U_FORTIFY_SOURCE -D_FORTIFY_SOURCE=1     -I/usr/include/x86_64-linux-gnu    -o objects/gui_at_fs.o gui_at_fs.c
In file included from /usr/include/string.h:495,
                 from os_unix.h:473,
                 from vim.h:228,
                 from gui_at_fs.c:44:
In function ‘strncat’,
    inlined from ‘SFreplaceText.isra.0’ at gui_at_fs.c:288:9:
/usr/include/x86_64-linux-gnu/bits/string_fortified.h:136:10: warning: ‘__builtin___strncat_chk’ specified bound depends on the length of the source argument [-Wstringop-overflow=]
  136 |   return __builtin___strncat_chk (__dest, __src, __len, __bos (__dest));
      |          ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
gui_at_fs.c: In function ‘SFreplaceText.isra.0’:
gui_at_fs.c:284:11: note: length computed here
  284 |     len = strlen(str);
      |           ^~~~~~~~~~~

I do see a few compiler warnings when building with Athena, but not this
one.  Perhaps your compiler has different defaults?
I'll make a patch for the errors that I can see.
--
Very funny, Scotty.  Now beam down my clothes.
/// Bram Moolenaar --<EMAIL_ADDRESS>-- http://www.Moolenaar.net   \
///        sponsor Vim, vote for features -- http://www.Vim.org/sponsor/ \
\\  an exciting new programming language -- http://www.Zimbu.org        ///
\\            help me help AIDS victims -- http://ICCF-Holland.org    ///

Thanks, but the exact same warning is still appearing.
I don't know what kind of defaults the compiler has.  I'm just using whatever came with Ubuntu 20.04.

This eventually went away at some point.


get src/data/problem/valid/Database-img_mg_annotation_objects.yaml to be clearly valid or clearly invalid, or delete it

Hi @mbthornton-lbl and @pkalita-lbl
I could use some of your help with an example file that was passing in the nmdc-schema for the past 6 months but is failing with an ambiguous message in the berkeley-schema-fy24
I have been working on the nmdc:type slot in berkeley-schema-fy24 and am going to merge my work. In my branch's current state, everything builds, the valid examples pass, and the invalid files fail as expected.
This also succeeds:
poetry run linkml-validate \
  --schema src/schema/nmdc.yaml \
  --target-class Database src/data/problem/valid/Database-img_mg_annotation_objects.yaml

but if I
cp src/data/problem/valid/Database-img_mg_annotation_objects.yaml src/data/valid/Database-img_mg_annotation_objects.yaml
make squeaky-clean all test

I get a report like this for each

ValueError: Example src/data/valid/Database-img_mg_annotation_objects.yaml failed validation:
{'has_input': ['nmdc:b4b798cc9e7e9253ae8256a8237fd371'], 'git_url': 'https://img.jgi.doe.gov', 'name': 'MetagenomeAnnotation activity for gold:Gp0153825', 'has_output': ['nmdc:a1f2c190aa6d470f2eea681126e0470e', 'nmdc:7d69d28f4abec72a7ad66411312c37fb', 'nmdc:c3ea4b3caf0c86e27118b3ffd51014b8', 'nmdc:a79973ef9a0c96d13fa19b2725b21d17', 'nmdc:1055b8fab0f63a1e56312813f47897ec'], 'started_at_time': '2021-01-12T00:00:00+00:00', 'execution_resource': 'NERSC-Cori', 'part_of': 'nmdc:wfch-11-ab', 'type': 'nmdc:MetagenomeAnnotation', 'id': 'nmdc:wf-99-v7tNhU', 'ended_at_time': '2021-01-12T00:00:00+00:00'} is not valid under any of the given schemas in $.workflow_execution_set[0]

@pkalita-lbl can you please help us think of situations in which a data file would pass linkml-validate but fail in linkml-run-examples. Are they using two different genration of the validation code?

can you please help us think of situations in which a data file would pass linkml-validate but fail in linkml-run-examples

Starting with 1.6.6 both of those CLIs use the same code under the hood. linkml-validate offers a lot more flexibility in terms of choosing loading and validating strategies, but by default both it and linkml-run-examples use the same strategy.
When I do a fresh checkout of the berkeley-schema-fy24 repo, run poetry install, and then run the linkml-validate command above it does not succeed. It says essentially the same thing as what you reported for linkml-run-examples:
[ERROR] [src/data/problem/valid/Database-img_mg_annotation_objects.yaml/0] Additional properties are not allowed ('type' was unexpected) in /
[ERROR] [src/data/problem/valid/Database-img_mg_annotation_objects.yaml/0] {'has_input': ['nmdc:b4b798cc9e7e9253ae8256a8237fd371'], 'git_url': 'https://img.jgi.doe.gov', 'name': 'MetagenomeAnnotation activity for gold:Gp0153825', 'has_output': ['nmdc:a1f2c190aa6d470f2eea681126e0470e', 'nmdc:7d69d28f4abec72a7ad66411312c37fb', 'nmdc:c3ea4b3caf0c86e27118b3ffd51014b8', 'nmdc:a79973ef9a0c96d13fa19b2725b21d17', 'nmdc:1055b8fab0f63a1e56312813f47897ec'], 'started_at_time': '2021-01-12T00:00:00+00:00', 'execution_resource': 'NERSC-Cori', 'part_of': ['nmdc:wfch-11-ab'], 'type': 'nmdc:MetagenomeAnnotation', 'id': 'nmdc:wf-99-v7tNhU', 'ended_at_time': '2021-01-12T00:00:00+00:00'} is not valid under any of the given schemas in /workflow_execution_set/0

Admittedly the failure message here isn't great but it is saying "This object, starting with the has_input key, is not valid under any of the given schemas in /workflow_execution_set/0". Okay, so what is it expecting in /workflow_execution_set/0? Look at the JSON Schema and it has:
        "workflow_execution_set": {
            "description": "This property links a database object to the set of workflow activities.",
            "items": {
                "anyOf": [
                    {
                        "$ref": "#/$defs/WorkflowExecution"
                    },
                    {
                        "$ref": "#/$defs/MetagenomeAssembly"
                    },
                    {
                        "$ref": "#/$defs/MetatranscriptomeAssembly"
                    },
                    {
                        "$ref": "#/$defs/MetagenomeAnnotation"
                    },
                    {
                        "$ref": "#/$defs/MetatranscriptomeAnnotation"
                    },
                    {
                        "$ref": "#/$defs/MetatranscriptomeAnalysis"
                    },
                    {
                        "$ref": "#/$defs/MagsAnalysis"
                    },
                    {
                        "$ref": "#/$defs/MetagenomeSequencing"
                    },
                    {
                        "$ref": "#/$defs/ReadQcAnalysis"
                    },
                    {
                        "$ref": "#/$defs/ReadBasedTaxonomyAnalysis"
                    },
                    {
                        "$ref": "#/$defs/MetabolomicsAnalysis"
                    },
                    {
                        "$ref": "#/$defs/MetaproteomicsAnalysis"
                    },
                    {
                        "$ref": "#/$defs/NomAnalysis"
                    }
                ]
            },
            "type": "array"
        }

Okay so it's supposed to be an array of objects and each one needs to match one of any number of different $ref subschemas. Since the data has type: nmdc:MetagenomeAnnotation and that's one of the allowed subschemas let's look there first:
        "MetagenomeAnnotation": {
            "additionalProperties": false,
            "description": "A workflow execution activity that provides functional and structural annotation of assembled metagenome contigs",
            "properties": {
                "alternative_identifiers": {
                    "description": "A list of alternative identifiers for the entity.",
                    "items": {
                        "pattern": "^[a-zA-Z0-9][a-zA-Z0-9_\\.]+:[a-zA-Z0-9_][a-zA-Z0-9_\\-\\/\\.,]*$",
                        "type": "string"
                    },
                    "type": "array"
                },
                "description": {
                    "description": "a human-readable description of a thing",
                    "type": "string"
                },
                "end_date": {
                    "description": "The date on which any process or activity was ended",
                    "type": "string"
                },
                "ended_at_time": {
                    "pattern": "^([\\+-]?\\d{4}(?!\\d{2}\\b))((-?)((0[1-9]|1[0-2])(\\3([12]\\d|0[1-9]|3[01]))?|W([0-4]\\d|5[0-2])(-?[1-7])?|(00[1-9]|0[1-9]\\d|[12]\\d{2}|3([0-5]\\d|6[1-6])))([T\\s]((([01]\\d|2[0-3])((:?)[0-5]\\d)?|24\\:?00)([\\.,]\\d+(?!:))?)?(\\17[0-5]\\d([\\.,]\\d+)?)?([zZ]|([\\+-])([01]\\d|2[0-3]):?([0-5]\\d)?)?)?)?$",
                    "type": "string"
                },
                "execution_resource": {
                    "$ref": "#/$defs/ExecutionResourceEnum"
                },
                "git_url": {
                    "type": "string"
                },
                "gold_analysis_project_identifiers": {
                    "description": "identifiers for corresponding analysis project in GOLD",
                    "items": {
                        "pattern": "^gold:Ga[0-9]+$",
                        "type": "string"
                    },
                    "type": "array"
                },
                "has_input": {
                    "description": "An input to a process.",
                    "items": {
                        "type": "string"
                    },
                    "type": "array"
                },
                "has_output": {
                    "description": "An output from a process.",
                    "items": {
                        "type": "string"
                    },
                    "type": "array"
                },
                "id": {
                    "description": "A unique identifier for a thing. Must be either a CURIE shorthand for a URI or a complete URI",
                    "pattern": "^[a-zA-Z0-9][a-zA-Z0-9_\\.]+:[a-zA-Z0-9_][a-zA-Z0-9_\\-\\/\\.,]*$",
                    "type": "string"
                },
                "instrument_used": {
                    "description": "What instrument was used during DataGeneration or MaterialProcessing.",
                    "items": {
                        "type": "string"
                    },
                    "type": "array"
                },
                "name": {
                    "description": "A human readable label for an entity",
                    "type": "string"
                },
                "part_of": {
                    "description": "The WorkflowChain that this WorkflowExecution is part of",
                    "type": "string"
                },
                "processing_institution": {
                    "$ref": "#/$defs/ProcessingInstitutionEnum",
                    "description": "The organization that processed the sample."
                },
                "protocol_link": {
                    "$ref": "#/$defs/Protocol"
                },
                "start_date": {
                    "description": "The date on which any process or activity was started",
                    "type": "string"
                },
                "started_at_time": {
                    "pattern": "^([\\+-]?\\d{4}(?!\\d{2}\\b))((-?)((0[1-9]|1[0-2])(\\3([12]\\d|0[1-9]|3[01]))?|W([0-4]\\d|5[0-2])(-?[1-7])?|(00[1-9]|0[1-9]\\d|[12]\\d{2}|3([0-5]\\d|6[1-6])))([T\\s]((([01]\\d|2[0-3])((:?)[0-5]\\d)?|24\\:?00)([\\.,]\\d+(?!:))?)?(\\17[0-5]\\d([\\.,]\\d+)?)?([zZ]|([\\+-])([01]\\d|2[0-3]):?([0-5]\\d)?)?)?)?$",
                    "type": "string"
                },
                "type": {
                    "description": "the id of the class that is instantiated by some data",
                    "enum": [
                        "nmdc:MetagenomeAnnotation"
                    ],
                    "type": "string"
                },
                "version": {
                    "type": "string"
                }
            },
            "required": [
                "ended_at_time",
                "execution_resource",
                "git_url",
                "part_of",
                "started_at_time",
                "has_input",
                "has_output",
                "id",
                "type"
            ],
            "title": "MetagenomeAnnotation",
            "type": "object"
        },

Is the data valid under that subschema? Nope, that says part_of is a string but we gave it an array.
You can also copy the entire JSON Schema (gen-json-schema src/schema/nmdc.yaml | pbcopy) into https://www.jsonschemavalidator.net/ along with a JSON-ified version of you data instance. It gives much more verbose information for these types of nested subschema failures.


Update names of events to be a little less specific

These names probably better reflect what we care about. We care if the report was in the DOM already (and it is quick to switch to) or it was not in the DOM (and slow to switch to)
Fixed Issues
From this slack thread
Tests

Log into the chat app
Switch between chats that are either pinned or unpinned
Verify the events are logged to the API

Tested this locally and it does work:
Uploading Screen Recording 2020-12-18 at 5.30.06 PM.mov…


Replace bit field manipulation functions with macros

JerryScript-DCO-1.0-Signed-off-by: Akos Kiss<EMAIL_ADDRESS>

I have related work in https://github.com/LaszloLango/jerryscript/commit/1223b994c7970c2a237f9907f4b0a0786bc18d4f
There is much optimization possibility in ecma_make_*_value functions too.

This patch achieves quite good code size reduction on arm targets (2-8K on release builds).

filename
master/text
master/data
pr/text
pr/data
gain/text
gain/data

release.linux-armv7lhf/jerry
195943
52
187192
52
8751
0

release.linux-armv7lhf-cp/jerry
142148
52
136555
52
5593
0

release.linux-armv7lhf-cp_minimal/jerry
87957
0
85396
0
2561
0

release.linux-armv7lhf-mem_stats/jerry
196539
52
188297
52
8242
0

release.linux-armv7lhf-mem_stress_test/jerry
195575
52
187588
52
7987
0

release.linux-x86_64/jerry
278590
61
277340
52
1250
9

release.linux-x86_64-cp/jerry
210702
61
210010
52
692
9

release.linux-x86_64-cp_minimal/jerry
132993
0
132442
0
551
0

release.linux-x86_64-mem_stats/jerry
280071
61
278549
52
1522
9

release.linux-x86_64-mem_stress_test/jerry
279031
61
277469
52
1562
9

release.mcu_stm32f3-cp.bin/jerry
142748
72
140232
72
2516
0

release.mcu_stm32f3-cp_minimal.bin/jerry
82436
20
80912
20
1524
0

release.mcu_stm32f4-cp.bin/jerry
142748
72
140232
72
2516
0

release.mcu_stm32f4-cp_minimal.bin/jerry
82436
20
80912
20
1524
0

debug.linux-armv7lhf/jerry
734016
60
733252
60
764
0

debug.linux-armv7lhf-cp/jerry
537776
60
537020
60
756
0

debug.linux-armv7lhf-cp_minimal/jerry
368272
24
366996
24
1276
0

debug.linux-armv7lhf-mem_stats/jerry
737516
60
736660
60
856
0

debug.linux-armv7lhf-mem_stress_test/jerry
734064
60
733300
60
764
0

debug.linux-x86_64/jerry
817371
68
816185
68
1186
0

debug.linux-x86_64-cp/jerry
635223
68
633962
68
1261
0

debug.linux-x86_64-cp_minimal/jerry
443502
32
442300
32
1202
0

debug.linux-x86_64-mem_stats/jerry
821176
68
820710
68
466
0

debug.linux-x86_64-mem_stress_test/jerry
817391
68
816205
68
1186
0

debug.mcu_stm32f4-cp.bin/jerry
547212
76
546324
76
888
0

debug.mcu_stm32f4-cp_minimal.bin/jerry
367396
44
366500
44
896
0

Performance on x86_64/linux also improved slightly, especially on the longer running test cases (crypto-md5.js and crypto-sha1.js).
                  Benchmark |                   Perf(+ is better)
                 3d-cube.js |   0.259s ->   0.262s :  -1.093%  (+-1.765%) : [≈]
     access-binary-trees.js |   0.137s ->   0.132s :  +3.519%  (+-1.882%) : [+]
         access-fannkuch.js |   0.719s ->   0.717s :  +0.255%  (+-1.278%) : [≈]
            access-nbody.js |   0.316s ->   0.307s :  +2.847%  (+-0.907%) : [+]
bitops-3bit-bits-in-byte.js |   0.205s ->   0.203s :  +0.893%  (+-2.276%) : [≈]
     bitops-bits-in-byte.js |   0.262s ->   0.269s :  -2.610%  (+-2.358%) : [-]
      bitops-bitwise-and.js |   0.308s ->   0.296s :  +3.794%  (+-1.580%) : [+]
   controlflow-recursive.js |   0.090s ->   0.090s :  -0.557%  (+-7.179%) : [≈]
              crypto-aes.js |   0.508s ->   0.494s :  +2.854%  (+-1.115%) : [+]
              crypto-md5.js |   3.048s ->   2.736s : +10.226%  (+-0.374%) : [+]
             crypto-sha1.js |   1.351s ->   1.213s : +10.178%  (+-0.343%) : [+]
       date-format-tofte.js |   0.214s ->   0.208s :  +2.802%  (+-1.420%) : [+]
       date-format-xparb.js |   0.100s ->   0.097s :  +2.663%  (+-4.337%) : [≈]
             math-cordic.js |   0.293s ->   0.293s :  -0.057%  (+-2.025%) : [≈]
       math-partial-sums.js |   0.160s ->   0.159s :  +1.143%  (+-3.549%) : [≈]
      math-spectral-norm.js |   0.148s ->   0.148s :  +0.337%  (+-2.330%) : [≈]
            string-fasta.js |   0.449s ->   0.430s :  +4.306%  (+-1.561%) : [+]
            Geometric mean: |                 Speed up: 2.501% (+-0.650%) : [+]

Rebased and pushed. (Also: found a solution to get rid of not-so-nice type casts that were present in previous versions of this patch.)

@zherczeg I've updated the patch as suggested. Does it look better?

LGTM

In general functions are easier to debug but I have no strong opinion, because I also use a lot of macros. I did not find the RPi2 results, am I missing something?

RPi2 results
master (https://github.com/Samsung/jerryscript/commit/76b37f34d0df7fadbecf57ac52345c6b50631b54)
                  Benchmark |                  Perf(+ is better)
                 3d-cube.js |  2.627s ->   2.543s :  +3.173%  (+-3.506%) : [≈]
     access-binary-trees.js |  1.407s ->   1.370s :  +2.607%  (+-2.291%) : [+]
         access-fannkuch.js |  7.960s ->   7.967s :  -0.084%  (+-2.530%) : [≈]
            access-nbody.js |  3.070s ->   3.077s :  -0.217%  (+-1.078%) : [≈]
bitops-3bit-bits-in-byte.js |  1.730s ->   1.723s :  +0.386%  (+-1.912%) : [≈]
     bitops-bits-in-byte.js |  2.653s ->   2.603s :  +1.884%  (+-3.494%) : [≈]
      bitops-bitwise-and.js |  3.680s ->   3.663s :  +0.453%  (+-3.587%) : [≈]
   controlflow-recursive.js |  0.890s ->   0.870s :  +2.247%  (+-0.000%) : [+]
              crypto-aes.js |  4.730s ->   4.643s :  +1.832%  (+-2.769%) : [≈]
              crypto-md5.js | 21.490s ->  21.847s :  -1.660%  (+-0.982%) : [-]
             crypto-sha1.js |  9.750s ->   9.817s :  -0.684%  (+-3.406%) : [≈]
       date-format-tofte.js |  2.233s ->   2.223s :  +0.448%  (+-2.090%) : [≈]
       date-format-xparb.js |  1.087s ->   1.053s :  +3.068%  (+-4.240%) : [≈]
             math-cordic.js |  2.977s ->   2.943s :  +1.120%  (+-2.463%) : [≈]
       math-partial-sums.js |  1.660s ->   1.670s :  -0.602%  (+-0.000%) : [-]
      math-spectral-norm.js |  1.503s ->   1.457s :  +3.104%  (+-3.064%) : [+]
            string-fasta.js |  4.537s ->   4.467s :  +1.543%  (+-3.251%) : [≈]
            Geometric mean: |                Speed up: 1.106% (+-0.661%) : [+]

Binary sizes (bytes): 197,240 -> 193,144

LGTM


Use vaadin progress bar in dev-ui embedding store

Resolves: #554

Nice! Could you please, while we're at this, move the ${this._addEmbeddingConfirmation} element under the Create and store button?  For searching, the progress bar shows under the search form+button, but for adding, its progress bar shows above the form, which looks weird.


integration, vendor: remove e2esetup dependency from code (#63)

Towards https://github.com/giantswarm/giantswarm/issues/4709.
We were using e2esetup to create/delete tiller namespace in tests. We
don't want the dependency in the code though because e2esetup depends on
helmclient. This creates potential circular dependency problem and makes
vendoring hard.

Why are we doing this? I understand this for the single constant in e2e-harness but this here goes a bit too far IMO. Why don't we have a common lib? Let's please not copy so much and try to "fix" it with a comment.

Why are we doing this?

Circular dependencies. I explained that in the description.

Why don't we have a common lib?

Maybe at some point that would be a good idea to have it. I'm not sure how should it look like ATM and what would be its scope. Things are changing in e2e and I don't want to constrain myself. This change debatable I agree. I'll try to do the upgrades with overrides.

If you like we can just hang and come up with some proper dependency graph. Or just create a common lib for that.

Cool. Just give me a shout.

I chatted with @xh3b4sd. We agreed it's better to just use [[override]] for k8s.io libs in helmclient. We are not sure what is the future of our testing libraries. We should figure that out first before extracting some random stuff (which may require e2e tests itself) to a separate repo.


Feature: make cli password input hidden

Currently password input for creating a new account is rendered visibly. Would it be possible to hide the input to prevent over-the-shoulder attacks?
emerald-cli/target/release travis-deploy ⟠ ./emerald new --chain testnet
! Warning: passphrase can't be restored. Don't forget it !
Enter passphrase:
foo
Created new account: 0xb0d31ea6af9390c2727023eb8ec750f0cb7268f7

&
emerald new --chain testnet --security-level high "Test account" < echo "secret passphrase"

Maybe also worth considering using a 2x-input prompt for password confirmation? eg.
Enter your new passphrase:
***
Confirm your new passphrase:
****
> Yikes! Those passphrases don't match. New account creation aborted.

Moved ot #25


"Go to File..." to give extra weight to files in the same directory as the current editor; or add a token to narrow results to current directory

I've been running into an issue when using "Go to File..." (Ctrl+E) in very large workspaces. It seems to sort results based on how many folders deep they are, and then by alphabetical order. But in the project I work on, there are thousands of folders, each with its own test folders, which have a characteristic structure. They'll include a head.js file, which functions sort of like beforeEach in jest. So variables defined in head.js will be available in tests in the same directory.
When I'm working on one of those tests, sometimes I want to open the corresponding head.js file so its definitions will be picked up by Intellisense (no jsconfig). My first instinct would be to hit Ctrl+E and type head.js but that doesn't work since it gives no weight to the current editor. Instead I have to use the breadcrumbs, but there isn't a quick keyboard shortcut to open the previous breadcrumb. Could use the Editor, but typing a filename in there doesn't show any feedback and it doesn't restrict the 'search' to the current folder anyway.
I imagine it'd probably be a lot easier to just add a new token for the "Go to File..." menu. In the same way typing @ will restrict the search to symbols in the current editor, typing ./ could restrict the search to files in the same folder as the file open in the current editor. But it would also be nice if files were weighted in a more practical way in general, so that they are sorted by distance from the current editor's folder, rather than sorted by distance from the workspace root.
Thanks!

/duplicate https://github.com/microsoft/vscode/issues/133438

Thanks for creating this issue! We figured it's covering the same as another one we already have. Thus, we closed this one as a duplicate. You can search for similar existing issues. See also our issue reporting guidelines.
Happy Coding!


problems with deploying a py-shiny app to shinyapps.io

Hello,
I'm having some issues in deploying a Shiny for Python app (which works ok locally) to shinyapps.io, which I'll list here:

I think it may relate to installation of dependencies. I hadn't created a requirements.txt file, as this wasn't specified in the documentation (request 1 is to improve the documentation for deployment to shinyapps.io for py-shiny apps)
Even though deployemment failed, I think that it created an application in my account, because when I tried to deploy the app again the new error was that I had hit my limit of apps for my account (this new app did not show in the shinyapps.io applications list, but I could terminate it with rsconnect::terminateApp() in R).
I did manage to deploy an app after fixing the above, but then the app failed because I had a "pip install" command in my app, and this command was not permitted
I have a git clone then a pip install command in my app, because I'm installing from a repository (not a package available in pypi)
So I wonder how to do this: shall I have virtualenv in requirements.txt, then activate it from the app, and run the git clone, pip install commands
However, I can't test the question above because I'm currently getting a deployment error as follows:

Deploying bundle ... 	[ERROR]: shinyapps.io reported an error (calling /v1/applications/13222535): Not Found
Error: shinyapps.io reported an error (calling /v1/applications/13222535): Not Found

Please could someone help? I can't see any running/sleeping apps on shinyapps.io which I can terminate.
thanks in advance!

Update: can ignore most of the above as i've found workarounds / solutions.
Except for the request for improved documentation please @ https://docs.posit.co/shinyapps.io/guide/getting_started/#working-with-shiny-for-python to include instructions on requirements.txt (starting with the fact that such a file is recommended)
Thanks for the great resource!


Update validator.js

add name key index support and add required error both for radios

PR how to: https://github.com/olton/Metro-UI-CSS/blob/master/CONTRIBUTING.md#pull-request-guidelines
The current develop branch is 4.4.0. About contributing begin from 4.4.0 https://github.com/olton/Metro-UI-CSS/blob/4.4.0/CONTRIBUTING.md


Recreate QTL_pipeline_vignette

Recreate this vignette with an openly accessible example file, hosted here.

Added remotely hosted colocalization dataset example on the echolocatoR Fine-mapping Portal. So users can just download this directly.


Incomplete JSON example

The C# code creating the SQL container contains the following line that specifies the partition key path:
myCollection.PartitionKey.Paths.Add("/pk");
However the JSON example does not contain this path.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: bf261de8-a6fa-9497-ffff-106550e2a537
Version Independent ID: ee0468ba-1b3b-6ba4-d9f6-c60da3e7c486
Content: Unique keys in Azure Cosmos DB
Content Source: articles/cosmos-db/unique-keys.md
Service: cosmos-db
GitHub Login: @rafats
Microsoft Alias: rafats

@dlyall-maine Thanks for the feedback! We are currently investigating and will update you shortly.

JSON Sample:
{
"id": "1",
"firstName": "Gaby",
"lastName": "Duperre",
"email"<EMAIL_ADDRESS>"address": [
{
"line1": "100 Some Street",
"line2": "Unit 1",
"city": "Seattle",
"state": "WA",
"zipCode": 98012
}
],
}

Fixing in https://github.com/MicrosoftDocs/azure-docs-pr/pull/38336

The pk value has been added to the JSON sample in https://docs.microsoft.com/en-us/azure/cosmos-db/unique-keys#sql-api-sample. I think this addresses the issue. Thanks! #please-close

@dlyall-maine We will now proceed to close this thread. If there are further questions regarding this matter, please reopen it and we will gladly continue the discussion.


Weighting a tree by a tree of dataarrays isn't possible

ds.weighted(da).mean() can't be easily generalised to involve two trees, because there is no tree version of a dataarray. This is one reason why I haven't tried to write .weighted for datatree yet.
We should be able to generalise an operation involving multiple datasets such as ds.weighted(ds).mean(), i.e. dt.weighted(dt).mean() (as it's equivalent to dt + dt from map_over_subtree's perspective), but this particular weighted operation doesn't actually make sense.
We could also do dt.weighted(da).mean(), but I don't see how to make something like dt.weighted(dt).mean() work nicely.
The problem is that you can't weight by multiple variables, but at the moment you can't extract one variable from a node and retain the tree structure.
You could do this though, this is well-defined:
def weighted_mean_da(ds):
    return ds.data.weighted(ds.var).mean()

dt.map_over_subtree(weighted_mean_da)

cc @jbusecke

In the end I think it is actually desirable to nudge the user to store the weights as a variable/coordinate in the dataset! I think that will avoid errors when doing something like a weighted mean over many different nodes.

In the end I think it is actually desirable to nudge the user to store the weights as a variable/coordinate in the dataset! I think that will avoid errors when doing something like a weighted mean over many different nodes.

Why exactly? That is not ideal because that's not what xarray's Dataset.weighted currently expects, so the API would be inconsistent.

closing in favour of https://github.com/pydata/xarray/issues/9595 upstream


[Doom - Downgrade] Update cancel email copy + mailing existing

Related task and thread
Migration will be run right after merge:
LIVE=1 SENDGRID_API_KEY=ACTUALKEY npx tsx mailing/20231117-cancel-email.ts<EMAIL_ADDRESS><EMAIL_ADDRESS>
replacing with the list of emails extracted from stripe

FYI copy reviewed by gabriel by email + another change incoming in follow-up pr


MWPW-126640: consume standalone OST

This PR add ability to configure checkoutType and worfklowStep on OST CTA link.
It will also consume OST from web stage instead of copying js to Milo sources.
Resolves: MWPW-126640
Test URLs:
remember to set 'AOS_ACCESS_TOKEN'.

Before: OST
After: OST

ost styles should be loaded from the same domain offer-selector-tool.css OST looks broken to me.

@yesil i fixed it with @vhargrave  you can check again here
So I guess https://ost--milo--3ch023.hlx.page/libs/blocks/ost/ost.css got requested too early and franklin cached the 404 error.
we tried curl -X PURGE "{LIVE_URL}" but it didn't do any effect.
so i just committed a change on ost.css and it started loading properly.

@3ch023 this is a PR to ost branch. Can you sync up with @Axelcureno when you can get this merged into the main branch?

@3ch023 this is a PR to ost branch. Can you sync up with @Axelcureno when you can get this merged into the main branch?

yeah, it's just a temp PR to not lose our changes on ost.
waiting for an IMS to be ready before we can PR main branch.


Add wave and breathe mod.

Fixes https://github.com/wearefractal/msi-keyboard/issues/1
Original PR https://github.com/wearefractal/msi-keyboard/pull/20
Original work by @PaNaVTEC, first adaptation by @tobbebia, first PR adaptation by @ericmarsch
Just made this since @ericmarsch seems inactive.

Thanks!
Just a quick change, can you move the arguments for regions from three objects to one?
https://github.com/wearefractal/msi-keyboard/pull/31/files#diff-a6ae09d0821510ff1a6b06e0844a7ac9R3
To be one object:
{
  left: {},
  middle: {},
  right: {}
}

That removes the need to check for arguments length, and makes it easier to set just one region.

I just updated with examples. I believe this is working correctly.

I don't know why travis fails, but its working here, i don't see any js errors.

Yep, all actual attempts to send the feature report to the hardware will fail on travis. I'll probably remove (or fake) the tests resolving actually running the hardware.


Second API Response

WHEN I view future weather conditions for that city
THEN I am presented with a 5-day forecast that displays the date, an icon representation of weather conditions, the temperature, the wind speed, and the humidity

Forecast code is working fine, have to change metrics for wind speed.


[Bug]Fix unresolved references for Version field

Signed-off-by: Ashish Tiwari<EMAIL_ADDRESS>Description
This PR fixes #
Recently support for versioning Services was added. But in the Filler stage of pattern engine, version field was not being taken care of. This is causing those patternfiles to fail which do not have hardcoded version and take the version through references.
Notes for Reviewers
Signed commits

[ ] Yes, I signed my commits.

@leecalcote This is failing the E2E test in my recent PR adding versioning. After this fix, we will be completely ready for versioning and can go ahead with the PR in adapters.

Codecov Report

Merging #5926 (7b7f5e2) into master (b0c509c) will decrease coverage by 4.33%.
The diff coverage is 23.07%.

@@            Coverage Diff             @@
##           master    #5926      +/-   ##
==========================================
- Coverage   17.80%   13.47%   -4.34%
==========================================
  Files         107      107
  Lines        9994    10007      +13
==========================================
- Hits         1779     1348     -431
- Misses       7779     8368     +589
+ Partials      436      291     -145

Flag
Coverage Δ

gointegrationtests
?

unittests
13.47% <23.07%> (+0.01%)
:arrow_up:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

models/pattern/stages/filler.go
45.90% <23.07%> (-2.73%)
:arrow_down:

mesheryctl/internal/cli/root/system/update.go
1.05% <0.00%> (-58.95%)
:arrow_down:

mesheryctl/internal/cli/root/system/start.go
1.88% <0.00%> (-55.19%)
:arrow_down:

mesheryctl/internal/cli/root/system/status.go
1.14% <0.00%> (-55.18%)
:arrow_down:

mesheryctl/internal/cli/root/system/restart.go
1.92% <0.00%> (-48.08%)
:arrow_down:

mesheryctl/internal/cli/root/system/stop.go
2.00% <0.00%> (-46.67%)
:arrow_down:

mesheryctl/internal/cli/root/system/logs.go
3.26% <0.00%> (-36.96%)
:arrow_down:

mesheryctl/internal/cli/root/system/check.go
1.03% <0.00%> (-23.03%)
:arrow_down:

mesheryctl/internal/cli/root/system/dashboard.go
1.70% <0.00%> (-9.41%)
:arrow_down:

mesheryctl/pkg/utils/healthcheck.go
8.82% <0.00%> (-4.42%)
:arrow_down:

Continue to review full report at Codecov.

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@sudo-NithishKarthik is this related to your recent question?

@sudo-NithishKarthik is this related to your recent question?

No it is not. I have answered his recent question. This is a leftover thing from a previous PR I made, adding Version field to services.

Ok, I see.


CVAT DISCONTINUED?

My actions before raising this issue

[x] Read/searched the docs
[ ] Searched past issues

Is cvat development stopped?
30 days without any change?

You could find some details here: https://github.com/openvinotoolkit/cvat/issues/4444#issuecomment-1141066544

@sezarxray ,
The short answer is no. Please send your questions to https://community.intel.com/t5/Intel-Distribution-of-OpenVINO/bd-p/distribution-openvino-toolkit forum.

@sezarxray , CVAT.org should be online in the nearest future. But you can try this one: https://app.cvat.ai/. It is supported by CVAT core team. Please try our new repository: https://github.com/cvat-ai/cvat

Now it online in read only mode.
Users are able to move their data to https://app.cvat.ai
cvat.org will be maintained for some period of time and then disabled forever.