b3 endless event

What is your question?
Is there a script event that does that one b3 endless event where the characters are in front of everything, more closer to the screen like a standoff

Someone?

you can probably make the illusion of that by resizing them and setting their scroll factor on something higher than one

alr thx


Specify icon/variable type in json schema

Would be really helpful to be able to specify the type of variable in custom json schemas.
This would allow anyone to show different icon for each property of the json schema to help the end user recognizing the functionality of each property.
Right now we cannot change the icon nor specify the variable type, right?
Check this screenshot:

Thanks!

I manually edited the json schema logic adding a new attribute "kind" to force the entry to get a different icon.

@LoneDev6 What line of code and file did you change?

"node_modules\monaco-yaml\lib\esm_deps\yaml-language-server\out\server\src\languageservice\services\yamlCompletion.js"
around line 220 I added this, so now I can add a "kind" attribute to my schema and specify the icon value I want (type).
kind: propertySchema.kind ? propertySchema.kind : this.getSuggestionKind(propertySchema.type),

@LoneDev6 Thank you for sharing your solution!


ACME documentation improvement

Adds documentation how to reuse an ACME account.
Additionally also adds the configuration parameters, to the configuration documentation.
Fixes #3149

Coverage remained the same at 57.779% when pulling b44431b6a2bb533fb51e9a10c1b6b48e7b3c5415 on unic:feature/acme-documentation-improvement into 772894c414baca916c44ce1f91fb3fe6b33c88f1 on Netflix:master.

Thanks for the feedback. I've integrated your suggestions

@peschmae thanks for the quick workaround. I don't seem to have the permissions, to update the branch to latest version, before being able to merge it.

@hosseinsh That's probably because I switched over from my private fork, to an organizational one. Need to check that tomorrow.
For now, I've rebased my branched to the master, and it should be up to date again

Thanks @peschmae for the PR!
Documentation is certainly an area, we need to improve.


Remove ImageBuf from druid-shell

We've got a piet release containing ImageBuf, so remove it from druid-shell.

Never mind, this is too soon: piet-common doesn't forward image yet.


Maybe doesn't work?

Maybe I am misunderstanding how to use this- but I am unable to get cookies to persist on my browser
I put this at the start of my streamlit app
controller = CookieController()
user_id = controller.get('user_id')
if user_id is None:
    controller.set("user_id", str(uuid4()))
user_id = controller.get('user_id')

And I am getting new UUIDs each time I refresh the page.
Seems like the cookies are getting cleared on refresh ( I get new UUIDs each time I refresh )
I've tried setting some different settings, most recently
 same_site="lax", secure=False, partitioned=True, max_age=999999999999999
but I always get the same result (different UUIDS on refresh)

Same here.
I got the following test code from Streamlit Forum but getAll() is misleading since it doesn't fetch cookies from browser (just buffered return).
Then I tried with a refresh (see after) but raises streamlit.errors.DuplicateWidgetID: There are multiple widgets with the same key='cookies'
controller = CookieController()

# Set a cookie
controller.set('cookie_name', 'testing')

# Get all cookies
# controller.refresh()
cookies = controller.getAll()

# Get a cookie
cookie = controller.get('cookie_name')

# Remove a cookie
controller.remove('cookie_name')

Nota: while running under debugger, the cookie appeared once in the browser... but not repeatable.

+1

For me,  it seem neither the getAll() nor get()  picked up any thing from cookie.   It's weird .

I'm also seeing very weird behavior (especially with multipage app).
During logout, I do
token_expiry(email)
    if controller.get('c_user'):
        controller.remove('c_user')
    st.info("Logged out successfully!")
    st.switch_page("Home.py")

And below is a repeated error I see.
File "/usr/local/lib/python3.12/site-packages/streamlit_cookies_controller/cookie_controller.py", line 163, in remove
self.__cookies.pop(name)
KeyError: 'c_user'
There are multiple other cases noted as well where this doesn't seem to work consistently. Sometimes getAll() doesn't even print anything.
What is equally weird is when I print
st.write(st.session_state.get('cookies'))

prints cookies with c_user (key)
But when I print below, both donot return anything.
st.write(controller.getAll())
st.write(controller.get('c_user'))

I'm also having problems getting a cookie.

unavailable
import streamlit as st
from streamlit_cookies_controller import CookieController

# 设置页面配置
st.set_page_config('Cookie QuickStart', '🍪', layout='wide')

# 初始化 Cookie 控制器
controller = CookieController()

# 检查是否已登录
def check_login():
    cookies = controller.getAll()
    return 'username' in cookies

# 显示欢迎信息
def welcome_user():
    cookies = controller.getAll()
    username = cookies.get('username', 'Guest')
    st.write(f"Welcome to Streamlit Cookie Controller :cookie: {username}")

# 登录表单
def login_form():
    st.title("欢迎访问 Streamlit Cookie Controller :cookie:")
    username = st.text_input("用户名")
    password = st.text_input("密码", type="password")
    if st.button("登录"):
        if username and password:
            # 简单验证（例如，用户名和密码是否都不为空）
            controller.set('username', username)
            st.experimental_rerun()

# 主逻辑
if check_login():
    welcome_user()
    if st.button("注销"):
        controller.remove('username')
        st.experimental_rerun()
else:
    login_form()

I solved it.
https://github.com/duolabmeng6/duolabmeng6.github.io/issues/2


Update docs for Cluster Autoscaler on AKS Engine

Update docs for Cluster Autoscaler on AKS Engine.

Coverage remained the same at 34.344% when pulling 8f8000edad9e5ddc554b4ee043be5733c501a6ab on xiongyf/ca-docs into 17c79494e2772afbae2ec942838aaefac11cd618 on master.

@abuccts Would you like to add this doc to the openpai handbook? I think we can add a question like How to enable cluster autoscaler in https://openpai.readthedocs.io/en/latest/manual/cluster-admin/installation-faqs-and-troubleshooting.html, and let users refer to https://github.com/microsoft/pai/blob/master/contrib/aks-engine/readme.md as an answer.

Currently there's no way to enable CA in an existing cluster, you need to use aks and deploy with aks-engine from scratch, so this is a standalone part under contrib. It's not applicable for most users, so it might not be suitable for faq?

Installation FAQ is not just FAQ for the quick-start installation. It could be any questions about the installation. I think it is OK to put this in the FAQ section and tell users who are interested to install the cluster from scratch and try this feature.


Useless "Please select an Incremental Reading deck." when reviewing

I mix decks as described in https://github.com/aleksejrs/anki-2.0-vsa-and-ire#usage, and am getting that dialog, which seems to be completely pointless since the add-on knows where to extract and where to find the cards among which to organize this card.

Hmm, apparently it means something.
Decks:
/
/::s
/::ir
/::s has a New card.

I go to "/" and rate the New card from /::s. Now it should be a Review card.
A few seconds to load the next card from /::ir.
I press "s" or "Esc" to stop reviewing.
The mentioned New card is New again.

Hi,
I'm not sure I understand the first part. That message should only occur when opening the organiser in a deck with no IR cards. If there are no IR cards, there is nothing organise.
The second part I will look into. If I understand correctly, you're saying that regular Anki cards are being reset if they are followed immediately by an IR card. That shouldn't happen.

The first part:
Decks:
/ (root deck, empty)
/::s (normal Anki spaced repetition deck, Review/Learn/New)
/::ir (Incremental reading deck)
The current deck is "/", so IR cards are in the same global queue (or queue of queues) as the spaced repetition card that is reset.
There are three queues:

Learn cards,
Review cards,
New cards (in /::s and its subdecks), then Incremental Reading cards (in /::ir).
The 2nd and the 3rd queues are intermingled with each other.

When I am reviewing and an IR card appears, the message appears.  Maybe it depends on the kind of the previous card, but after it happened once, that card was New.

Now I am reviewing and two cards have been reset, but I didn't notice any message. Could have dismissed as the review limit message though.

You didn't miss anything. This is a serious bug, that I somehow didn't notice until now. Whenever you answer an IR card, the add-on reschedules the previous card, not the current one.
Give me a couple of days to come up with a decent solution for this. The scheduling code is the only part of the add-on that I haven't completely rewritten, so there's probably a lot I need to fix.

I've fixed that particular problem, but the scheduling code still needs a lot of work. It hasn't really changed since IR2, and I've been procrastinating about rewriting it because it's such a big job. It doesn't even use Qt widgets -- it's just a bunch of HTML and JavaScript in a webview. I'll put this at the top of my to-do list, but it'll probably take a few weeks.


Convert Istio templates to helm style

I don't think we should do this for 0.2 unless it's somehow super straightforward, it's an unplanned new feature

It requires just replacing the syntax in the templates, it's not a new feature, and there are no code changes.

the feature (as far as I understand) is to (re-)use the helm engine to do variable substitution in our templates,
that sounds great but again not sure now is the right time, maybe we should finish up creating the N yamls the way we've been doing so far and only what we need to check in and consider that change for when we have more time to think it through (unless again it's very straightforward, I'm very much looking forward to a big red diff at some point to delete all those generated files but probably not 0.2)

@lachie83 can you take a crack at this? Many of our users love the helm charts that you guys did. So we would like to make sure that the helm charts for 0.2.x are well tested before public consumption. Also, it would be great if you could fix the helm versions. The 0.2 helm chart installing 0.1.x has been thoroughly confusing for some of our end users.
To be clear, the 0.2.4 is not the final release. There will be quite a few patch releases and potentially weekly releases going forward. It would be good to sync the helm chart version with the istio version.

note that this task is slightly different from the helm chart themselves
See https://github.com/kubernetes/charts/issues/2297 for cleanup request of confusing helm versions
See https://github.com/kubernetes/charts/issues/1909 for having helm charts for 0.2 series

Sure. I'd love it. Thanks for asking. Would it be worth jumping on a quick call to straighten out the details then I'll write up a proposal in Github?

@lachie83 @rshriram @ldemailly I think we want a stable version before update the helm charts for istio based on the request here https://github.com/kubernetes/charts/issues/1909

@gyliu513 stable version will not help when we start doing weekly releases. We need a mechanism for users to specify the version they want or pick a helm chart corresponding to the minor version (0.2.x, 0.3.x, etc).

@rshriram ok, I see, I think that now the helm chart should already have such capability to handle different versions. @lachie83

@rshriram can you confirm that I'm clear to cut a chart for 0.2.4 pre-release? I've created a release variable in the chart values so it should be simple enough to update that value once we have the 0.2.x kubernetes resources updated. See https://github.com/kubernetes/charts/blob/master/incubator/istio/values.yaml#L6

@lachie83 sorry we missed this earlier.  Yes, it would be great if you could cut a chart for 0.2.4, which is our first RC.  I expect a new RC will come out this week too, but it is good to have the helm chart and people testing that too.

@linsun -- Absolutely. I will rebuild the chart of that pre-release. I will provide a link to the PR and you can let me know what values need to be exposed as configurable items when installing with Helm. I'm planning to start working on this tomorrow

@lachie83 excellent, thank you!!

@lachie83 can you please use the files and templates from master? There will be another release, and there have been changes in the last 6 days.

@andraxylia okay can do. Where are the installation docs?

https://istio.io/docs/setup/kubernetes/quick-start.html

@lachie83 are you going to post some PRs for https://github.com/kubernetes/charts/issues/1909 ? If not, I can help to make a 0.2.4 version of istio.

Yes I will

Here's the PR #2369 - I'm having issues rendering CRDs correctly using helm 2.6.1 on a Kubernetes 1.7 cluster. I'm going to raise an issue there.

Here's the helm issue - https://github.com/kubernetes/helm/issues/2994

The PR is all but done but need an assist on the following:

ServiceGraph not rendering dotviz
Dashboard not displaying data
Deploying BookInfo only works in the same namespace as the istio components (istio-system)

Happy to schedule a time to walk through the helm chart to demo the UX and gather feedback.

Great, thanks @lachie83 !
For ServiceGraph and Dashboard cc @douglas-reid
I need to try bookinfo, it works for us, and the fact istio is install with helm should not change behaviour.

@lachie83 how can I help troubleshoot? have you tried deploying in a similar fashion (w/o Helm) and verified that dotviz and the istio dashboard work as expected with your test case?
Should we troubleshoot in a separate thread?

@douglas-reid Thanks for reaching out Doug. No doubt I've probably make a typo in the configuration when converting to Helm. I have a cluster up and running with helm and just need a set of eyes to walk me through how to debug. Do you have a free 30m to jump on a zoom?

@lachie83 Sure. Maybe tomorrow mid-morning?  Let's schedule over email: dougreid at google.

Deploying BookInfo only works in the same namespace as the istio components (istio-system)
I have been deploying bookinfo in the default namespace, and it works fine.  In fact, we don't recommend users to deploy the microservices in the istio-system namespace, as automatic side car injection would not work.

@andraxylia I've fixed all remaining issues and the PR should be good to review. I was able to work around all but a single helm issue which was to do with the initializer install which I will follow up.

Thanks @linsun I found an issue in my configuration and have fixed this. I'm now able to install bookinfo into another namespace.

Thanks, I will review as well. FYI, the initializer requires kubernetes cluster with alpha features enabled.

@ldemailly we may have to rethink the way we're doing chart versioning. See https://github.com/kubernetes/helm/issues/3009

Based on feedback, we are going with making the helm functionally identical with the old templates and deprecating.

that hasn't shipped, did it ? so a bit early to close, no ?

I believe helm is standard now. Closing.


You can enter in your own wool room (Some maps)

XML: http://pastebin.com/kb8yazNA
Version: 9f9f043
EDIT: This doesn't happen in map proto 1.3.0

Appears to be a <regions> problem, maybe a bug in c3dfc8cd27

@AngelCasillas01 That does not touch anything of

@Carlos934 Yes it does, they modify and check liquid regions, so they have added BlockPlaceEvent isn't nothing to do but something there maybe has bugged something about this

@Carlos934 Try compiling Cardinal for lastest version and try it again, make sure to post the new log :)

@AngelCasillas01 The commit version is what we want, so a link to the commit is perfectly fine.

@twizmwazin ¿Al final cual es el error?

@twizmwazin es "were is the bug on" estas diciendo que es el bug ;)

@AngelCasillas01 I don't have a doctorate in English, I speak Spanish

@Carlos934 I'm just correcting you, i speak spanish too

@AngelCasillas01 Me refería a.. ¿Cuál es el error?
No me refería a ¿Dónde está el error?
Sorry for the Spanish.
@AngelCasillas01 Me refería a.. ¿Cuál es el error?
No me refería a ¿Dónde está el error?
Sorry for the Spanish.

@Carlos934 por eso, pero no se traduce inmediatmente como lo hace google, lo haces con el common sense de la gramatica en ingles, puedes usar lo que te dije o puedes dejarlo haci pero como usted quiera :)

@AngelCasillas01 @Carlos934 Traten de mantener el el problema aqui, pueden discutir eso en privado.
Try to keep the issue here, you can discuss that in private

Último, no tengo idea de como se dice cual, y no uso traductor :'D
Esto se termina, mejor hay que concentrarnos en CardinalPGM.
Last, I don't have idea how say "cual", and i don't use translator :'D
This has finished, we must concentrate in Cardinal PGM.

Not sure what you mean by "this has finished", just wanted to let you know that Reshif's public download of GDIII is a bit different from the one on overcast, so a direct porting of XML will not work.

@SungMatt is correct, I remember having to nudge the map an mcedit. However, there are still a few lingering region issues in Cardinal that need to be worked out.

@SungMatt is a map downloaded with World Downloader... do not tell anyone ...

@Carlos934 You say that with a map developer helping develop the plugin :p

@CaptainElliott I mean that the map is correct with xml

Dont worry carlos, its LEGAL on oc.tc,
But u have a rule: don't distribute with out author's permission 😉
El dia 30/03/2015 17.34, "Carlos934"<EMAIL_ADDRESS>va escriure:

@SungMatt https://github.com/SungMatt is a map downloaded with World
Downloader... do not tell anyone ...
—
Reply to this email directly or view it on GitHub
https://github.com/twizmwazin/CardinalPGM/issues/492#issuecomment-87724758
.

Closing as this seems to be an issue between the XML and the map; they don't match.

Reopen, the map fits perfectly

Try with this xml: view-source:https://maps.oc.tc/Other/Tournament/Guardians of the Wool/Golden Drought III/map.xml

@TiTo-418 I use that

Are you guys using the map as it is on OCN or are you using Reshif's download?

@twizmwazin The problem is that parent filters are not implemented, the problem isn't a mismatched map and XML.

Reshif's download, with both XML (Reshif dowload and maps.oc.tc)

@CaptainElliott You however cannot enter your own wool room, so that is fixed. It is also not an issue of the map being incorrectly positioned, as it happens in both lanes equally.

Please, reopen this
Now you can not enter in your own wools room, but you can place blocks on it.

@twizmwazin Shouldn't this have a "bug" tag?

Maybe this is an XML problem, im not sure

For the ones subscribed to this issue, I guess this will interest you. I modified the xml by adding 2 more applied filters so you cannot place blocks in your own wool room. Feel free to comment my gist if you have a better way of doing it, but I think it's fine the way I've done it. Link

@iEli2tyree011 @twizmwazin Could you change the issue's title?

Pretty sure this issue was fixed on https://github.com/twizmwazin/CardinalPGM/commit/09d13e740b10751ba640060a36e664618c803f1c


change highlighted panel entry background color

This is fixed, but will only be live with the next full re-render in the next few days.


Madninja/test suite

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Create catalog.bom

This allows us to select the location etc. Please review and bring in line with app.yaml as required.

@duncanjw thanks for your contribution. I'm going to close it without merging and incorporate the template into brooklyn-spark.bom instead.


renderButton isn't working

I've tried to create a custom button using renderButton method. I found that all renderButton method is wrapper by TouchableHighlight with function to open the modal. But it's not working at all. So I've tried this
return (
    <LinkedInModal
      clientID="..."
      clientSecret="..."
      redirectUri="..."
      onSuccess={(token) => console.log(token)}
      renderButton={() => <Text>Sign in with LinkedIn</Text>}
    />
 );

Then I've got just text, which is open modal by clicking on it. But the thing is, that the text I wrapped isn't open a modal. What's the problem then?

React version: 16.11.0
React Native version: 0.62.2
react-native-linkedin version: 2.1.1
Platform(s) (iOS, Android, or both?): IOS

The actual problem is here:

On master branch in .ts file you're wrapping all renderButton with TouchableOpacity, but in node_modules there's no such wrapper, that's the problem

UPD:
This is working solution
const LinkedInButton = ({ ...props }) => {
  const modalRef = useRef();

  return (
    <LinkedInModal
      ref={modalRef}
      clientID="..."
      clientSecret="..."
      redirectUri="..."
      onSuccess={props.onSuccess}
      renderButton={() => (
        <CustomButton
          {...props}
          onPress={() => modalRef.current && modalRef.current.open()}>
          Sign in with LinkedIn
        </CustomButton>
      )}
    />
  );
};

Thanks for posting the solution @whitestranger7
This is a well timed issue :smile:


Start to build support for exploring the consensus layer

This is very W.I.P. now.

This is now obsolete, closing


Using libffi to build arm64 library and use it to build node-ffi

Hi all !
I want to use node-ffi on my arm64 device but the libffi embedded in the node-ffi package does not support arm64 whereas the npm libffi module is arm64 compliant. So is there a way to use the cross-compiled libffi to cross-compile node-ffi with arm64  ?
Thanks !

Yes, the lib included is as old as dinosaurs. You need to get latest libffi from git to deps/libffi
then cd deps/libffi
./autogen.sh;./configure --prefix=/usr;make;make install
cp aarch64-unknown-linux-gnu/include/ffi.h /usr/include
cp aarch64-unknown-linux-gnu/include/ffitarget.h /usr/include
cp aarch64-unknown-linux-gnu/fficonfig.h /usr/include
then put https://github.com/node-ffi/node-ffi/blob/master/deps/libffi/libffi.gyp file to deps/libffi with a fix:
line 118
      'conditions': [
        ['target_arch=="arm"', {
          'sources': [ 'src/arm/ffi.c' ],
          'conditions': [
            ['OS=="linux"', {
              'sources': [ 'src/arm/sysv.S' ]
            }]
          ]
        }, { # ia32 or x64

replace with
      'conditions': [
        ['target_arch=="arm64"', {
          'sources': [ 'src/aarch64/ffi.c' ],
          'conditions': [
            ['OS=="linux"', {
              'sources': [ 'src/aarch64/sysv.S' ]
            }]
          ]
        }, { # ia32 or x64

go back to module root cd ../../
and node-gyp rebuild

I fork an arm64 version.
I tried on odroid c2 ubuntu 18.02 aarch64.
Now compiling.
git clone https://github.com/jmcomby/node-ffi-napi.git
cd node-ffi
npm install
node-gyp rebuild

I am able to use npm install ffi-napi on nvidia jetson nano instead of node-ffi.


DRILL-4529: Force $SUM0 to be used when Window Sum is supposed to ret…

…urned non-nullable type

Since we have use same approach for regular sum() aggregate, it makes sense to apply to window sum() aggregate function.
LGTM
+1.


🚀 Enhance Protocol Support: Add HTTP/2 and HTTP/3 (QUIC)

Problem Overview
The current version of our HTTP server only supports HTTP/1.x, which limits its performance and scalability, especially under high load conditions. Modern web applications expect faster, more efficient protocols, and without support for HTTP/2 and HTTP/3 (QUIC), our server might struggle to handle concurrent connections effectively. This results in slower response times, inefficiencies in handling multiplexed requests, and increased latency for users—issues that modern web standards have already addressed.

Why This is Important:

Performance Gains: HTTP/2 offers significant improvements like multiplexing, header compression, and server push, reducing latency and improving resource load times.
Future-Proofing: HTTP/3 (built on QUIC) is designed for even faster connections and improved security. It's already widely adopted by leading tech companies, and adding support for it will keep our server competitive and future-proof.
Scalability: With improved protocol support, the server can handle many more concurrent requests efficiently, reducing bottlenecks in high-traffic scenarios.

Proposed Enhancement
The goal is to implement support for both HTTP/2 and HTTP/3 (QUIC) to make the server more performant, secure, and future-ready. Libraries such as Jetty or Netty provide built-in support for these protocols, which can be leveraged to extend the existing codebase.
Key Areas of Focus:

Multiplexing: HTTP/2 allows multiple requests over a single TCP connection, reducing overhead. This will need to be integrated into the server’s connection management.
Header Compression: Implement support for HPACK (HTTP/2) and QPACK (HTTP/3) to reduce the size of headers sent between the client and server.
Server Push: HTTP/2 introduces server push capabilities, where the server can push resources to the client without the client explicitly requesting them. This could be an optional feature for users of the server.
Security: HTTP/3 is built on top of QUIC, which works over UDP rather than TCP. Implementing this means addressing security concerns associated with UDP, such as potential amplification attacks.

Requirements for Contributors:
Before diving into this task, please explain in detail how you plan to implement the new protocol support, including:

Which libraries or frameworks (Jetty, Netty, etc.) you plan to use. Custom code is much appreciated
Step-by-step breakdown of how you will integrate HTTP/2 and HTTP/3 support into the current server architecture.

How will you modify the ServerListenerThread to handle HTTP/2 connections?
How will you modify the HttpConnectionWorkerThread to support multiplexed streams?
How will you integrate QUIC (for HTTP/3) into the server’s networking stack?

Backward Compatibility: How will you ensure that HTTP/1.x support is retained for older clients?
Testing Strategy: How do you plan to test the new features, especially for performance improvements and multiplexing? Please include unit tests, integration tests, and load tests.
Error Handling: How will errors specific to these newer protocols be managed and logged?

Contribution Guidelines:
If you're interested in working on this, please comment below with your detailed plan on how you intend to implement this feature. Once your plan is reviewed and approved, you can begin work.

Important: Before making any contributions, please read the README.md file carefully to understand the project's goals and purpose. This will give you clarity on our mission.
For first-time contributors, please also review the CONTRIBUTING.md file, which contains important guidelines to make the contribution process smoother, especially for newcomers.

Helpful Resources:

Jetty HTTP/2 and HTTP/3 Documentation
Netty Documentation
HTTP/2 Specification
HTTP/3 (QUIC) Specification

Let's make our server faster, more efficient, and ready for the future!

@ajaynegi45  I can take this up if it's still available.

@ajaynegi45 I can take this up if it's still available.

Hi there! 👋
Thank you for your interest in contributing! Yes, this issue is still available, and I’m happy to assign it to you. When working on the Enhancement: Protocol Support for HTTP/2 and HTTP/3 (QUIC), please keep a few things in mind:

Security is key 🔐—make sure that implementing HTTP/3 (QUIC) doesn’t compromise on security. Address any potential vulnerabilities (like those related to UDP and QUIC) with care.

Our primary focus is to maintain a lightweight and highly efficient server. While integrating these protocols, ensure that we stick to our goal of minimal resource usage without sacrificing functionality. Please avoid adding anything that might make the server heavier.

Looking forward to your implementation! Feel free to ask any questions or request clarifications as you work on this.
Best of luck! 🚀

@ajaynegi45 I can take this up if it's still available.

Hi @manishrw,
I hope you're doing well! I wanted to check in and ask how things are progressing with the implementation of HTTP/2 and HTTP/3 (QUIC) support for the server. Have you made any updates or progress so far? Please feel free to share any work done or insights you’ve gathered.
Let me know if you need any assistance or have any questions.


Growatt SPH10K BH-UP not respondig

I try to apply this solution with Growatt SPH10k BH-UP hybrig inventer. I cannot get any response from the inverter.
Using osciloscope I see the data are repeatedly sent to inventer on the 485 link, but there is no response visible (and nothing in serial monitor).
Using 485-3 RJ-45 port on inverter, pins 1-B, 5-A
Slave ID is 1 as on the other Growatt inverters, speed 9600, checked in inverter registry.
What to do the get it worked?

You can try swapping the A and B lines. But I have written this for more basic Growatt inverters. Hybrid inverter is a lot more complicated device, I it is likely that the inverter is using a different set of registers. So even if the communication works, the data you get from the inverter will be unusable.


Export svg of tree to be used for JS error design, social media preview image, and website banner/card

I've generated a couple of exports using svg crowbar browser bookmarklet, and it seems to be working well. I uploaded one version to Figma, and was able to turn off the label layer visibility. I added a recent version to the noscript branch (#206).  I manually removed the labels svg group from the dom before exporting. I can easily generate another version when we want to update, if we make changes to the tree that are affecting the visuals.
Figma seems to pick up on id attributes, so it may be helpful to use those more consistently, right now I'm using classes for some of the groups. - probably depends how much we're doing with it in Figma if this matters, but not a very difficult change for me to make if it helps.


add minor amount handling

Financial systems and APIs use minor amounts in order to make it
impossible to encounter invalid amounts, like '0.5 JPY' or '0.001 EUR'
that aren't allowed per ISO-4177 currency standard.
Embedded the Amount type, to keep all calculation handling logic in
the same place.  For conversion to string (Number method and encoding)
the minor unit string is used instead of the locale-encoded string.
Fixes #5

Thank you for the PR, and for taking the time to explore this problem.
I am not a fan of the current approach (the Minor type). It introduces a lot of duplication and significantly expands the API surface of the package.
My initial suggestion was to introduce NewFromMinorUnits(n string, currencyCode) and convert ToMinorUnits() to return a string. What are the downsides to that approach, in your opinion? We could also use big.Int instead of strings, but I am not sure that buys us anything, since in my experience minor unit amounts are usually used for communication across the wire, not calculations (which are still doable by passing the string to big.Int, of course).

My goal here was to make a replacement for an api object that needs marshaling functionality.  Parsing individual values in a constructor still leaves the JSON handling to the user, with the possible errors that will arise from using Number method.

Coming back to this, I think if we expose the constructor you suggested (NewFomMinorUnits) and return a *big.Int from ToMinorUnits, then this can be moved into a separate (or sub-)package.
In the end, I want to avoid users juggling back and forth between minor and major units.  That's a recipe for headaches.  Keeping the same methods on the minor and major types allows users to swap easily without mixing them.

Thank you for your patience.
I gave this another thought, and I think we want to ensure we have methods for both big.Int and int64.
The reason why I had ToMinorUnits() return an int64 is because it's commonly used, e.g. in the Stripe package. The problem with the current implementation was that no error is returned in case of overflow, even though apd supports that (when using d.Int64() instead of reaching into the Coeff field).
So, I think we want to do the following:

Add NewAmountFromBigInt(n *big.Int, currencyCode string) and BigInt() *big.Int
Add NewAmountFromInt64(n int64, currencyCode string) and Int64() (int64, error)
Add a comment marking ToMinorUnits() deprecated (I'll do the removal later in a followup).

This solves the following problems:

There is no way to retrieve a big.Int from an amount, or create an amount from a big.Int
There is no way to create an amount from an int64
There is no error handling if an amount can't be converted to an int64

I think we want to keep currency.Minor outside of this repo, but tracked as a feature request, until we have more feedback on how people would like to use it. I strongly believe people should avoid doing arithmetic with both Amount and Minor, the Minor type should just be used to unmarshal and retrieve the amount. People declaring custom types for such cases is common in the community as a stop-gap (e.g. the lack of time.Date when only the date portion of a Time should be sent/received).

We're making good progress in #7, so let's close this one.


tour: [REPLACE WITH SHORT DESCRIPTION]

Opened by mistake, please delete this issue.

Opened by mistake, please delete this issue.

Greetings Arzar, you can close this issue with the close button next to the Comment button below the comment text.

Closed, sorry for the trouble.


Add app method to detect mode

Not sure if operating outside the two official "modes" of either :build or :server is supported, but if so this additional method would be convenient.
An example is the Contentful Middleman library (https://github.com/contentful/contentful_middleman), which for V3 had the concept of a :contentful environment when the task that pulls content down was run, but has now switched to setting :contentful as the mode for V4.
Anyhow, this method is just a convenience but I expected it's existence based on the parallel existence of the environment? method.

Yup, I made a :contentful mode in my own fork of their repo. This is a nice convenience method.


Missing cephfs API components: file xattr

The cephfs API implements function(s) below but go-ceph does not:

ceph_fgetxattr
ceph_flistxattr
ceph_fremovexattr
ceph_fsetxattr

This issue has been filed to track implementing this missing
functionality in the appropriate package within go-ceph.
Please refer to the Ceph C API for details about the function(s)
in question.
NOTE: This issue was generated by a script.
If the content is innacurate or wording seems a bit odd
please excuse the script and blame the creator @phlogistonjohn

https://tracker.ceph.com/issues/46084


New zwave-js config version available: 7.3.1-20210503

Problem/Motivation

update persistent does not install

Expected behavior

(server to update when pressing the install button)

Actual behavior

Nothing happens

zwavejs2mqtt: 4.0.1
zwave-js: 7.3.0
home id:<PHONE_NUMBER>
home hex:0x811182e0
persistent
New zwave-js config version available: 7.3.1-20210503
press install this shows on the log
2021-05-07 20:29:00.731 INFO ZWAVE: Node 19: value updated: 37-0-currentValue true => true
2021-05-07 20:29:01.793 INFO ZWAVE: Success zwave api call installConfigUpdate { success: true, message: 'Success zwave api call', result: false }
Steps to reproduce

(click the install button)

Proposed changes

(If you have a proposed change, workaround or fix,
describe the rationale behind it)

Same. Fresh install, have only ever been on 0.14.1
"New zwave-js config version available: 7.3.1-20210503"
Clicking install shows a "Successfully call api installConfigUpdate" dialog, but nothing happens and the config notification remains.

zwavejs2mqtt: 4.0.1
zwave-js: 7.3.0
Home Assistant 2021.5.2
Using the update GUI install button doesn't update the zwave-js version and the notification remains.  After clicking install  a message is displayed  " successful call api installConfigUpdate"
"New zwave-js config version available: 7.3.1-20210503."

Config update persistence was fixed in the current release version of ZwaveJS2mqtt.
@frenck has already committed the new version to the add-on in #169. I suspect we'll see the new add-on version available soon.
https://github.com/hassio-addons/addon-zwavejs2mqtt/pull/169

Resolved in v0.15.0


Fix for topK and groupUniqArray over Nullable columns

Crash can be replicated without the fix as follow:
CREATE DATABASE db1;

CREATE TABLE db1.tx_src
(
    partition Date,
    timestamp DateTime,
    user_id Nullable(UInt32),
    counter_id Nullable(UInt32),
    description Nullable(String)
) ENGINE = ReplicatedMergeTree('/clickhouse/tables/{shard}/db1/tx_src', '{replica}', partition, timestamp, 8192)

CREATE TABLE db1.tx AS db1.tx_src ENGINE = Distributed(cluster_test, db1, tx_src ,rand())

INSERT INTO db1.tx_src(partition, timestamp, user_id, counter_id, description) VALUES(now(), now(), 1, 1, 'ss');
INSERT INTO db1.tx_src(partition, timestamp, user_id, counter_id, description) VALUES(now(), now(), 1, 1, NULL);
INSERT INTO db1.tx_src(partition, timestamp, user_id, counter_id, description) VALUES(now(), now(), 1, 1, 'aa');

Then execute :
SELECT groupUniqArray(description) FROM db1.tx
or
SELECT topK(3)(description) FROM db1.tx

@alexey-milovidov  can you please review this and also add a test in the project for this scenario to make sure won't break in the future as well.
I don't know yet what's the procedure to add tests and run them over the project but I'll figure out one day when I'll have more time :)

@silviucpp you can add a test file like this one https://github.com/yandex/ClickHouse/blob/master/dbms/tests/queries/0_stateless/00453_top_k.sql with expected output like here https://github.com/yandex/ClickHouse/blob/master/dbms/tests/queries/0_stateless/00453_top_k.reference

Sure,
Any instructions on how I can run the tests from sql file to generate the
reference file and also to test that test is ok ?
On Thu, 14 Dec 2017 at 03:36, Marek Vavruša<EMAIL_ADDRESS>wrote:

@silviucpp https://github.com/silviucpp you can add a test file like
this one
https://github.com/yandex/ClickHouse/blob/master/dbms/tests/queries/0_stateless/00453_top_k.sql
with expected output like here
https://github.com/yandex/ClickHouse/blob/master/dbms/tests/queries/0_stateless/00453_top_k.reference
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/yandex/ClickHouse/pull/1637#issuecomment-351581272,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AEl3ixfXiCeMgIxTsj7TegEiQSSty_wjks5tAHuggaJpZM4RBOvE
.

What I do usually is paste the commands into clickhouse console and copypaste output to the reference file. I'm sure there's a nicer way, but I forgot cc @ludv1x

OK I added test files based on your instructions... I guess are fine as time I'm not sure how to test them

What I do usually is paste the commands into clickhouse console and copypaste output to the reference file. I'm sure there's a nicer way, but I forgot cc @ludv1x

clickhouse-client -n < test.sql > test.reference

@alexey-milovidov I fixed the memory leak you mentioned

I renamed file 00531_aggregate_over_nullable to 00531_aggregate_over_nullable.reference as expected.
Also wrapped results of aggregate functions to arraySort, as aggregate function returns array in non-deterministic order.
(The order should be deterministic when running in single thread. And in the test, the query is run in single thread. But the order also depend on details of obtaining data from columns, that was changed recently, and the order of results also change.)
Also I decided to implement all my thoughts
For proper fix, we need to get rid of setArguments method and pass arguments in constructor of aggregate function in factory methods.

in #1681

Great job !


You should replace all size_t with "unsigned int"

size_t is defined as uint64_t in most cases.
Pure C does NOT support size_t.

unsigned int is equal to uint_64 in case of x64 switched on, or uint_32 as default.

You are right. Thank you! I will replace all size_t with "unsigned int" after you add page_presser.c.


Update eslint-plugin-lit to ^1.3.0

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

Thanks!


DR-1035 - Configuration Page - Add icons status dkim and spf

Hi team,
I added icons of dKim and Spf status as in domains list page
Could you review?
Example:

Nice!
If you want, you can also create tests for the different icons. But when you change how the data is obtained you have to update those tests.
Could you work along @mvillaseco to fix vertical alignment and spacing?

Ok, Yes it is possible. I will add those tests.

:+1:

💯
Nice PR!

Looks great! 🔥


LIFX firmware update breaks home-assistant integration

Make sure you are running the latest version of Home Assistant before reporting an issue.
You should only file an issue if you found a bug. Feature and enhancement requests should go in the Feature Requests section of our community forum:
Home Assistant release (hass --version):
0.49.0.dev
Python release (python3 --version):
3.6
Component/platform:
lifx
Description of problem:
I've updated the firmware version on my colour 1000 and white 800 lights to version 1.22 from version 1.21 and they no longer work with home assistant. However they work on the lifx phone app like normal.
Expected:
Problem-relevant configuration.yaml entries and steps to reproduce:
light:
  - platform: lifx
    server: <IP_ADDRESS>

Traceback (if applicable):

Additional info:
When I toggle them on or off they just show as unavailable and nothing happens.

This is literally my nightmare if a new lifx firmware breaks the lan protocol. I do not use the lifx app at all so if the lan protocol goes anywhere, they will lose any 'smart' functionality they once had for me

@adamja I do not see a 1.22 firmware, where can it be downloaded?

This might be something for https://github.com/frawau/aiolifx
Have you tried with the example lifx-cli.py? I haven't yet, but I'm still on older firmware.

Indeed, the issue probably is in aiolifx. I do expect to be able to fix it either way, as soon as I get the new firmware installed.

Sorry guys, just saw the updates. I was having an issue with one of my lights and the support team linked me to a windows/mac updater that updated all my lights on the network to try and solve the issue.
However after that I can no longer control any of the updated lights with HA. There was one that didn't get updated and works fine. They still populate in HA, but as soon as you toggle on the UI it switches to unavailable for ~30s and none of my automations trigger them anymore.

@adamja A fix was already made and is on its way to HA. To apply the fix by hand, just open the file .homeassistant/deps/aiolifx/message.py and change line 98 from
    payload_size_bytes = len(self.payload)/8

to
    payload_size_bytes = len(self.payload)

(so just delete the slash-eight characters at the end).

@amelchio got it, thank you so much! I have my light back 👍


Segmentation Fault (Core Dumped )

Hi there,
When I try to run SoftGym, The PyFleX compilation works just fine, but when I run the line in the example python file that goes:
env = normalize(SOFTGYM_ENVSargs.env_name)
I get the error:
Unable to initialize SDLCould not initialize GL extensions
Reshaping
Segmentation fault (core dumped)
Do you have any idea what could be causing this?
System specifications:
Ubuntu 18.04, CUDA 9.1
OpenGL applications work fine on my system, for example glxinfo and glxgears work as expected.

We have not tested the compilation steps for ubuntu 18. Are you using the docker?

I have encountered the same problem. BTW I am using a docker.

I am not using the docker, have used the other installation method. I am doing this whole process on a compute cluster and for admin reasons cannot use docker.

If you are using a cluster, then you probably do not have a display enviornment for GL applications. Can you try running softgym with the headless option on?

I had this problem when running the example from inside the docker. (In Ubuntu 18 and CUDA 11)
I solved it executing the example outside the container, but you need to set env variables again if not already in .bashrc
conda activate softgym
export PYFLEXROOT=${PWD}/PyFlex
export PYTHONPATH=${PYFLEXROOT}/bindings/build:$PYTHONPATH
export LD_LIBRARY_PATH=${PYFLEXROOT}/external/SDL2-2.0.4/lib/x64:$LD_LIBRARY_PATH

python examples/random_env.py --env_name PourWaterAmount

So on the cluster I have been using xvfb and so the display environment should be working properly (because other GL applications like glxgears works as expected). However, I just ran it again headless and get a very similar error. I also attempted the solution provided by FranBesq and get the same issue.
Waiting to generate environment variations. May take 1 minute for each variation...
eglInitialize() failedeglChooseConfig() failedfailed to find suitable EGLConfigeglCreateContext() failedeglCreatePbufferSurface() failedeglQueyContext(EGL_RENDER_BUFFER) failedCould not initialize GL extensions
Segmentation fault (core dumped)

Looks like this is an EGL error. Are you sure you have all correct EGL libraries installed on the cluster? maybe try this:
apt-get install libglfw3 libgles2-mesa-dev

Yup, these libraries are all installed.

I have encountered the same problem. BTW I am using a docker.

I had this problem when running the example from inside the docker. (In Ubuntu 18 and CUDA 11)
I solved it executing the example outside the container, but you need to set env variables again if not already in .bashrc
conda activate softgym
export PYFLEXROOT=${PWD}/PyFlex
export PYTHONPATH=${PYFLEXROOT}/bindings/build:$PYTHONPATH
export LD_LIBRARY_PATH=${PYFLEXROOT}/external/SDL2-2.0.4/lib/x64:$LD_LIBRARY_PATH

python examples/random_env.py --env_name PourWaterAmount

I still get:
Could not initialize GL extensions
CUDA 11 and Ubuntu 18.04
I wonder if you have some ideas, thank you

I have encountered the same problem. BTW I am using a docker.

I had this problem when running the example from inside the docker. (In Ubuntu 18 and CUDA 11)
I solved it executing the example outside the container, but you need to set env variables again if not already in .bashrc
conda activate softgym
export PYFLEXROOT=${PWD}/PyFlex
export PYTHONPATH=${PYFLEXROOT}/bindings/build:$PYTHONPATH
export LD_LIBRARY_PATH=${PYFLEXROOT}/external/SDL2-2.0.4/lib/x64:$LD_LIBRARY_PATH

python examples/random_env.py --env_name PourWaterAmount

I still get:
Could not initialize GL extensions
CUDA 11 and Ubuntu 18.04
I wonder if you have some ideas, thank you

Have you tried @yufeiwang63 answer? If it didn't work here are some things I would try. Although I don't want to send you on a wild goose chase.

I described the steps I followed to install on my fork

@Xingyu-Lin links this article on his docker.md wich may be helpful

The way I call random_env.py is through python interpreter directly, although you may have to do some minor changes on random_env.py.
I dont see how this can be of any help with openGL, but it helped me with imports (conda messed up some env variables). Your installation may have some problem locating gl libraries, again, check the article above for additional help with this.

python
import examples.random_env as rand_env
rand_env.main()

I have encountered the same problem. BTW I am using a docker.

I had this problem when running the example from inside the docker. (In Ubuntu 18 and CUDA 11)
I solved it executing the example outside the container, but you need to set env variables again if not already in .bashrc
conda activate softgym
export PYFLEXROOT=${PWD}/PyFlex
export PYTHONPATH=${PYFLEXROOT}/bindings/build:$PYTHONPATH
export LD_LIBRARY_PATH=${PYFLEXROOT}/external/SDL2-2.0.4/lib/x64:$LD_LIBRARY_PATH

python examples/random_env.py --env_name PourWaterAmount

I still get:
Could not initialize GL extensions
CUDA 11 and Ubuntu 18.04
I wonder if you have some ideas, thank you

Have you tried @yufeiwang63 answer? If it didn't work here are some things I would try. Although I don't want to send you on a wild goose chase.
* I described the steps I followed to install on my [fork](https://github.com/FranBesq/softgym/blob/master/docker/docker.md)

* @Xingyu-Lin links [this<EMAIL_ADDRESS>on his docker.md wich may be helpful

* The way I call random_env.py is through python interpreter directly, although you may have to do some minor changes on random_env.py.
  I dont see how this can be of any help with openGL, but it helped me with imports (conda messed up some env variables). Your installation may have some problem locating gl libraries, again, check the article above for additional help with this.

python
import examples.random_env as rand_env
rand_env.main()

Hello, Thanks for your answering.
I have tried your solution and I successfully complied outside the container but it still did not work. I have also tried on Ubuntu 16.04 NVIDIA 440.33.01 and CUDA 10.2 (actually I suspect that whether the authors have successfully complied on CUDA 9.2 cause I have tried it before, but apparently some libraries do not match where you will get a error 'undefined symbol: cudaSetupArgument'. ), but still got 'Could not initialize GL extensions.' So I really do not know how to successfully compile authors' softgym as I have already tried at least 30 hours on it while nothing comes out. I wonder if you could provide some alternative ideas. Thanks for your answer!

Hi LiDuanAtGlasgow,
I  feel sorry that the compilation brings so much trouble to you. We ourselves also spent lots of time getting the system running correctly at our early stage of development on this project.
We were indeed able to compile the project with Nvidia driver 440.33.01, and cuda version 9.1 or 9.2. See the screenshot below.

Also, can you check your $LD_LIBRARY_PATH to make sure it looks sth similar to mine?

@DhananjayAshok For running on clusters, NvidiaFlex requires OpenGL. The solution is to simulate a display with virtual GL and TurboVNC. You can try the followings:

Install OpenGL: sudo apt-get install freeglut3-dev mesa-utils
Install VGL
Install TurboVNC 2.11. I tried other versions but only 2.11 worked for me...
sudo apt install x11-xserver-utils libxrandr-dev
Configure the X: sudo nvidia-xconfig -a --use-display-device=None --virtual=1280x1024
Emulate virtual display: sudo nohup Xorg :7 &
Run an auxiliary VNC server: /opt/TurboVNC/bin/vncserver :x, where x is the virtual display number
Run everything with DISPLAY=:x vglrun -d :x.y, where y denotes which GPU to use

After setting up this, you can try 'DISPLAY=:x, vglrun -d :x.y glxinfo' to see if it is working.

Hi @yufeiwang63  and @Xingyu-Lin ,
I am also running into the same problem that @LiDuanAtGlasgow  has been running into. I am using Ubuntu 18.04 and the provided Docker.
I can produce a detailed issue report, but before doing that, I am interested in knowing the workflow that you two use to run softgym. Just to be clear, did you need to follow the instructions in this fork linked above? For example, the author says to move outside the docker environment -- but I thought that defeats the purpose of using docker in the first place?

Hi @yufeiwang63  and @Xingyu-Lin ,
I am also running into the same problem that @LiDuanAtGlasgow  has been running into. I am using Ubuntu 18.04 and the provided Docker.
I can produce a detailed issue report, but before doing that, I am interested in knowing the workflow that you two use to run softgym. Just to be clear, did you need to follow the instructions in this fork linked above? For example, the author says to move outside the docker environment -- but I thought that defeats the purpose of using docker in the first place?

The purpose of the container is to compile PyFlex as far as I understood. I followed similar steps to the PyFlex docker.md when creating the fork and got it to work this way. Again, Im not going to talk in behalf of the authors obviously. But I think is worth giving it a try.

The purpose of the container is to compile PyFlex as far as I understood. I followed similar steps to the PyFlex docker.md when creating the fork and got it to work this way. Again, Im not going to talk in behalf of the authors obviously. But I think is worth giving it a try.

We generally do not use the docker on our local desktop and only use it for launch experiments on computing clusters. On our local desktop, we follow the instructions here https://github.com/Xingyu-Lin/softgym/blob/master/README.md. The purpose of the docker was to make the compilation easier for more people. What @FranBesq said is correct: The docker is only used for compiling the Flex and PyFlex. Once the compilation is done, softgym can be run in a normal python environment.

Hi @yufeiwang63 and @Xingyu-Lin ,
I am also running into the same problem that @LiDuanAtGlasgow has been running into. I am using Ubuntu 18.04 and the provided Docker.
I can produce a detailed issue report, but before doing that, I am interested in knowing the workflow that you two use to run softgym. Just to be clear, did you need to follow the instructions in this fork linked above? Is this the workflow that you generally follow?

We generally do not use the docker on our local desktop and only use it for launch experiments on computing clusters. On our local desktop, we follow the instructions here https://github.com/Xingyu-Lin/softgym/blob/master/README.md. The purpose of the docker was to make the compilation easier for more people. What @FranBesq said is correct: The docker is only used for compiling the Flex and PyFlex. Once the compilation is done, softgym can be run in a normal python environment.

Hi @yufeiwang63 and @Xingyu-Lin ,
I am also running into the same problem that @LiDuanAtGlasgow has been running into. I am using Ubuntu 18.04 and the provided Docker.
I can produce a detailed issue report, but before doing that, I am interested in knowing the workflow that you two use to run softgym. Just to be clear, did you need to follow the instructions in this fork linked above? Is this the workflow that you generally follow?

Hi @Xingyu-Lin  @FranBesq  here is my more detailed minimum working example:
https://github.com/Xingyu-Lin/softgym/issues/9
(In a separate issue report)

Hey @Xingyu-Lin  what do you have in your /usr/lib/nvidia-440 folder? I do not have a folder like that in /usr/lib, and I suspect that could be my issue.

Hi @rehaanahmad2013, here is my ls result:
alternate-install-present
alt_ld.so.conf
bin
ld.so.conf
libEGL_nvidia.so.0
libEGL_nvidia.so.440.64.00
libEGL.so
libEGL.so.1
libEGL.so.1.1.0
libEGL.so.440.64.00
libGLdispatch.so.0
libGLESv1_CM_nvidia.so.1
libGLESv1_CM_nvidia.so.440.64.00
libGLESv1_CM.so
libGLESv1_CM.so.1
libGLESv1_CM.so.1.2.0
libGLESv2_nvidia.so.2
libGLESv2_nvidia.so.440.64.00
libGLESv2.so
libGLESv2.so.2
libGLESv2.so.2.1.0
libGL.so
libGL.so.1
libGL.so.1.7.0
libGLX_indirect.so.0
libGLX_nvidia.so.0
libGLX_nvidia.so.440.64.00
libGLX.so
libGLX.so.0
libnvcuvid.so
libnvcuvid.so.1
libnvcuvid.so.440.64.00
libnvidia-allocator.so
libnvidia-allocator.so.1
libnvidia-allocator.so.440.64.00
libnvidia-cbl.so.440.64.00
libnvidia-cfg.so
libnvidia-cfg.so.1
libnvidia-cfg.so.440.64.00
libnvidia-compiler.so
libnvidia-compiler.so.1
libnvidia-compiler.so.440.64.00
libnvidia-eglcore.so.440.64.00
libnvidia-egl-wayland.so.1
libnvidia-egl-wayland.so.1.1.4
libnvidia-encode.so
libnvidia-encode.so.1
libnvidia-encode.so.440.64.00
libnvidia-fatbinaryloader.so.440.64.00
libnvidia-fbc.so
libnvidia-fbc.so.1
libnvidia-fbc.so.440.64.00
libnvidia-glcore.so.440.64.00
libnvidia-glsi.so.440.64.00
libnvidia-glvkspirv.so.440.64.00
libnvidia-ifr.so
libnvidia-ifr.so.1
libnvidia-ifr.so.440.64.00
libnvidia-ml.so
libnvidia-ml.so.1
libnvidia-ml.so.440.64.00
libnvidia-opticalflow.so
libnvidia-opticalflow.so.1
libnvidia-opticalflow.so.440.64.00
libnvidia-ptxjitcompiler.so
libnvidia-ptxjitcompiler.so.1
libnvidia-ptxjitcompiler.so.440.64.00
libnvidia-rtcore.so.440.64.00
libnvidia-tls.so.440.64.00
libnvoptix.so.1
libnvoptix.so.440.64.00
libOpenGL.so
libOpenGL.so.0
tls
vdpau
xorg

Hello, I got the same question in an ubuntu16.04 server. My cuda version is 9.2, and the nvidia driver version is 460.73.01. When I ran the random_env.py, if headless 0, it showed
Could not initialize GL extensions
Reshaping
Segmentation fault (core dumped)
and if headless 1, it showed
eglGetDisplay() failedeglInitialize() failedeglChooseConfig() failedeglCreateContext() failedeglCreatePbufferSurface() failedeglMakeCurrent() failedeglQueyContext(EGL_RENDER_BUFFER) failedCould not initialize GL extensions
Segmentation fault (core dumped)
I tried the methods above, but can't work.
I wonder whether the nvidia driver version affect?

If you are on a ubuntu server, it's very likely that you don't have a display environment. Does it work with headless set to 1?

No, I tried both, neither 1 nor 0, it didn't work.

Dirver version does make a difference. We got it working with Nvidia driver 440.33.01, and cuda version 9.1 or 9.2, although others also got it working under some other driver versions.

Ok，thanks, I 'll try.

Hi，when I  ran . ./compile_1.0.sh, there were some warnings:
/softgym/PyFlex/bindings/opengl/shadersGL.cpp:3386:25: warning: invalid conversion from ‘EGLConfig {aka void*}’ to ‘void**’ [-fpermissive]
g_eglConfig = configs[0]
/PyFlex/bindings/opengl/shadersGL.cpp:3390:33: warning             : invalid conversion from ‘EGLContext {aka void*}’ to ‘void**’ [-fpermissive]
g_eglContext = eglCreateContext(
^
/PyFlex/bindings/opengl/shadersGL.cpp:3398:40: warning             : invalid conversion from ‘EGLSurface {aka void*}’ to ‘void**’ [-fpermissive]
g_eglSurface = eglCreatePbufferSurface(g_eglDisplay, g_eglConfig,
Is this the reason why I couldn't run softgym？

So on the cluster I have been using xvfb and so the display environment should be working properly (because other GL applications like glxgears works as expected). However, I just ran it again headless and get a very similar error. I also attempted the solution provided by FranBesq and get the same issue.
因此，在集群上我一直在使用 xvfb，因此显示环境应该能够正常工作(因为其他 GL 应用程序如 glxgears 可以正常工作)。然而，我只是运行它再次无头，并得到一个非常相似的错误。我还尝试了 FranBesq 提供的解决方案，得到了同样的问题。
Waiting to generate environment variations. May take 1 minute for each variation...
eglInitialize() failedeglChooseConfig() failedfailed to find suitable EGLConfigeglCreateContext() failedeglCreatePbufferSurface() failedeglQueyContext(EGL_RENDER_BUFFER) failedCould not initialize GL extensions
Segmentation fault (core dumped)

Hi, have you solved this problem?

So on the cluster I have been using xvfb and so the display environment should be working properly (because other GL applications like glxgears works as expected). However, I just ran it again headless and get a very similar error. I also attempted the solution provided by FranBesq and get the same issue.
Waiting to generate environment variations. May take 1 minute for each variation...
eglInitialize() failedeglChooseConfig() failedfailed to find suitable EGLConfigeglCreateContext() failedeglCreatePbufferSurface() failedeglQueyContext(EGL_RENDER_BUFFER) failedCould not initialize GL extensions
Segmentation fault (core dumped)

@DhananjayAshok  Have you been able to solve this problem. Others have had the segmentation fault but I'm also experiencing the exact same output error with "eglInitialize()..." etc. I also used a non-docker approach for admin reasons.

Have you solved the problem yet?

I have encountered the same problem. BTW I am using a docker.

Have you solved the problem yet

I have encountered the same problem. BTW I am using a docker.

Have you solved the problem yet?

lib/nvidia-440文件夹中有什么？我在/usr/lib中没有这样的文件夹，我怀疑这可能是我的问题
Hello, I also encountered this issue. I entered echo $LD_ LIBRARY_ The PATH display is as follows

/compile_1.0.sh，有一些警告

你好，我在ubuntu16.04服务器上遇到了同样的问题。我的cuda版本是9.2，nvidia驱动版本是460.73.01。当我运行random_env.py时，如果headless 0，它显示 Could not initialize GL extensions Reshaping Segmentation fault (core dumped) ，如果headless 1，它显示 eglGetDisplay() failedglInitialize() failedglChooseConfig() failedglCreateContext() failedglCreatePbufferSurface() failedglMakeCurrent( ) failedglQueyContext(EGL_RENDER_BUFFER) failedCould not initialize GL extensions Segmentation fault (core dumped) 我试过上面的方法，但是不行。 请问nvidia驱动版有影响吗？

Hello, I have encountered the same problem as you. Have you resolved it?

Late to the party, but if anyone is stuck on this, you can run the scripts in headless mode. e.g.,
python examples/random_env.py --headless 1 --env_name PassWater
This worked in the prebuild Docker image which I setup in Ubuntu 20.04. The build script uses CUDA 9.2.


mycroft-msm: command not found

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

Configure SSH access to mycroft
SSH into the box
Run mycroft-msm, or mycroft-msm -h
See error -bash: mycroft-msm: command not found

Expected behavior
mycroft-msm is installed and can be used to manage skills.
Environment (please complete the following information):

Device type: Mark II
OS: Ubuntu
Mycroft-core version: 2022-10-18 06:11
Mycroft version: 21.2.1

Additional context
According to Mycroft Skills Manager, I should be able to manage Mycroft's skill with mycroft-msm but it seems mycroft-dinkum has deprecated it.
If there another way to install custom skill (TuneIn Radio for example)?
Thank you!

Not a good solution to the bug, but I just got mine this week and found this piece of documentation. https://mycroft-ai.gitbook.io/mark-ii/differences-to-classic-core/porting-classic-core-skills
I've yet to successfully port a skill over though.

Skills seems to work different under dinkum and the missing cli commands are on purpose https://github.com/MycroftAI/hardware-mycroft-mark-II/issues/95#issuecomment-1289972130


SECURESIGN-362 | Remove Keycloak from the installer

This pr aims to remove the key cloak installation from the tas installer and allows user to specify what OIDC provider to use.
Testing

Checkout branch
Launch OpenShift cluster and authenticate
Do a fresh build of the tas installer using the command go build -C tas-installer -o ../tas-install from root
Run the command ./tas-install install

With Keycloak

To use with keycloak,
Run the command oc apply --kustomize keycloak/operator/base
Wait for keycloak pods to run
Run the command  oc apply --kustomize keycloak/resources/base
Wait again
Run the command ./tas-install install
Press Y when prompted for OIDC configuration
Fill out details
Sign and Verfy

Without OIDC

Run the command ./tas-install install
Press n when prompted for OIDC configuration
This will set the OIDC to the public good instance
Sign and Verfy

There is a bit of syncing that needs to happen with this repo's moving parts! I cherry-picked the remove-keycloak commit into #104 because the other commits in this PR might not be necessary when combined with #99, and #103 Once #99 and #103 are in, we might remove the prompts for pull-secret & certs from the installer - and the custom OIDC config we might also want to manage only with helm. In any case, the remove-keycloak commit will be merged.

No worries, let me know if theirs anything else needed from this pr, if not Ill close it


CodeFix column not showing using style cop analyzer.

showing all rule set but not showing option to code fix. Please guide me to show codefix column to fix code.

I took a guess at where you were looking. Can you confirm that this is where you expected to see code fixes?


Constrain the mirror's movement to the container

After digging through the source code I don't think this is possible at the moment. I'm trying to do somthing like jQuery UI's containment option, but in Dragula's case with the mirror.
https://jqueryui.com/draggable/#constrain-movement
Would you accept a PR that adds this? Or would it be too much added complexity (based on my searches not a lot of people seem to need this)?
I think the simplest implementation would be an event that gets fired when the mirror moves, and allow the user to override the value.

In case anyone needs this, I wrote a (hacky) package to achieve it without changing anything in Dragula itself: https://github.com/spatie/dragula-constrain


How to run elasticsearch pod in gke autopilot mode

Hi there, Can some please tell me, why the pod deployed through GKE autopilot mode throws this error,  when describe events suggests that init containers were successfully created, started, and have done the task of passing "sysctl -w vm.max_map_count=262144".
max virtual memory areas vm.max_map_count [65530] likely too low, increase to at least [262144]

gke cluster throws me below stack-trace error for the deployed pod in GKE autopilot mode. These are logs of elasticsearch-pod-0
ubuntu@ubuntu$ kubectl logs  elasticsearch-pod-0

2021-03-04T18:57:19,302][INFO ][o.e.n.Node               ] [] initializing ...
[2021-03-04T18:57:19,520][INFO ][o.e.e.NodeEnvironment    ] [gbOK4rP] using [1] data paths, mounts [[/usr/share/elasticsearch/data (/dev/sdb)]], net usable_space [9.7gb], net total_space [9.7gb], spins? [unknown], types [ext4]
[2021-03-04T18:57:19,521][INFO ][o.e.e.NodeEnvironment    ] [gbOK4rP] heap size [1.9gb], compressed ordinary object pointers [true]
[2021-03-04T18:57:19,523][INFO ][o.e.n.Node               ] [gbOK4rP] node name [gbOK4rP] derived from node ID; set [node.name] to override
[2021-03-04T18:57:19,525][INFO ][o.e.n.Node               ] [gbOK4rP] version[5.0.0], pid[1], build[253032b/2016-10-26T05:11:34.737Z], OS[Linux/5.4.49+/amd64], JVM[Oracle Corporation/OpenJDK 64-Bit Server VM/1.8.0_111/25.111-b14]
[2021-03-04T18:57:22,709][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [aggs-matrix-stats]
[2021-03-04T18:57:22,710][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [ingest-common]
[2021-03-04T18:57:22,710][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [lang-expression]
[2021-03-04T18:57:22,710][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [lang-groovy]
[2021-03-04T18:57:22,772][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [lang-mustache]
[2021-03-04T18:57:22,772][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [lang-painless]
[2021-03-04T18:57:22,772][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [percolator]
[2021-03-04T18:57:22,773][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [reindex]
[2021-03-04T18:57:22,773][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [transport-netty3]
[2021-03-04T18:57:22,773][INFO ][o.e.p.PluginsService     ] [gbOK4rP] loaded module [transport-netty4]
[2021-03-04T18:57:22,774][INFO ][o.e.p.PluginsService     ] [gbOK4rP] no plugins loaded
[2021-03-04T18:57:23,193][WARN ][o.e.d.s.g.GroovyScriptEngineService] [groovy] scripts are deprecated, use [painless] scripts instead
[2021-03-04T18:57:31,491][INFO ][o.e.n.Node               ] [gbOK4rP] initialized
[2021-03-04T18:57:31,492][INFO ][o.e.n.Node               ] [gbOK4rP] starting ...
[2021-03-04T18:57:32,001][INFO ][o.e.t.TransportService   ] [gbOK4rP] publish_address {<IP_ADDRESS>:9300}, bound_addresses {[::]:9300}
[2021-03-04T18:57:32,008][INFO ][o.e.b.BootstrapCheck     ] [gbOK4rP] bound or publishing to a non-loopback or non-link-local address, enforcing bootstrap checks
ERROR: bootstrap checks failed
max virtual memory areas vm.max_map_count [65530] likely too low, increase to at least [262144]
[2021-03-04T18:57:32,086][INFO ][o.e.n.Node               ] [gbOK4rP] stopping ...
[2021-03-04T18:57:32,184][INFO ][o.e.n.Node               ] [gbOK4rP] stopped
[2021-03-04T18:57:32,184][INFO ][o.e.n.Node               ] [gbOK4rP] closing ...
[2021-03-04T18:57:32,208][INFO ][o.e.n.Node               ] [gbOK4rP] closed

Here's events of elasticsearch deployed pod
kubectl describe pod/elasticsearch-0
ubuntu@ubuntu$ kubectl describe pod/elasticsearch-0

Name:         elasticsearch-0
Namespace:    default
Priority:     0
Node:         gk3-autopilot-cluster-1-nap-1535p6rr-5687b4d4-2w8t/<IP_ADDRESS>
Start Time:   Fri, 05 Mar 2021 00:25:11 +0530
Labels:       app=elasticsearch
              controller-revision-hash=elasticsearch-6c57546b4b
              statefulset.kubernetes.io/pod-name=elasticsearch-0
Annotations:  seccomp.security.alpha.kubernetes.io/pod: runtime/default
Status:       Running
IP:           <IP_ADDRESS>
IPs:
  IP:           <IP_ADDRESS>
Controlled By:  StatefulSet/elasticsearch
Init Containers:
  increase-vm-max-map:
    Container ID:  containerd://bfda3431afee52e71a789cb7d6f612f4bb2ea5d81f9cb74bdc0733d8aa64a29f
    Image:         busybox
    Image ID:      docker.io/library/busybox@sha256:c6b45a95f932202dbb27c31333c4789f45184a744060f6e569cc9d2bf1b9ad6f
    Port:          <none>
    Host Port:     <none>
    Command:
      sh
      -c
      sysctl
      -p
    State:          Terminated
      Reason:       Completed
      Exit Code:    0
      Started:      Fri, 05 Mar 2021 00:25:30 +0530
      Finished:     Fri, 05 Mar 2021 00:25:30 +0530
    Ready:          True
    Restart Count:  0
    Limits:
      cpu:                750m
      ephemeral-storage:  1Gi
      memory:             3000Mi
    Requests:
      cpu:                750m
      ephemeral-storage:  1Gi
      memory:             3000Mi
    Environment:          <none>
    Mounts:
      /var/run/secrets/kubernetes.io/serviceaccount from kube-api-access-p7f8t (ro)
Containers:
  elasticsearch:
    Container ID:   containerd://ea6d1f14ec03b683fab51feb0cb0e540f7299250d973fcfc07301bd51128f865
    Image:          elasticsearch:5.0.0
    Image ID:       docker.io/library/elasticsearch@sha256:29f6b68a0088238f4a108e6c725163130e382a0f34ed62159c82e3961f0639fa
    Ports:          9200/TCP, 9300/TCP
    Host Ports:     0/TCP, 0/TCP
    State:          Terminated
      Reason:       Error
      Exit Code:    78
      Started:      Fri, 05 Mar 2021 00:27:15 +0530
      Finished:     Fri, 05 Mar 2021 00:27:32 +0530
    Last State:     Terminated
      Reason:       Error
      Exit Code:    78
      Started:      Fri, 05 Mar 2021 00:26:31 +0530
      Finished:     Fri, 05 Mar 2021 00:26:49 +0530
    Ready:          False
    Restart Count:  3
    Limits:
      cpu:                750m
      ephemeral-storage:  1Gi
      memory:             3000Mi
    Requests:
      cpu:                750m
      ephemeral-storage:  1Gi
      memory:             3000Mi
    Environment Variables from:
      elastic-config  ConfigMap  Optional: false
    Environment:         <none>
    Mounts:
      /usr/share/elasticsearch/config/elasticsearch.yml from elasticsearch-configfile (rw,path="elasticsearch.yml")
      /usr/share/elasticsearch/data from elastic-pvc (rw,path="elastic-data")
      /var/run/secrets/kubernetes.io/serviceaccount from kube-api-access-p7f8t (ro)
Conditions:
  Type              Status
  Initialized       True
  Ready             False
  ContainersReady   False
  PodScheduled      True
Volumes:
  elastic-pvc:
    Type:       PersistentVolumeClaim (a reference to a PersistentVolumeClaim in the same namespace)
    ClaimName:  elastic-pvc-elasticsearch-0
    ReadOnly:   false
  elasticsearch-configfile:
    Type:      ConfigMap (a volume populated by a ConfigMap)
    Name:      elasticsearch-config
    Optional:  false
  kube-api-access-p7f8t:
    Type:                    Projected (a volume that contains injected data from multiple sources)
    TokenExpirationSeconds:  3607
    ConfigMapName:           kube-root-ca.crt
    ConfigMapOptional:       <nil>
    DownwardAPI:             true
QoS Class:                   Guaranteed
Node-Selectors:              <none>
Tolerations:                 node.kubernetes.io/not-ready:NoExecute op=Exists for 300s
                             node.kubernetes.io/unreachable:NoExecute op=Exists for 300s
Events:
  Type     Reason                  Age                    From                                   Message
  ----     ------                  ----                   ----                                   -------
  Normal   TriggeredScaleUp        3m43s                  cluster-autoscaler                     pod triggered scale-up: [{https://content.googleapis.com/compute/v1/projects/lexical-pattern-305514/zones/us-east1-c/instanceGroups/gk3-autopilot-cluster-1-nap-1535p6rr-5687b4d4-grp 0->1 (max: 1000)}]
  Warning  FailedScheduling        3m34s (x3 over 4m39s)  gke.io/optimize-utilization-scheduler  0/2 nodes are available: 2 Insufficient cpu, 2 Insufficient memory.
  Warning  FailedScheduling        3m2s (x2 over 3m2s)    gke.io/optimize-utilization-scheduler  0/3 nodes are available: 1 Insufficient ephemeral-storage, 2 Insufficient cpu, 2 Insufficient memory.
  Warning  FailedScheduling        2m42s (x3 over 2m54s)  gke.io/optimize-utilization-scheduler  0/3 nodes are available: 1 node(s) had taint {node.kubernetes.io/not-ready: }, that the pod didn't tolerate, 2 Insufficient cpu, 2 Insufficient memory.
  Normal   Scheduled               2m32s                  gke.io/optimize-utilization-scheduler  Successfully assigned default/elasticsearch-0 to gk3-autopilot-cluster-1-nap-1535p6rr-5687b4d4-2w8t
  Normal   SuccessfulAttachVolume  2m17s                  attachdetach-controller                AttachVolume.Attach succeeded for volume "pvc-d9ab9683-a408-421f-96f3-dd4eba1b871d"
  Normal   Pulling                 2m13s                  kubelet                                Pulling image "busybox"
  Normal   Pulled                  2m13s                  kubelet                                Successfully pulled image "busybox"
  Normal   Created                 2m13s                  kubelet                                Created container increase-vm-max-map
  Normal   Started                 2m12s                  kubelet                                Started container increase-vm-max-map
  Normal   Pulling                 2m12s                  kubelet                                Pulling image "elasticsearch:5.0.0"
  Normal   Pulled                  2m4s                   kubelet                                Successfully pulled image "elasticsearch:5.0.0"
  Normal   Created                 27s (x4 over 2m1s)     kubelet                                Created container elasticsearch
  Normal   Started                 27s (x4 over 2m1s)     kubelet                                Started container elasticsearch
  Normal   Pulled                  27s (x3 over 103s)     kubelet                                Container image "elasticsearch:5.0.0" already present on machine
  Warning  BackOff                 10s (x4 over 86s)      kubelet                                Back-off restarting failed container

Here's the statefulset of elasticsearch yaml resource.
apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: elasticsearch
spec:
  selector:
    matchLabels:
      app: elasticsearch
  serviceName: "elasticsearch"
  replicas: 1
  updateStrategy:
    type: RollingUpdate
  template:
    metadata:
      labels:
        app: elasticsearch
    spec:
      containers:
      - name: elasticsearch
        image: elasticsearch:5.0.0
        resources:
          limits:
            memory: "4000Mi"
            cpu: 1000m
          requests:
            memory: "3000Mi"
            cpu: 600m
        imagePullPolicy: IfNotPresent
        envFrom:
          - configMapRef:
              name: fx-elastic-config
        ports:
        - containerPort: 9200
          name: http-port
        - containerPort: 9300
          name: transport
        volumeMounts:
        - name: elastic-pvc
          mountPath: /usr/share/elasticsearch/data
          subPath: elastic-data
        - mountPath: "/usr/share/elasticsearch/config/elasticsearch.yml"
          subPath: elasticsearch.yml
          name: elasticsearch-configfile

      volumes:
        - name: elasticsearch-configfile
          configMap:
            name: elasticsearch-config

      initContainers:
      - name: fix-permissions
        image: busybox
        command: ["sh", "-c", "chown -R 1000:1000 /usr/share/elasticsearch/data"]
        securityContext:
          privileged: true
        volumeMounts:
        - name: elastic-data
          mountPath: /usr/share/elasticsearch/data
      - name: increase-vm-max-map
        image: busybox
        imagePullPolicy: IfNotPresent
        command: ['sh', '-c', 'sysctl', '-w', 'vm.max_map_count=262144']
        command: ["sh", "-c", "echo", "vm.max_map_count=262144", ">>", "/etc/sysctl.conf"]
        command: ["sh", "-c", "sysctl", "-p"]
        securityContext:
          privileged: false

      - name: increase-fd-ulimit
        image: busybox
        command: ['sh', '-c', 'ulimit -n 65536']
        securityContext:
          privileged: false

  volumeClaimTemplates:
  - metadata:
      name: elastic-pvc
#      annotations:
#        ...
    spec:
      accessModes: [ "ReadWriteOnce" ]
      storageClassName: "premium-rwo"
      resources:
        requests:
          storage: 10Gi
---

apiVersion: v1
kind: Service
metadata:
  name: elasticsearch
  labels:
    app: elasticsearch
spec:
  type: ClusterIP
  selector:
   app: elasticsearch
  ports:
    - port: 9200
      targetPort: 9200
      name: elasticsearch-http
    - port: 9300
      targetPort: 9300

Same elasticsearch statefulset k8s resource file, when deployed in GKE standard mode, runs successfully without any error.
Can some please tell me why this kind of behaviour and how to fix this issue?

Hello, sorry you're encountering this friction.
What are the CPU and memory specs of your cluster? How many nodes? The elasticsearch pod events suggest your cluster doesn't have enough CPU and memory
 Normal   TriggeredScaleUp        3m43s                  cluster-autoscaler                     pod triggered scale-up: [{https://content.googleapis.com/compute/v1/projects/lexical-pattern-305514/zones/us-east1-c/instanceGroups/gk3-autopilot-cluster-1-nap-1535p6rr-5687b4d4-grp 0->1 (max: 1000)}]
  Warning  FailedScheduling        3m34s (x3 over 4m39s)  gke.io/optimize-utilization-scheduler  0/2 nodes are available: 2 Insufficient cpu, 2 Insufficient memory.
  Warning  FailedScheduling        3m2s (x2 over 3m2s)    gke.io/optimize-utilization-scheduler  0/3 nodes are available: 1 Insufficient ephemeral-storage, 2 Insufficient cpu, 2 Insufficient memory.
  Warning  FailedScheduling        2m42s (x3 over 2m54s)  gke.io/optimize-utilization-scheduler  0/3 nodes are available: 1 node(s) had taint {node.kubernetes.io/not-ready: }, that the pod didn't tolerate, 2 Insufficient cpu, 2 Insufficient memory.

It seems like this happened despite a cluster scale-up.
I recommend looking at the Autopilot documentation, and the various constraints of an autopilot cluster - for instance the resource section. Also, I notice that your pods are privileged, and this isn't allowed in autopilot.

Hi there,
For elasticsearch container/pod to be deployed and run successfully a
setting "sysctl -w vm.max_map_count=262144" needs to be added/passed in any
VM and this setting in k8s is passed through init containers with the
privileged value under security-context set as true(which is not allowed in
GKE-autopilot mode).
Below is the init-containers specs(See attached file for full specs)
  initContainers:
  - name: init-sysctl
    image: busybox:1.27.2
    imagePullPolicy: IfNotPresent
    command:
    - sh
    - -c
    - sysctl
    - -w
    - vm.max_map_count=262144
    securityContext:
      privileged: true

If I  set privileged value under securityContext as false, the attached
file spec is successfully passing all hurdles except that successfully
deployed pod logs throw an error "max virtual memory areas vm.max_map_count
[65530] is too low, increase to at least [262144]", which somehow didn't
passed successfully with the privileged value set as false and
elasticsearch pod remains in error/crashloop-backoff state.
Standard mode doesn't give any errors and the attached file k8s resource
gets deployed successfully in any of the nodes.
So how to pass this setting "sysctl -w vm.max_map_count=262144" through the
attached k8s resource file's init containers section or anyway in
GKE-AUTOPILOT mode.
Awaiting a quick response in this scenario.
Regards,
Imran
On Wed, Mar 17, 2021 at 11:29 PM askmeegs @.***> wrote:

Hello, sorry you're encountering this friction.
What are the CPU and memory specs of your cluster? How many nodes? The
elasticsearch pod events suggest your cluster doesn't have enough CPU and
memory
Normal   TriggeredScaleUp        3m43s                  cluster-autoscaler                     pod triggered scale-up: [{https://content.googleapis.com/compute/v1/projects/lexical-pattern-305514/zones/us-east1-c/instanceGroups/gk3-autopilot-cluster-1-nap-1535p6rr-5687b4d4-grp 0->1 (max: 1000)}]
Warning  FailedScheduling        3m34s (x3 over 4m39s)  gke.io/optimize-utilization-scheduler  0/2 nodes are available: 2 Insufficient cpu, 2 Insufficient memory.
Warning  FailedScheduling        3m2s (x2 over 3m2s)    gke.io/optimize-utilization-scheduler  0/3 nodes are available: 1 Insufficient ephemeral-storage, 2 Insufficient cpu, 2 Insufficient memory.
Warning  FailedScheduling        2m42s (x3 over 2m54s)  gke.io/optimize-utilization-scheduler  0/3 nodes are available: 1 node(s) had taint {node.kubernetes.io/not-ready: }, that the pod didn't tolerate, 2 Insufficient cpu, 2 Insufficient memory.
It seems like this happened despite a cluster scale-up.
I recommend looking at the Autopilot documentation
https://cloud.google.com/kubernetes-engine/docs/concepts/autopilot-overview,
and the various constraints of an autopilot cluster - for instance the resource
section
https://cloud.google.com/kubernetes-engine/docs/concepts/autopilot-overview#range_ratio.
Also, I notice that your pods are privileged, and this isn't allowed in
autopilot
https://cloud.google.com/kubernetes-engine/docs/concepts/autopilot-overview#no_privileged_pods
.
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access to GKE-Autopilot managed nodes is not allowed, hence you cannot change node-level settings like vm.max_map_count

Hi there,
thanks for the response, then what is the alternative to deploy
elasticsearch pod in GKE auto-pilot mode without passing vm.max_map_count
setting.
What approach you people suggest as elasticsearch one of the main
components/service of our product, we definitely need this service.
Could you please look into this issue?
Regards
On Thu, Mar 25, 2021 at 4:36 AM Viacheslav Vasilyev <
@.***> wrote:

access to GKE-Autopilot managed nodes is not allowed, hence you cannot
change node-level settings like vm.max_map_count
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There is no way to run it with GKE-Autopilot, better to raise this question to GCP support team

Since GKE manages the nodes for you for Autopilot clusters, you cannot alter the nodes.

ref. https://cloud.google.com/kubernetes-engine/docs/concepts/autopilot-overview#no_changes_to_nodes
Probably standard GKE with customer-managed node pools may help you


Implemented catching sliders feature

As requested here: http://www.qlcplus.org/forum/viewtopic.php?f=18&t=10814&p=46597#p46597
It would be great if sliders could be "caught" by external controls, if they have no motor faders.
I tried to implement this. It depends on if there is a feedback patched to the universe - if not, the new behavior is applied.
To catch the slider, simply move the external control to the current level of the slider and the slider will follow your external control as soon as you reached a certain area around the current level with your external control.
There is one drawback: If you move very fast across the current value, the slider might not be caught, but I wouldn't consider this is a big problem.

Works well with a BCF 2000.
With the last commit, drawback when moving fast across the value is resolved.

Hi,
I was again around qlc and noticed that this PR has not been merged yet. Is there any problem here? I would really appreciate this function...
thanks all

Since someone has again requested this feature here I would like to dig this up. I think there are a lot of users who would be happy to see that feature (at least from 4 I know).
I'm happy to change the PR to resolve conflicts or other issues if you are willing to merge.

@siegmund42  Implemented my way: 29ec50d51fca1cec6c9a978ac587c2670593d090
It has less impact than your patch. Please check if everything is OK.
I'll leave this open for discussion until the feature is OK.

Thanks for the repsonse! I replied in the forum thread, there may be some issues left.

@siegmund42 thanks for the loopback example
I think I've fixed the remaining cases here 3e556d0fc116bb60170926918c067c2c4f22773e
The problem was the 'surpassing' case (for fast values change) that did not consider page switch (show/hide) and disable state.
Please check if everything is fine now, thanks

Thank you for fixing! Seems to work fine now - closing.
Thanks again, I'm sure there will be lots of users who are appreciating this!


chore: Update devcontainer.json to start Jupyter Lab

With the frequent time outs on jupyterlab we should reconsider this tighter coupling until jupyterlab is out of beta in codespaces.


Add Data and Error generics to pagesResponseInterface

I noticed pageSWRs in the pagesResponseInterface type was typed with <any, any>. I fixed this with the Data and Error generics.

Thanks @Kerumen -- included in this smoke-test package: https://www.npmjs.com/package/@neolefty/swr


I renamed the vscose-test dependency to @vscode/test-electron

I changed the name of vscose-test dependency to @vscode/test-electron in package.json
Closes #126

So it looks like the CI is failing because package-lock.json wasn't updated. If you could run npm i and commit the result that should fix the issue.


Feature: Streaming Say verb

Is there a way to add a Streaming Say verb that will work like config with bargein for listening but for sending TTS?

I dont understand what you are asking for.

I'll clarify, I'd like to be able to stream text to an always open SAY verb.
It's like the inverse of sticky bargein listening to the user talk and if they talk it hits an actionHook with event speechDetected and streams the text.
I'd like to be able to stream the text response I receive from an LLM Agent stream so it can speak faster.
Currently I created a FIFO queue and after a few words I send them off but there is a hiccup and sometimes the audio gets cut off. I'm not sure why, I've logged it and there is nothing that should be interrupting the last say verb but it gets cut off every now and then.

we have no plans for this, the the upcoming bidirectional audio streaming support in listen verb may do what you want


How to get short[] samples to byte[]

Hi
I seem to be missing something here. I have signed up for the PluraSight course and followed many examples out there on the web but keep running into the same issue.
I have an array of shorts. Each int16 value is an audio sample. The array contains left channel and then right channel. So far so good.
However, bufferedwaveprovider only takes a byte[] array. All the examples in the Plurasight course as well as on line show how to convert from a Byte[] array to a short or float and so on. This seems useless to me when the classes in nAudio all seem to take a byte[] array. So somehow I need to take this short[] array and get it into a byte[] array for naudio.
So why are the examples the reverse?
Can someone please show me how to deal with getting my short[] data into the bufferedwaveprovider?
Thanks

The WaveBuffer class can help you here. I wrote about it here

Hi Mark,
I tried to do this but have had little luck.  This is part of a larger issue here:
https://stackoverflow.com/questions/74020442/naudio-outputting-an-audio-stream-at-high-sample-rate-results-in-dropped-and-ch
Can you please help out with this?  I subscribed to Plurasight but have not found a way.
Thanks


JavaScript

#JavaScript
User story
As a boot camp student
I want the prework notes to be structured on a webpage
So that I can easily find and read the information
Acceptance Criteria
GIVEN a Prework Study Guide website
WEHN I view the study guide
Then I can see the four topics I learned listed along with a suggestion on what I should study first

Will need to study a lot more about JS


.NET 8 Support for MaxiCode / UPS Barcodes

Hey there,
first of all many thanks for this repository - we saved a lot of time using it.
As time goes on, we are preparing to upgrade to .NET 8. However, as we serve UPS labels I stumbled upon the System.Drawing dependency using the Zint lib for Maxicodes.
I had a look into the code and recognized a strong dependency to the Graphics object in the MaxiCodeElementDrawer.cs, assuming this would be a breaking change for .NET 8.
Are there any plans / workarounds to continue viewing MaxiCode labels using .NET 8? Afaik the libgdi+ dependency won't be available for .NET 8 projects, so I was wondering if and how this project will handle future implementations.
Sorry if I'm mixing things up, I'm quite new to this topic.

System.Drawing dependency using the Zint lib for Maxicodes.
That is unfortunate. We may need to find an alternative moving forward.


update comment

Test build
@anhou

the docs build failed https://readthedocs.org/projects/rackhd/builds/6384006/
a test PR for it