Let ConfigurationCacheReport use coreAndPluginsScope loader for storing json

This fixes CNFE for Groovy's FastStringServiceFactory
See https://gradle-community.slack.com/archives/C013WEPGQF9/p1624521157046300
Before the fix: https://ge.gradle.org/s/f3iacdlsazub6/tests/:configCacheFunctionalTest/org.graalvm.buildtools.gradle.JavaApplicationWithAgentFunctionalTest/agent is passed and generates resources files on Gradle 7.0.2 with JUnit Platform 5.7.2?anchor=e30&focused-exception-line=0-167&top-execution=1
After the fix: https://ge.gradle.org/s/kobh57ffdh34e/tests/:configCacheFunctionalTest/org.graalvm.buildtools.gradle.JavaApplicationWithAgentFunctionalTest/agent is passed and generates resources files on Gradle 7.0.2 with JUnit Platform 5.7.2?anchor=e30&focused-exception-line=0-78&top-execution=1

@bot-gradle help

Currently I support the following commands:

@bot-gradle test {BuildStage} to trigger a build

e.g. @bot-gradle test SanityCheck plz
SanityCheck/CompileAll/QuickFeedbackLinux/QuickFeedback/ReadyForMerge/ReadyForNightly/ReadyForRelease are supported
test this means test ReadyForMerge
test and merge to trigger a pre-tested commit build
cancel to cancel a running pre-tested commit build or remove it from queue
SanityCheck can be abbreviated as SC, ReadyForMerge as RFM, etc.
Specific builds:

AST: AllSmokeTestsReadyForMerge
AFT: AllFunctionalTestsReadyForMerge
ASB: AllSpecificBuildsReadyForMerge
ACC: AllConfigCacheTestsReadyForMerge
ACT: AllCrossVersionTestsReadyForNightly
APTN: AllPerformanceTestsReadyForNightly
AFTN: AllFunctionalTestsReadyForNightly
ACTR: AllCrossVersionTestsReadyForRelease
AFTR: AllFunctionalTestsReadyForRelease

@bot-gradle help to display this message
@bot-gradle clean to clear the conversation history

@bot-gradle test ACC

OK, I've already triggered AllConfigCacheTestsReadyForMerge build for you.

Superseded by https://github.com/gradle/gradle/pull/17538

I'm assuming the classloader is no longer needed since we're not encoding objects via Groovy anymore.

I was wrong, the classloader is still needed :/

@bot-gradle test ACC

OK, I've already triggered AllConfigCacheTestsReadyForMerge build for you.

@bot-gradle test this

OK, I've already triggered ReadyForMerge build for you.

@bot-gradle test this

OK, I've already triggered ReadyForMerge build for you.

Superseded by https://github.com/gradle/gradle/pull/17550


My bots API for price prediction bots

Repo for other bots for both stats on landing page and bot details on mybots page https://github.com/VolumeFi/bot-info-api

[ ] Mybots api
There are 2 bots like Current active bot info and previous days bot
{
bot: 'CRV_price_prediction' , 'ETH_price_prediction', 'BTC_price_prediction'
dex_name: 'curve',
epoch_id,
competition_start,
competition_end,
coin_info,
coin_info1,
coin_info2,
prediction_price,
current_price,
network_name: 'ARBITRUM',
chainId: '42161',
old: '0',
contract: prediction bot contract Address,
token: token contract address,
denominator: eth-> 100, btc-> 1, crv->10**6,
fixed: eth, btc->0, crv->3,
}
[ ] stats api

[ ] number of bots
[ ] total winnings

We will pause on this for now.


Strange server connection issue

Whenever I connect to my server, when it has a recipe file, my client errors with this as the only output I can find. If I remove the recipes in the file I can connect with no issues.
[21:27:06] [main/INFO]: Connecting to localhost, 25565
[21:27:08] [Netty Client IO #1/INFO]: Server protocol version 2
[21:27:08] [Netty Client IO #1/INFO]: Attempting connection with missing mods [ctgui] at SERVER
[21:27:08] [Netty Client IO #1/INFO]: Injecting existing registry data into this client instance
[21:27:08] [Netty Client IO #1/INFO]: Registry IRecipe: Found a missing id from the world crafttweaker:ct_shapeless-1897185629
[21:27:08] [Netty Client IO #1/INFO]: Registry IRecipe: Found a missing id from the world crafttweaker:ct_shapeless1065180319
[21:27:08] [Netty Client IO #1/ERROR]: Unidentified mapping from registry minecraft:recipes
[21:27:08] [Netty Client IO #1/ERROR]:     crafttweaker:ct_shapeless-1897185629: 449
[21:27:08] [Netty Client IO #1/ERROR]:     crafttweaker:ct_shapeless1065180319: 448
[21:27:08] [Netty Client IO #1/ERROR]: Network Disconnect: Fatally missing blocks and items
[21:27:08] [Netty Client IO #1/FATAL]: Failed to connect to server: there are 4 missing blocks and items

Use the issue template.


Not using complete data of sample

Actual Behaviour
We aren't displaying all the information we have in the sample JSON files.
Expected Behaviour
The organiser information could be used in 2 ways:-

Adding the description in the splash screen along with logo.

Creating another fragment for organiser description. So now, we will have 2 "about" fragments- about event and about organiser.

Would you like to work on the issue?
Yes.
Target Milestone to solve the issue
Till which milestone will you be fixing the issue?
https://github.com/fossasia/open-event-android/milestone/26

@mariobehling @mananwason @the-dagger what do you think about it?

@mahikaw Using a single fragment is a good choice.
No need to have 2 separate fragments for event and organiser.
I was thinking of adding the bookmarks to the first fragment as well since that's what user cares most about.
So please think along these lines.

Sure @the-dagger 👍

@mahikaw also @shreyasnbhat is working on something similar in #1499
Might want to take a look at it.

I have done the work. You could check put the screens I posted a while back in the issue itself.

@the-dagger What if there are no bookmarks. This will be the case when the app is opened for the first time of course.

Bookmarks will be populated in a recycler view on the top whose visibility
will be marked as GONE in case of no bookmarks.

Yeah, I figured. My bad. I guess @shreyasnbhat is working on that. Meanwhile, I will work about the event and organiser description.

@mahikaw Please update regarding the timeline. There are many bumps from one milestone to another

@mahikaw @iamareebjamal  I believe this was fixed with the new HOME screen that we have right?

@the-dagger Yes. Furthermore, I have broken the missing info in smaller issues, so this can be closed


CMOS-100: Caching images across jobs

Tweaks to handle only building once per workflow and sharing the container across jobs.
Updated to also run 7.0.2 tests.

@markspolakovs we probably should fix the linting errors - currently they just get output for ansible but ideally we resolve them once we have a good set of rules to use. make lint will do it as well or just use the tools/ansible-lint.sh script directly from here.

@markspolakovs we probably should fix the linting errors - currently they just get output for ansible but ideally we resolve them once we have a good set of rules to use. make lint will do it as well or just use the tools/ansible-lint.sh script directly from here.

Agreed, I skimmed them and many look legit - I'll go through them properly tomorrow.

This all looks good now, most of the changes were automated using the pre-commit framework with the included config file. I've added a comment to the makefile lint target to link out but basically:

Install pre-commit framework: https://pre-commit.com/#install
Run config: pre-commit run --all-files


Adopt semantic highlighting

Since 1.43, VSCode themes can take advantage of semantic highlighting.
Every theme controls whether semantic tokens are enabled. So far, only built-in themes have it enabled and I filed this issue to ask you to opt-in for the Noctis themes as well.
Adoption is easy and there are new cool styling possibilities.
To turn on semantic highlighting for a theme, all you have to do is put
"semanticHighlighting": true
in the theme's definition file.
There's a good chance that no further change to the theme is needed (thanks to a default mapping from semantic tokens to TextMate scopes (if not, I'd be interested to know, so I can improve the defaults further)).
But, more interestingly, themes can tune and go wild by defining new styling rules against the semantic tokens:
"semanticTokenColors": {
    "variable.readonly": "#ff0000",
    "parameter": { "fontStyle": "underline" },
    "*.declaration:java": { "fontStyle": "bold" }
}

Check out our Semantic Highlighting Wiki and the Semantic Highlighting Guide for more details and feel free to ping me in this issue if I can help.
Thanks for the great work and looking forward to semantic highlighting in your theme.

I definitely plan to implement it. Let me have a look and I'll get to you.
Thank you for all the info mate.
Cheers!

Here is TextMate version:

With "semanticHighlighting": true

When Developer: Inspect Editor Tokens and Scopes command is activated:

From what I can see I would need to redo most of the token color definitions.
However, it seems that other than enabling semantic highlighting, none of the built in themes has any specific semantic token definition.They are still using TextMate theme rules. E.g. https://github.com/Microsoft/vscode/blob/master/extensions/theme-kimbie-dark/themes/kimbie-dark-color-theme.json
Can you please point out a theme that adopted and leverages the power of semantic tokens, as I would like to use it as an example?

We don't have any such example yet. So far I focused on improving the default mappings (semantic tokens -> TextMate scope) so that turning on the semantic property flag works smoothly.
Can you let me know which color change in your example you don't like? In theory they should be for the better :-)

I like the new standard semantic tokens and token modifiers as it makes higligting more consistent,
I'm quite happy with the changes I can make using "semanticTokenColors": {}.
Initially I was bummed because I coudn't target support.class.consoleanymore, but I think it's for the best as the reading code becomes less distracting.
There is only one other thing I would've liked to be able to target and that is meta.object-literal.key. It would be fantastic if there was a way to do it with the new rules.
Kudos for the excelent work.

@liviuschera Thanks for the feedback. I have https://github.com/aeschli/typescript-vscode-sh-plugin/issues/12 for meta.object-literal.key.

Export, Import and Return and some words are in italic. It's so sad :(

Maybe, this isn't quite the best place for it, but a suggestion I have for semantic highlighting for the Noctis themes is that rather than have property accesses be in italic, have references be in italic.
At least for Rust code, I have no trouble telling just from vanilla syntax when I'm accessing a property, but I don't always know if something is a reference until the compiler yells.
I have found adding these to my editor.sematicTokenColorCustomizations in settings helps me out a ton when editing Rust code when I need to know whether something is a reference or not:
            "property": {
                "fontStyle": ""
            },
            "*.reference": {
                "fontStyle": "italic"
            },


Extended Content Model only when requested in the graphQL fields

Question
Hi, I am extending my content model with custom properties, like this tutorial:
https://nikcio.github.io/Nikcio.UHeadless/v3/content/extendexistingpublicaccess/
I was wondering, is there a way to only perform an action if the field was requested in the graphQL fields? For example, to get the public access settings only if it was requested in the graphQL fields.

@PriscilaSS Yes there is. If you make the property a method then it will only be executed if quried. See the Public access example for v5: https://nikcio.github.io/Nikcio.UHeadless/v5/extending/content/#example-custom-content-model-extending-the-existing-content-model
As long as you dont set the value for a property in the constructor but via the get then it will only be created if requested and the same for methods of that makes sense

Hi! That was very helpfull, thank you so much.


chore: improve changes made in #223

there are some improvements to be made for the changes in #223, namely a few changes on the new rpc method tests, feature flags, variable name changes, and improving evm_setNextBlockTimestamp implementation.

At least for now I would prefer to just have two features: "development" and "production".

At least for now I would prefer to just have two features: "development" and "production". A one-to-one replacement of the Environment enum.

Are those features mutually exclusive? The Cargo Book  states that "This should be avoided if at all possible, because it requires coordinating all uses of the package in the dependency graph to cooperate to avoid enabling them together.". Maybe we can have only a "development" feature, and have not(feature = "development") mean production,


refactor Permission classmethods

Summary

Refactor permission generation. The existing way of 0b integers is prone to breaking and is hard to read.
Additionally, adds a missing events classmethod.
Checklist

[ ] If code changes were made, then they have been tested

[x] I have updated the documentation to reflect the changes
[x] I have formatted the code properly by running task lint or pre-commit run --all-files

[ ] This PR fixes an issue
[x] This PR adds something new (e.g. new method or parameters)
[ ] This PR is a breaking change (e.g. methods or parameters removed/renamed)
[ ] This PR is not a code change (e.g. documentation, README, ...)

what does this do exactly?

what does this do exactly?

Overall, makes the code easier to read, as it can now be seen exactly what permissions are being set. The previous style was manually created binary, which is prone to error and needs to be updated when a new permission is added.

what does this do exactly?

Overall, makes the code easier to read, as it can now be seen exactly what permissions are being set. The previous style was manually created binary, which is prone to error and needs to be updated when a new permission is added.

how is it prone to error?

well, you might type an extra one, and you won't notice


Faster git clone

We shouldn't clone the entire git history. Instead we clone only the latest commit. This will make cloning progress more faster.

Thanks!


[Feature Request] accessibility

Existing Component
否
Component Name
/
Description
I have a question,Whether the element UI supports accessibility? if not, how do I do?

Actually Element UI supports a11y. If you found any component which does not support, PR welcome :)


purge: add monitoring group in final cleanup play

This adds the monitoring group in the "final cleanup play" so any cid
files generated are well removed when purging the cluster.
Closes: https://bugzilla.redhat.com/show_bug.cgi?id=1974536
Signed-off-by: Guillaume Abrioux<EMAIL_ADDRESS>

jenkins test centos-container-purge_cluster

jenkins test centos-container-purge


fix: add missing keys in helm chart so the helm installation will not…

… fail

Closes: #1541

I have read the Code of Conduct and I hereby accept the Terms

I have read the CLA Document and I hereby sign the CLA


Fix a reference issue in ClippingPrimitive

Overview
Add a null check in AcquireMaterials to prevent a missing reference issue. Thanks @JakobAnarkyLabs for reporting the bug!
Changes

Fixes: #10626

/azp run


Add config extraCredentials.googleServiceAccountKey

I recorded a video developing this in https://www.youtube.com/watch?v=rNE-XV9RNY0.
I pushed a small schema commit (470611b) after recording the video.

fixes #123

I'll go for a merge so I can trial use of this easier in 2i2c-org/infrastructure.


Stream implementation

Is there no pass through for the stream implementation?

Unfortunately no. Many of the features, like eager loading, would need a completely separate implementation to be used with streaming. Consider this:
Movie
  .query()
  .where('foo', 'bar')
  .eager('[actors, reviews]')
  .stream();

We would need to fetch the related models each time we get a row out of the stream. That would actually be really inefficient compared to the way it is done without streams.
What we could do, is to support the streaming with basic cases, where there is no eager or other special ORM features.
You can always just bypass the objection query builder and do this:
Movie
  .knex()
  .where('foo', 'bar')
  .stream();

but you don't get the row --> model mapping when you do this.
How would you like to use the streaming interface? Would the knex interface with model mapping be enough?

Yea, in my specific case I don't need the eager loading and am pulling a lot of records.  I had done what you suggested and just used the knex function to build the query.
What I did to get back the Model though was I added a method to the model on creation that I could use to create the stream.  The stream returns an instance of the model for each write:
Stream = require 'stream'

_model.createStream = _model.prototype.createStream = (write, end) ->
      stream = new Stream
      stream.writable = true
      stream.write = (buffer) ->
        model = new _self.model
        model.$setDatabaseJson buffer
        write model
      stream.end = (buffer)->
        if arguments.length
          stream.write buffer
        stream.writable = false
        end()
      stream

_model.knex()
    .select()
    .from _model.tableName
    .stream()
    .pipe _model.createStream (myModel) ->
        #doSomething with each model
    , -> #stream complete

I'll probably add a pass through method for the stream at some point. I'll post here when I start working on it. The basic implementation is simple, but I need to make sure the method handles all the cases (throws if there is an eager call, doesn't work with insert, etc.)

I don't think this is going to happen since no one else has wanted this. Closing this now.

I just googled for this, grabbing batches of records is fine, but being able to leverage a stream for a where query would be great.

We too would profit for having the stream() method

I've found myself needing this so worked through a rough implementation of a stream() method on a custom query builder. The implementation is below, hopefully it is useful to somebody.
Firstly, you need to implement a custom query builder. The best way to do this is to use a base model class, this is thoroughly documented on the Objection site.
Now, we can add the following method to the custom query builder (implementation is shown below in TypeScript: strip out the type annotations for plain JS):
/**
 * Stream the query results, calling the passed handler once for each result.
 *
 * @param resultHandler handler which is called for each streamed model instance.
 */
public stream(resultHandler: (result: M) => void | Promise<void>) {
  const modelClass = this.modelClass();
  const { parse: keysToCamelCase } = snakeCaseMappers();  // Make sure to import this from 'objection'

  // Create a custom writable stream to handle each result.
  const out = new Writable({
    // objectMode is needed as we are streaming knex pojo results.
    objectMode: true,
    async write(knexResult, _, next) {
      try {
        // Since we are using the knex API to stream, the results passed to the writable stream are knex-formatted objects.
        // We therefore need to convert these into the respective objection model.
        // Firstly, perform the snake_case -> camelCase conversion for the keys in the knexResult object.
        const objectionPojo = keysToCamelCase(knexResult);

        // Then, pass in this POJO to the respective Objection model.
        const model = modelClass.fromDatabaseJson(objectionPojo);

        // We now have our model which can be passed into the handler.
        await resultHandler(model);

        // Move on to the next result.
        next();
      } catch (e) {
        // There was an error above: abort the stream.
        next(e);
      }
    },
  });

  // We need to drop down to the knex query builder to stream the results.
  // By passing a function handler to the `stream` method, a promise will be returned.
  // The promise will be fulfilled when the stream is complete.
  return this.toKnexQuery().stream((stream) => {
    stream.pipe(out);
  });
}

We are now free to use the following in our calling code (service, etc):
await SomeModel.query().where('someCondition', 'foo').stream((modelInstance) => {
  // Do something with the streamed model instance
});

There are some obvious caveats: only use this for basic select queries, and don't expect things like eager loading to work. But, for simpler use cases, this is working nicely for me.

We would greatly benefit from a stream() implementation as well.
Use Case
We have a web API with a route required to fetch a large number of records to be downloaded as a CSV file. Due to the large number of records (hundreds of thousands), it is not possible to load the query's result into memory before delivering to the client.
We have built a CSV library that adds decorators to the model class to simplify CSV header mapping, eg:
@Sheet()
export class Snack {
  @SheetColumn({ header: 'Name' })
  name!: string;

  @SheetColumn({ header: 'Deliciousness Level' })
  deliciousnessLevel!: number;

  @SheetColumn({ header: 'Date Eaten', dateFormat: ['YYYY-MM-DD'] })
  dateEaten!: Date;
}

This fits perfectly with Objection since we can simply add these decorators to our existing Objection models. Our CSV library supports streaming, so the only missing piece is an Objection implementation of stream().
As a work around we have tried the method above suggested by @fiznool, but came across errors when using joins (joinEager() since eager() is understandably not possible with streaming).
We could try to implement this entirely in Knex, but after manually mapping columns and performing joins with relations, we are basically re-implementing what Objection is doing.
I am interesting in contributing, but first need to learn a lot more about Objection internals, hooks, and strategies to throw for operations that are not possible with streams (like eager and insert as you mention @koskimas).
We have found that streams are becoming a common requirement in this space and hope the above is a compelling use case.

I was hoping this would be implemented as I wanted to use it for responding with a large CSV file on my HTTP server


feat: add pnpm starter

Yikes I do love the contribution but starters are one of the harder things to justify in the repo given they are huge but also every change must now be across all starters.
Wondering what's the best route? Maybe just throw this one in it's own repo, it'll be destined to drift unfortunately. Honestly just documenting the steps for pnpm is super helpful it's hard to see exactly what changed here from the default starter.

Yeah, i do understand that ✌
will close this PR for now.

I've created a template based on the Tamagui starter with PNPM for anyone that is interested:
https://github.com/mate-h/tamagui-base


'start' parameter seems to not working

I want to get the second result of a search without uselessly use my quota with "num" parameter (which using quickly my quota).
So I wanted to use 'start' parameter but it seems to not working, it returns me the same image each time.
What this code is doing ?

Why not using this ?

Can you please share you code where you "uselessly use my quota with "num" parameter"?

I tested with this code :
`from google_images_search import GoogleImagesSearch
gis = GoogleImagesSearch(api, cx)
from PIL import Image
search_params = {
'q': 'test',
'imgColorType': 'trans',
'start' : 1,
'num': 10
}
for i in range(101):
gis.search(search_params=search_params)
print(i)`
The 101th request stops with : "Quota exceeded for quota metric 'Queries' and limit 'Queries per day'
But I was wrong, it seems to NOT exceed quota quicker than with 'num':1, you can forgot this part
However, I can change the 'start' param as I want, I always get the first image

Ok, I see.
That's not how you use it.
start param is used for paging.
Please read Paging section:
https://github.com/arrrlo/Google-Images-Search#paging

Ok, so 'start' param from cse api can't be used, right ?
https://developers.google.com/custom-search/v1/reference/rest/v1/cse/list#body.QUERY_PARAMETERS.start

Yes, not for now.

Ok, thanks for answer


ui.tests (both cypress and wdio) throw errors with "install" or "deploy" phases

The modules at https://github.com/adobe/aem-project-archetype/blob/develop/src/main/archetype/ui.tests.cypress/pom.xml and https://github.com/adobe/aem-project-archetype/blob/develop/src/main/archetype/ui.tests.wdio/pom.xml have default packaging (=jar) but only build a secondary/attached artifact with the maven-archiver-plugin. That leads to issues with more recent versions of maven-install-plugin and maven-deploy-plugin (https://issues.apache.org/jira/browse/MINSTALL-118) failing the build with
The packaging plugin for this project did not assign a main file to the project but it has attachments. Change packaging to 'pom'

The packaging should be pom and also the tar.gz should only be conditionally created (in a profile only active in Cloud Manager), as for local execution with docker it is not used at all.

@dulvac something you could look into?

should only be conditionally created (in a profile only active in Cloud Manager)
@kwin, unfortunately I can't change the behaviour, but I will change the packaging


Add clflush as needed to support concurrent cache-incoherent mounts

clflush needed:
after mkfs, on superblock and log
after log append (on log)
before logplay (on log)
after 'famfs cp'
after 'famfs creat' if the file was initialized.
User or app will be responsible for flushing the cash on any data written by apps other than the famfs cli
Still thinking about how the generalized cases should work. Probably a "famfs flush" command and api call that should flush data as appropriate...

This is done, but not in an x86-specific way. This ticket is done, but https://github.com/cxl-micron-reskit/famfs/issues/8 will get us to a multi-architecture approach.

Done, but #8 will refine this to multi-arch


comparison always false (-Wtype-limits)

Hi !
Just in case you missed it, compiling with gcc with -Wtype-limits produces the following warning:
jwt-cpp/jwt.h: In static member function ‘static std::unique_ptr<bignum_st, void (*)(bignum_st*)> jwt::algorithm::ecdsa::raw2bn(const string&)’:
jwt-cpp/jwt.h:269:15: warning: comparison is always false due to limited range of data type [-Wtype-limits]
     if(raw[0] >= 0x80) {

I don't know if it's relevant in the way computations are done, but maybe you could be interested :)

This has already been pointed out in #10 and is fixed in the current master. And yes I did indeed miss it :)
Please check if the problem is still there if you use the most recent commit.


QSynth evaluation

Hi, I was testing (together with @pgarba) the instruction synthesis of some obfuscated expressions obtained from the QSynth repository. As an example this expression has been converted to the Souper IR and souper-check has been used to synthesise it both with enumerative and component-based synthesis. Both methods quickly converge to the correct candidate (mul %1, %1, obtained with the bit-width reduced synthesis using i8/i16) but it seems they get stuck during the Z3 equivalence phase.
The enumerative synthesis opt file is the following:
; RUN: %souper-check -infer-rhs -souper-enumerative-synthesis -souper-enumerative-synthesis-debug-level=4 %solver %s > %t1
; RUN: %FileCheck %s < %t1
; CHECK: mul %1, %1

%0:i64 = var
%1:i64 = var
%2 = xor %1, -1:i64
%3 = or %0, %2
%4 = shl %3, 1:i64
%5 = add %0, -2:i64
%6 = sub %5, %1
%7 = sub %6, %4
%8 = xor %7, %0
%9 = and %8, %1
%10 = or %8, %1
%11 = mul %10, %9
%12 = and %8, %2
%13 = xor %8, -1:i64
%14 = and %1, %13
%15 = mul %12, %14
%16 = add %11, %15
infer %16

The feeling is that the Z3 equivalence phase takes so long just because proving the matching with the original MBA expression is hard. I noticed that other Souper test files are synthesising the mul instruction and the equivalence check is immediate, hence it seems to be related with the complexity of the obfuscated expression.
Is that a correct guess or something can be done to speedup that phase?

Hello,
It's great that you're looking at QSynth in Souper!
The full-width equivalence proof here is going to be challenging and I don't think we have any great ideas about how to speed it up.
Some not-so-great ideas include:

try a bunch of other solvers
identify the bottleneck and then tweak the Z3 tactics pipeline
Sorry, wish I had a better answer, but we're mainly compiler people who use solvers, as opposed to being actual solver people, and we basically just rely on the solver to just do the right thing.

Thanks for the answer!
I tried to specify other solvers while doing the synthesis with Souper (e.g. stp) but it looks like they are rejected and make the synthesis fail with the ; Failed to infer RHS message. Is this expected behaviour?
As of now the reduced-width equivalence is enough for some testing, but the soundness isn't the same. Considering SMT-Solvers are pretty much black magic to me, as I'm a simple user with no advanced knowledge of the internals, I'll probably try to ask the question to the Z3 GitHub repository.


frontend: Fix doc viewer breaking

With a recent CRA update node related modules are not shipped with CRA anymore. This broke the doc viewer as it was using the buffer module. We already had a patch earlier that added the polyfill but one problem with polyfilling it in a place like index.tsx is that when building the frontend for production, the polyfill is not included. The correct place to polyfill is to include it at the place where it is being used.

fixes #899


Get rid of dev branch

Is your feature request related to a problem? Please describe.
Bot does not have dev version hosted anywhere. All the tests related to updates are done locally on developer's machine. We don't need additional branch for this. In case bot will increase amount of users, we might get this branch back.
Describe the solution you'd like
Remove dev branch.
Describe alternatives you've considered
—
Additional context
—

Branch was deleted.


Failed to watch for joystick connections

I love the JoeyDeVries tutorials, they've helped me understand opengl - I've worked through them in C++ and ported some of them to Vala. So I was happy to see this port.
But when I try this code using cargo run 1_1_1 I get an error from glfw::init:
thread 'main' panicked at 'GLFW Error: Linux: Failed to watch for joystick connections in /dev/input: No such file or directory', /home/darkoverlordofdata/.cargo/registry/src/github.com-1ecc6299db9ec823/glfw-0.23.0/src/lib.rs:392:5

and then my desktop is messed up - I'm unable to close or open any application windows.
They still work - I opened my text editor first and was able to cust and paste the error. But I can't close the text editor, and when I type exit in the console, the window just becomes unresponsive. The only way I can find to clear it up is to reboot,
When I try the original, here: https://github.com/JoeyDeVries/LearnOpenGL/blob/master/src/1.getting_started/1.1.hello_window/hello_window.cpp, it works as expected.
I'm running rustc 1.38.0 (625451e37 2019-09-23) on Debian Buster.

I found there are 2 issues in 1.

The original code calls glfwinit with no params. So I changed the rust code to this:
let mut glfw = glfw::init(glfw::LOG_ERRORS).unwrap();

and the demo program no longer dies.

Other application windows close events are trapped by rust; for example when I click on the close button for my text editor, this demo closes, but the text editor stays open. It seems to me that the event pump in the glfw wrapper is not filtering events to the current application, and captures events for all open applications.

I've been trying to decide between rust and dotnet core 3.0. I would say the decision is made - I'm looking for something that works, not something that frustrates me :) I think the rust ecosystem may not be mature enough for general use.

I found that if I build the project as
cargo run -j 1 1_3_2

Then the problems listed in issue #2 go away.
Apparently cargo or rustc enters a race condition on my machine, causeing some odd side effects.


Link_to helper

There is a way to add class if page is current page?
Like that:
link_to "SomePage", somepage_path, :class => current_page
Now I only can hide or show link if it current or not by
link_to "SomePage", somepage_path, :if => :current

Not built in, but you should have all the tools necessary to craft such a helper using request.path. Something like:
helpers do
  def magic_link_to(link, url, opts={})
    if request.path == link
      opts[:class] = "current"
    end
    link_to(link, url, opts)
  end
end

Here's a lazy implementation I made on the fly:
  def current_page?(page)
    current = current_resource.url.gsub('/', ' ').strip
    target = page.gsub('/', ' ').strip

    current == target
  end

I'll try to propose the addition to the standard helpers in a PR when I get the time.

Here’s a new gem for marking up a current link with aria-current (which you can then use to style off of): https://github.com/thoughtbot/middleman-aria_current


Increase minimum height of single rows in case space is available

The height of the rows is so small that it's hardly possible to see labels. Let's use the same minimum height as for the string column rows.

@bikramkawan, this should be an easy fix, right?

@katush and we discussed yesterday related to this. She should have probably done this I think. @katush Any update ?

This seems to be addressed in the https://github.com/Caleydo/mothertable/tree/user_selected_visses_%23238 branch.

@katush, can you extract the change that fixes this issue from the https://github.com/Caleydo/mothertable/tree/user_selected_visses_%23238 branch and file a PR that just fixes the row height issue?

@mstreit Could you please check again, if this is fixed. I'm not sure.

should be, though the name of this issue is not precise - at least I think that the goal was to increase maximum height of rows - so they can still shrink, but if they have space, they will expand. That is what I have done

Yes, it was about the max height.


Improve error handling on deletion

https://github.com/abapGit/abapGit/blob/5e629f19a7243140e9d7a0eb039a411c26e28f83/src/objects/zcl_abapgit_objects.clas.abap#L521-L532
The "report the error later" approach doesn't really work all that well when multiple errors occur, especially follow up errors. I ran into this in this scenario:

Delete SHI3 -> reports error, structure is still used
Delete SHI5 -> reports error via popup, SHI3 structure still exists

You cannot see why the SHI3 structure failed to be deleted. I suggest collecting the errors in a log.

Check if https://github.com/abapGit/abapGit/pull/4198 works for showing the log

The log does show up! Not the message I found last time in the debugger but I guess the SHI3 object now was already partly deleted. I think generally SHI3 does not seem to support GHIER very well yet.

The SHI* types should go into https://github.com/abapGit/abapGit/blob/master/src/zcl_abapgit_dependencies.clas.abap (there’s a case) in the right order


Fix for python3.10

Fix for error:
Traceback (most recent call last):
  File "/usr/lib/python3.10/threading.py", line 1016, in _bootstrap_inner
    self.run()
  File "/usr/lib/python3.10/threading.py", line 953, in run
    self._target(*self._args, **self._kwargs)
  File "/usr/local/lib/python3.10/dist-packages/pytask_io/pytask_io.py", line 189, in _run_event_loop
    self._worker_queue = asyncio.Queue(loop=self.main_loop)
  File "/usr/lib/python3.10/asyncio/queues.py", line 34, in __init__
    super().__init__(loop=loop)
  File "/usr/lib/python3.10/asyncio/mixins.py", line 17, in __init__
    raise TypeError(
TypeError: As of 3.10, the *loop* parameter was removed from Queue() since it is no longer necessary

Thanks @creatorrr


Too many characters prompt not showing up

For some reason the too many characters prompt is being skipped. This isn't a major issue but it is something I am looking into fixing. Must be something to do with the loop with how it's implemented.

This should be fixed now. :)


Automated cherry pick of #1503: fix cloud-init lock root login issue

Cherry pick of #1503 on release/2.11.0.
#1503: fix cloud-init lock root login issue

Codecov Report

:exclamation: No coverage uploaded for pull request base (release/2.11.0@e5b9122). Click here to learn what that means.
The diff coverage is 100%.

@@               Coverage Diff                @@
##             release/2.11.0   #1504   +/-   ##
================================================
  Coverage                  ?   7.68%
================================================
  Files                     ?     411
  Lines                     ?   62834
  Branches                  ?       0
================================================
  Hits                      ?    4828
  Misses                    ?   57596
  Partials                  ?     410

Flag
Coverage Δ

#aFlag
7.68% <100%> (?)

Impacted Files
Coverage Δ

pkg/util/cloudinit/cloudconfig.go
57.62% <100%> (ø)

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update e5b9122...aca4edb. Read the comment docs.

/lgtm
/approve


hubstaff: 1.3.0 → 1.3.1

Motivation for this change
Version bump.
Things done

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

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

[x] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[x] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[x] Fits CONTRIBUTING.md.

@GrahamcOfBorg build hubstaff

No attempt on aarch64-linux
The following builds were skipped because they don't evaluate on aarch64-linux: hubstaff
No log is available.

No attempt on x86_64-darwin
The following builds were skipped because they don't evaluate on x86_64-darwin: hubstaff
No log is available.

No attempt on x86_64-linux
The following builds were skipped because they don't evaluate on x86_64-linux: hubstaff
No log is available.

Thank you very much!


(rewrite) No more async recursion!

Because of the long list of traits and structs involved in handlers, it should be possible to make the handler call not borrow anything, allowing for async recursion to not be needed for nested handler calls

async recursion successfully removed!


does this.transform() make calls to the db?

It seems this.transform() is retrieving more data than is sent by an update/insert call. So is it making an additional read to the database to get it?
And if I don't use transform without a parameter, will it make that read anyway, i.e. if I do instead: this.transform(modifier.$set) as an optimization?
Or am I missing something about this whole thing for why the server already has the entire document. I'm operating under the assumption it doesn't have the entire document. Rather the client sends the minimum # fields I'd like to change to the server, and the server does the same passing that on to Mongo, without ever having full knowledge of the document. So I guess the question is: is this.transform() lazy?

this.transform() don't make calls to the db, but there where cases when unnecessary calls to fetch documents where made even when no hooks were added.
This should be in the next release.


GTK apps run from emacs daemon do not have KDE style

Issue description
On my KDE desktop, I configured a dark theme for GTK apps. I also run emacs daemon by using the services.emacs.enable = true; option in configuration.nix, and then connects to it with emacseditor. However, it appears that if I run okular from emacs, using either M-! okular, M-x shell <RET> okular, or from a LaTeX mode, okular has an ugly theme. However, if I run it from a non-daemon emacs instance, it works great, so I guess that the emacs system service does not configure properly the environment variables for KDE.
Technical details

system: "x86_64-linux"
host os: Linux 4.14.75, NixOS, 19.03pre155123.32bcd72bf28 (Koi)
multi-user?: yes
sandbox: yes
version: nix-env (Nix) 2.1.3
channels(leo): ""
channels(root): "nixos-19.03pre155123.32bcd72bf28"
nixpkgs: /nix/var/nix/profiles/per-user/root/channels/nixos

This behaviors would be hard to change without duplicating KDE environment setting in emacs systemd user service. Since plasma5 NixOS module does almost none of that environment magic I imagine most of it is done by Plasma itself.
Which means that if you want it, you would have to either "reverse-engineer" those environment computations and add them to emacs module (which, I imagine, would be very ugly; also, you would have to repeat that each time you change anything in KDE UI settings), or you can just start emacs --daemon from under KDE session instead of running it from systemd.
I suggest doing the latter and closing this.

Makes sense, thank you for your comment.


Create docker-image.yml

Just an example of github action to automatically build your docker image!
You can see the whole build log for every push:
https://github.com/venetanji/SketchModeling/actions/runs/11956535756/job/33331516346
Since you're mainly targeting cuda/pytorch, have you considered using a base image with pytorch already installed?
The official pytorch one might already have most of what you need:
https://hub.docker.com/r/pytorch/pytorch/tags
Or you could try the nvidia one, although it is much bigger in size (but comes with more libraries):
https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch

Thank you for the feedback! I was also worried about the size of CUDA image, and what you suggested is truely helpful. I will check those links and continue improving our project.
I was really touched that you took the time to fork our repository and check out our code after class. It means a lot to me and has really motivated me. ❤
Thanks again for all your help and guidance!
------------------ 原始邮件 ------------------
发件人:                                                                                "jiaqi404/SketchModeling"                                                                                @.>;
发送时间: 2024年11月22日(星期五) 凌晨0:07
@.>;
@.***>;
主题: [jiaqi404/SketchModeling] Create docker-image.yml (PR #8)
Just an example of github action to automatically build your docker image!
You can see the whole build log for every push:
https://github.com/venetanji/SketchModeling/actions/runs/11956535756/job/33331516346
Since you're mainly targeting cuda/pytorch, have you considered using a base image with pytorch already installed?
The official pytorch one might already have most of what you need:
https://hub.docker.com/r/pytorch/pytorch/tags
Or you could try the nvidia one, although it is much bigger in size (but comes with more libraries):
https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch
You can view, comment on, or merge this pull request online at:
  https://github.com/jiaqi404/SketchModeling/pull/8
Commit Summary
e798b49  Create docker-image.yml
9ad5b35  Create docker-publish.yml
File Changes
(2 files)
 A     .github/workflows/docker-image.yml     (18)

 A     .github/workflows/docker-publish.yml     (98)

Patch Links:
https://github.com/jiaqi404/SketchModeling/pull/8.patch
https://github.com/jiaqi404/SketchModeling/pull/8.diff
—
Reply to this email directly, view it on GitHub, or unsubscribe.
You are receiving this because you are subscribed to this thread.Message ID: @.***>

Thank you for the feedback! I was also worried about the size of CUDA image, and what you suggested is truely helpful. I will check those links and your pull request later. Thanks again for you took the time to fork our repository and check out our code after class. ❤


Create joachim-leonfellner.json

#WeAreDonet Creator Submission Guidelines

[x] Check all points before submitting the PR.

[x] By submitting this pull request to add my creator card, I verify that I adhere to the #WeAreDotnet creator card submission guidelines.

[x] Make sure to follow our Code of Conduct

[x] We do not accept submissions with the sole intention of promoting a product or company.

[x]  We add you as a creator, not your company.

[x]  The moderator team decides whether we accept or reject a submission.

When Do We Accept Someone's Creator Card Submission?

[x] You must have published at least three post (long form content) since 2022 on any of your channels.

[x] There must be three content pieces in English.

[x] There needs to be more than tweets.

[x] Longer-form article on LinkedIn is good, but a self-hosted blog or one on a well-known platform like Hashnode, medium etc., is better.

[x] Alternatively, you contributed with another form on a platform like YouTube, Twitch, Udemy or Pluralsight. If you have some recorded talks of conferences or anywhere else, that counts too! So in the form of a recorded video or a book.

RSS or Atom Feed

[x] Submit an Atom or RSS URL inside your creator card that belongs to your blog

[x] If you do not submit an RSS or Atom URL. We cannot consider your feed for the upcoming aggregation feature.

Content Guideline

[x] If you have a self-hosted blog, please ensure you have a valid HTTPS certificate.

[x] We host NO malicious or offensive content on the blog (including photos, swearing, etc.)

[x] You must add the full URL to your GitHub profile to your card, so we can assign it to the member account that used the same GitHub account for sign-up.

hi @DeeJayTC 👋
thanks for the review - must have overread that. I fixed in in my latest commit

Hi @DeeJayTC
i have just updated my card with the latest changes from the _creatorTemplate.json and added a .NET specific feed. Do you need anything else from my side?
Thank you 🙂

Nope, thanks!
Ill merge that later today, the split between dotnet and personal feed is not fully rolled out yet but prolly later today


fix xargo doc

by telling rustdoc about the sysroot via RUSTDOCFLAGS
closes #42
this should fix #42 but I can't test this until rust-lang/rust#36586 lands
cc @cbiffle

@homunkulus r+

:pushpin: Commit be99e65 has been approved by japaric

:hourglass: Testing commit be99e65 with merge be99e65...

:sunny: Test successful - status-appveyor
Approved by: japaric
Pushing be99e655335097a389d143e2f53fa3465db2b1f0 to master...


NNAPI/Hexagon

Hi, amazing little library!
Currently, exploring using it as a platform for GPU execution of an RNN-based LLM. One thing though, it will eventually get deployed to mobile, and there, NNAPI is king and provides crazy performance on some platforms.
Is there a chance the library can support NNAPI?
It would also be extremely beneficial, to, maybe, directly access or support Hexagon instead:
https://developer.qualcomm.com/software/hexagon-dsp-sdk
Thanks,
Oleksii

Hi, thank you.
That's sounds nice!
Yes, there is a chance that it will support NNAPI. I am currently setting up an android development environment in order to experiment with NNAPI and Rust.
Regarding Hexagon, I will look into it further.

wip nnapi bindings
https://github.com/elftausend/nnapi

Very cool stuff, @elftausend! In a week or so, I will have an environment to help out with testing (some ARM devices/phones on PostmarketOS/Linux) once you have a chance to have a look at the Hexagon API, as it should work on both Android and Linux (on Qualcomm).
The NNAPI one I can also help testing in a little bit of time, need to finish up some tickets for the current project first, maybe in a week too?
Actually, maybe it can be possible to directly use something like TFLite as a runtime to automatically support NNAPI (Android) + Hexagon (Android + Linux)?

Thanks, this is very helpful as reliable testing appears to be quite difficult.
Are there any tools to automate testing?
(https://github.com/rust-mobile/ndk/blob/master/.github/workflows/rust.yml ?)

Actually, maybe it can be possible to directly use something like TFLite as a runtime to automatically support NNAPI (Android) + Hexagon (Android + Linux)?

I thought about this as well and this should be possible too. However, I think it is beneficial to have an option with only one (pre-installed) dependency (NNAPI).
I added an experimental nnapi device to custos:
(https://github.com/elftausend/custos/blob/nnapi/src/devices/nnapi/nnapi_device.rs)

pub fn run_custos_model() -> custos::Result<String> {
    let device = NnapiDevice::new()?;

    let lhs = Buffer::with(&device, &[1, 2, 3, 4, 5, 6, 7, 8, 9, 11]);
    let rhs = Buffer::with(&device, &[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]);

    // a single operation
    let out = {
        let out = device.retrieve::<i32, Dim1<10>>(lhs.len(), ());
        let activation_idx = device.add_operand(Operand::activation())?;
        let mut model = device.model.borrow_mut();
        model.set_activation_operand_value(activation_idx as i32)?;
        model.add_operation(
            OperationCode::ANEURALNETWORKS_ADD,
            &[lhs.ptr.idx, rhs.ptr.idx, activation_idx],
            &[out.ptr.idx],
        )?;
        out
    };

    // another one
    let out = {
        let out1 = device.retrieve::<i32, Dim1<10>>(lhs.len(), ());
        let activation_idx = device.add_operand(Operand::activation())?;
        let mut model = device.model.borrow_mut();
        model.set_activation_operand_value(activation_idx as i32)?;
        model.add_operation(
            OperationCode::ANEURALNETWORKS_MUL,
            &[out.ptr.idx, rhs.ptr.idx, activation_idx],
            &[out1.ptr.idx],
        )?;
        out1
    };

    let out = device.run(out)?;

    log(
        android_LogPriority::ANDROID_LOG_ERROR,
        &format!("{out:?}"),
    );

    Ok(format!("out: {out:?}"))
}

This works on android.

About the automated testing, it looks like their tests, at first glance, only test the correct layout and type of generated bindings, not their functionality, but I might be wrong!
In the end, they are just setting up an Ubuntu environment 🤷🏻♂
Testing NNAPI might be tricky without a real device connected 24/7 for testing, unless Android provides emulation for it, for testing purposes...
Doesn't look like the emulator supports NNAPI, but maybe the docs just don't say anything? Will probably work if NNAPI has a CPU fallback backend, it certainly does have a GPU one 👀

Yeah, I think they do just that.
I use the emulator provided by Android Studio (as I do not own an Android device with at least Android 8.1). It can run NNAPI and it supports a CPU fallback.

So then maybe we can use this for running NNAPI unit tests?
Also, it has real busy here, will make an update from my side as soon as it comes!


feat!(blob/module): integrate blob service in node

Overview
Based on https://github.com/celestiaorg/celestia-node/pull/2052
TODO: add swamp tests
Checklist

[ ] New and updated code has appropriate documentation
[ ] New and updated code has new and/or updated testing
[ ] Required CI checks are passing
[ ] Visual proof for any user facing features like CLI or documentation updates
[ ] Linked issues closed with keywords

will be reworked


New features and changes

New features

SC plugin manager.

Changes

JAV-486 Changes: Add service-center error codes.

Coverage increased (+0.3%) to 70.431% when pulling 4d981a96ff42a784a1aef8bb7545de23361949a3 on little-cui:master into 4eda42bbeac77421a008def4c8fc7de5951ae04c on ServiceComb:master.

Codecov Report

Merging #163 into master will increase coverage by 0.32%.
The diff coverage is 55.5%.

@@            Coverage Diff             @@
##           master     #163      +/-   ##
==========================================
+ Coverage   65.85%   66.17%   +0.32%
==========================================
  Files          18       18
  Lines        4449     4435      -14
==========================================
+ Hits         2930     2935       +5
+ Misses       1334     1320      -14
+ Partials      185      180       -5

Impacted Files
Coverage Δ

server/service/util/dependency.go
47.93% <100%> (ø)
:arrow_up:

server/service/governservice.go
72.92% <25%> (+1.08%)
:arrow_up:

server/service/services_dependency.go
67.6% <50%> (ø)
:arrow_up:

server/service/microservices.go
72.21% <52.94%> (ø)
:arrow_up:

server/service/rule.go
71.51% <53.33%> (ø)
:arrow_up:

server/service/instances.go
69.72% <57.35%> (+1.65%)
:arrow_up:

server/service/tag.go
71.01% <60%> (ø)
:arrow_up:

server/service/schema.go
71.3% <66.66%> (ø)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 4eda42b...4d981a9. Read the comment docs.

Coverage decreased (-0.04%) to 70.137% when pulling cf7e33554374484625f5d1b42c0f8c65c450abf1 on little-cui:master into 4eda42bbeac77421a008def4c8fc7de5951ae04c on ServiceComb:master.

Coverage increased (+0.3%) to 70.431% when pulling 0fb302e496ffa33c3a4e3da95cd1e5089dfaf9e9 on little-cui:master into 4eda42bbeac77421a008def4c8fc7de5951ae04c on ServiceComb:master.

Coverage increased (+0.2%) to 70.386% when pulling 9484e2bef47a466873c4f5a30954acee080f8bc7 on little-cui:master into 4eda42bbeac77421a008def4c8fc7de5951ae04c on ServiceComb:master.

Coverage increased (+0.3%) to 70.492% when pulling 9484e2bef47a466873c4f5a30954acee080f8bc7 on little-cui:master into 4eda42bbeac77421a008def4c8fc7de5951ae04c on ServiceComb:master.


Can't deploy Karpenter 0.37.0 to EKS 1.30 via EKS blueprints

Description
Observed Behavior:
Installing Karpenter chart fails with: Error: UPGRADE FAILED: context deadline exceeded
Expected Behavior:
deployment
Reproduction Steps (Please include YAML):
Adapted from https://aws-quickstart.github.io/cdk-eks-blueprints/addons/karpenter/#usage to use 0.37.0
package.json
"dependencies": {
    "@aws-quickstart/eks-blueprints": "^1.15.1",
  }

my-blueprints.ts
import * as cdk from "aws-cdk-lib";
import * as blueprints from "@aws-quickstart/eks-blueprints";
import {KubernetesVersion} from "aws-cdk-lib/aws-eks";

const app = new cdk.App();
const region = 'us-east-1';
const clusterName = 'foobar-k8';

const karpenterAddOn = new blueprints.addons.KarpenterAddOn({
    version: '0.37.0',
    nodePoolSpec: {
        labels: {
            type: "karpenter-test"
        },
        annotations: {
            "eks-blueprints/owner": "young"
        },
        taints: [{
            key: "workload",
            value: "test",
            effect: "NoSchedule",
        }],
        requirements: [
            {
                key: 'node.kubernetes.io/instance-type',
                operator: 'In',
                values: [
                    't3.medium', 't4g.medium'
                ]
            },
            { key: 'topology.kubernetes.io/zone', operator: 'In', values: ['us-east-1a','us-east-1b', 'us-east-1c']},
            { key: 'kubernetes.io/arch', operator: 'In', values: ['amd64','arm64']},
            { key: 'karpenter.sh/capacity-type', operator: 'In', values: ['spot']},
        ],
        disruption: {
            consolidationPolicy: "WhenEmpty",
            consolidateAfter: "30s",
            expireAfter: "20m",
            budgets: [{nodes: "10%"}]
        },
    },
    ec2NodeClassSpec: {
        amiFamily: "AL2",
        subnetSelectorTerms: [{ tags: { "karpenter.sh/discovery": `${clusterName}` }}],
        securityGroupSelectorTerms: [{ tags: { "karpenter.sh/discovery": `${clusterName}` }}],
    },
    interruptionHandling: true,
    podIdentity: true, // Recommended, otherwise, set false (as default) to use IRSA
});
const addOns: Array<blueprints.ClusterAddOn> = [
    new blueprints.addons.ArgoCDAddOn(),
    new blueprints.addons.CalicoOperatorAddOn(),
    new blueprints.addons.MetricsServerAddOn(),
    new blueprints.addons.AwsLoadBalancerControllerAddOn(),
    new blueprints.addons.VpcCniAddOn(),
    new blueprints.addons.CoreDnsAddOn(),
    new blueprints.addons.KubeProxyAddOn(),
    karpenterAddOn
];
const stack = blueprints.EksBlueprint.builder()
    .account(process.env.AWS_ACCOUNT_ID as string)
    .region(region)
    .addOns(...addOns)
    .useDefaultSecretEncryption(true) // set to false to turn secret encryption off (non-production/demo cases)
    .version(KubernetesVersion.V1_30)
    .build(app, clusterName);

Versions:

Chart Version: 0.37.0
Kubernetes Version (kubectl version): 1.30

Please vote on this issue by adding a 👍 reaction to the original issue to help the community and maintainers prioritize this request
Please do not leave "+1" or "me too" comments, they generate extra noise for issue followers and do not help prioritize the request
If you are interested in working on this issue or have submitted a pull request, please leave a comment

This repo does not own or maintain the blueprint NPM module, I would recommend opening an issue over in cdk-eks-blueprints. I'm going to close this for now, feel free to reopen if you believe the underlying issue is Karpenter and not the blueprints.


Gem updates

First I want to say thank you, as I find this gem to be very usefull to me and my projects.
Do you still maintain this gem? I've forked it and made some minor changes in order to make it work with the most recent version of Grape (1.0.1). If you are willing to accept, I can submit a PR. I would also love to make some further contributions to improve the gem even better.

Hi @fabianoarruda, thank you for your kind words.
Unfortunately, I do not maintain this gem anymore. I can give you access to the repository if you are willing to take care of it :)


Add Database and it's Principal Assignments to Azure Verified Modules for Azure Data Explorer - avm/res/kusto/cluster

I noticed that they do not currently define databases and their principal assignments. Including these features would significantly enhance the functionality of the modules.

@KavyaYashas, thank you for submitting this issue. I've transferred it to the BRM (Bicep registry modules) repository, where we track all feature requests related to AVM modules.
@oZakari, as the owner of this module, can you please take a look and advise on the possible timeline. Thank you!

Hi @KavyaYashas, thanks for bringing this forward. I work on getting this in around to this later this month. If you have any questions or considerations, feel free to add them here. Thanks!

Hey @KavyaYashas. sorry for the delay. Been stretched a bit thin recently, so will need to push this into next month. If you need it sooner, please feel free to submit a PR or share a working branch and we can tag team it.


Is there a plugin for perspective transform ?

I found a powerful fork version of Pixi.js https://github.com/gameofbombs/pixi.js , but it is too complex and not based on Pixi.js v4 .
So I want to know where could I find a simple plugin just for  perspective transform .
Thanks

Its based on pixi-v4.0.0-rc1. Whats so complex about it? https://gameofbombs.github.io/pixi-bin/index.html?s=flip&f=cards.js&title=Cards
What features from 4.1 do you need in it? I'll make new iteration soon.

@ivanpopelyshev  , complex is not correct , sorry.
In fact , I mean there are many features needless for me ,  and many differences between this fork version and origin pixi.js .
And  the features in  this fork are not designed as plugins or extensions ,  they mix with the origin version, I don't like this way.
I hope the 3D feature could  exists with origin pixi.js as  plugin or extension.
However,  the key point is I just need that  apply  perspective transform on one sprite.

It will be possible in pixi-v5 may be ;) To change it only for one sprite, you'll have to add new renderer anyway.

@ivanpopelyshev  , So  the answer of "Is there a plugin for perspective transform" is  NO ???

@finscn No, you're free to make one. I'd like to see how will you do that without punching straight through the pixi core ;)
You can also hack threejs into pixi, use the same webgl context. For that, please search in gitter.im/pixijs/pixi.js log, we collabed something with someone.

@ivanpopelyshev  , thank you & kiss you !

Hi, @ivanpopelyshev  ,  I found this https://github.com/evanw/glfx.js  .
in glfx demo http://evanw.github.io/glfx.js/demo/ , there is a perspective filter is very good.
And in 2D game , perspective filter is just a vision effect,  so  it doesn't need interaction I think.
Could you add it to PIXI.js , please  @englercj  @GoodBoyDigital  ?
I want to do and tried , but I failed. I'm too weak at WebGL & PIXI.js .
I don't  know how to find a way to  add a new filter to PIXI.js .

There is a simple one  http://jsfiddle.net/rjw57/A6Pgy/

@ivanpopelyshev  , I've code a renderer & a filter for perspective transform :
https://github.com/finscn/pixi.js/blob/master/src/extension/PerspectiveRenderer.js
https://github.com/finscn/pixi.js/blob/master/src/extension/PerspectiveFilter.js
Thanks for your help :)

@finscn Nice. now make it into a separate plugin like  https://github.com/pixijs/pixi-plugin-example and give us a demo :)

@finscn Are these extensions available somewhere? Because I really do need something similar right now and demo looks pretty good, so the source would be really helpful to me.

@finscn you had that plugin in different repo somewhere, right?
@glalev we have to ask @GoodBoyDigital what is he using for production. Latest dev-geometry branch has something, there are 2 3d games already:
http://www.bbc.co.uk/cbbc/games/the-worst-witch-magic-adventure-game
https://christmasexperiments.com/2016/14/night-before-christmas/

@glalev  , it's here : https://github.com/finscn/pixi.js/tree/master/src/extensions/renderers/perspective

@GoodBoyDigital  , you've created many wonderful examples/demos/samples  of PIXI.js , But not opensource ,and no any document/tutorial talk about how to do that . It's so pity.
I've asked at https://github.com/pixijs/pixi.js/issues/3160 . Could you tell why?

mainly down to time :/
but when update is ready - i will have some examples to share

@GoodBoyDigital  , thanks.  the  https://christmasexperiments.com/2016/14/night-before-christmas/ is amazing!
I'll close  #3160 .
Thanks


placeholder's dont work

Using angular 1.5.1 and latest version of angular-chosen
tried defining the chosen select as so:
select.form-control(
    name='school'
    chosen
    ng-model='pageData.selectedSchool'
    ng-options='school.name for school in pageData.schools'
    ng-if='!isDisabled'
    required
    ng-change='pageData.selectSchool($item)'
    data-placeholder="Pick one of these"
  )

And the placeholder is not set to "Pick one of these". I've also tried using placeholder-text-single and placeholder attributes and they also do not work (placeholder-text-single actually gives an error).

Hi @stringbeans, thank you for your request.
The correct placeholders for Chosen and Angular Chosen are:
placeholder-text-multiple and placeholder-text-single
Check our Documentation and an Example

Sorry I've just read your last expression:

And the placeholder is not set to "Pick one of these". I've also tried using placeholder-text-single and placeholder attributes and they also do not work (placeholder-text-single actually gives an error).

Could you please be more specific about your error?
That would be nice if you could fork my plunkr and make your changes.

My plunkr up to date with Angular Chosen 1.3.0 and Angular 1.5.1: http://plnkr.co/edit/EW2j9r?p=preview
Tested up to multiple and single

@leocaseiro thanks for the speedy response! i looked at your plunkr and noticed that i'm setting the attribute wrong. instead of placeholder-text-single='hello there' it should be placeholder-text-single="'hello there'"
this was not reflected in the documentation and is possibly why i was confused. if you're up for it i can do a pull request on your docs to update this.
btw, we are also a techstars company, so hi!

Yeah! This because those string attributes emulating a scope type '@'
With that said, you could have a variable to bind on your placeholder:
$scope.customPlaceholder: 'My message';

<select chosen placeholder-text-single="customPlaceholder">...</select>

PR are always welcome. We use slate on docs branch.
Send me a PR there. That would be nice refer the egghead link.


AttributeError: 'PrimitiveSchema' object has no attribute '_schemas'

https://github.com/dion-ricky/tokyo-lineage/blob/d30443d2e3d87b8917a25fbf66b479bc793aa698/tokyo_lineage/metadata_extractor/airflow/postgres_to_avro_extractor.py#L135

Marked as need testing for now.


Selection Sort

Submission Title
Selection Sort
Submission Type
Algorithm
Submission Description
Selection sort is a simple sorting algorithm. This sorting algorithm is an in-place comparison-based algorithm in which the list is divided into two parts, the sorted part at the left end and the unsorted part at the right end.
Contributors

[x]  C++ -
[x]  C -
[ ]  Python -
[x] Java -
[ ] JavaScript -
[ ] TypeScript -
[ ] Golang -
[ ] Ruby -
[ ] Scala -

@ahampriyanshu I would like to contribute to this, please assign me this task to implement selection sort in c++.

Hello, I would like to implement Selection Sort in Python

Hello, I would like to work on implementing Selection Sort in Java

I would like to code in java

I would like to code in C. Kindly assign me this.

I will like to code it in python

Submission Title
Selection Sort
Submission Type
Algorithm
Submission Description
Selection sort is a simple sorting algorithm. This sorting algorithm is an in-place comparison-based algorithm in which the list is divided into two parts, the sorted part at the left end and the unsorted part at the right end.
Contributors

[x]   C++ -
[x]   C -
[x]   Python -
[x]  Java -
[ ]  JavaScript -
[ ]  TypeScript -
[ ]  Golang -
[ ]  Ruby -
[ ]  Scala -

Hello, i would like to code in javascript. Thanks

thanks @everyone :v:


As Nucleus, I want to use a lock file to know when DUM is writing to a S3 bucket folder

Checked for duplicates
No - I haven't checked
🧑🔬 User Persona(s)
No response
💪 Motivation
...so that I can know when a directory has completed reading, and we can fully evaluate all the products (XML + data files) in the directory + sub-directories.
📖 Additional Details

Crawl file system
Each directory you come across, write a dum.lock file with TBD information in it
Continue to crawl and write data, as you complete a directory, and all it's sub-directories, remove the dum.lock file

Acceptance Criteria
Given
When I perform
Then I expect
⚙ Engineering Details
No response

Per discussions on Nucleus design, we are not going this route


pwd driver for Docker Machine

Hi,
as docker-machine binary is available in each instance, do you think the pwd driver could be installed as well ? This would help to demo Docker Machine without any link to cloud provider's driver and issue command like:
docker-machine create -d pwd dm-node0

@lucj think so. Does it make sense to manage PWD withing PWD? :face_with_head_bandage: ?

@marcosnils I think the use case could be to demo Docker-Machine directly within PWD, instead of popping up test instances on AWS, DO, ..
During a training, people using "Docker for Windows" were not able to play with Docker Machine as it was not possible to create a new VM on VirtualBox nor on Hyper-V.

@lucj the thing is that it's not possible to do docker-machine ssh in PWD at this moment. I wouldn't like users to "learn" how to use machine with some missing features. It makes the experience quite ackward.

@marcosnils I totally agree with you.
A workaround for the problem I had last time could be to have D4W users to install pwd driver then.
Thanks a lot.


[QST]

❓ Questions & Help
Details
Hi, I have experienced CUDA out of memory error while trying out examples in jupyter notebook files. Is there any neat way of solving this error?
os: Ubuntu 20.04
gpu: NVIDIA GeForce RTX 3060 Ti
cuda: 11.8
cudnn: 8
docker version: 24.0.1
docker image: nvcr.io/nvidia/merlin/merlin-pytorch-training:22.03
ipynb file: 02-ETL-with-NVTabular.ipynb
The code that throws an error cudaErrorMemoryAllocation out of memory:
train_dataset = nvt.Dataset([os.path.join(INPUT_DATA_DIR, "train.parquet")])

valid_dataset = nvt.Dataset([os.path.join(INPUT_DATA_DIR, "valid.parquet")])
%%time
workflow.fit(train_dataset)

@Bartoliinii  hello. Can you clarify the followings:

which 02 notebook is that?  the one in getting-started-movielens folder?
Are you using your own dataset or the dataset used in the notebook example?
Are you running the notebook as in the docker image or you are running the notebook from Merlin repo main branch? These two can be different.

Besides, the docker image version you mentioned above is like one year old. Is it possible for you to use our latest stable docker image? Can you please test merlin-pytorch-training:23.04  image?

Hi @rnyak thanks for responding.

which 02 notebook is that? the one in getting-started-movielens folder?

It was this notebook: https://nvidia-merlin.github.io/NVTabular/v0.7.1/examples/getting-started-movielens/02-ETL-with-NVTabular.html

Are you using your own dataset or the dataset used in the notebook example?

I was running cells, with no custom inputs on my part

Are you running the notebook as in the docker image or you are running the notebook from Merlin repo main branch? These two can be different.

I was running it as a docker image

Besides, the docker image version you mentioned above is like one year old. Is it possible for you to use our latest stable docker image? Can you please test merlin-pytorch-training:23.04 image?

I know, but the last time I tried to use a newer docker image with tensorflow I had to update drivers for nvidia graphics card, this update wrecked my cuda installation.

One additional question, is there a way to load a parquet file without filling GPU? Something that resembles dask_cudf.read_parquete?

One additional question, is there a way to load a parquet with nvt without filling GPU?

you can directly read data from path to NVT.. like that:
dataset= nvt.Dataset(<path to your parquet files>)
workflow.fit_transform(dataset)
...

does that answer your question?
btw, do you have 8 GB machine?

does that answer your question?
Yes, thank you.
btw, do you have 8 GB machine?
Yes, I do.

@Bartoliinii  I noticed that you are following examples in the NVT website.. Please use these notebooks instead:
https://github.com/NVIDIA-Merlin/Merlin/tree/main/examples/getting-started-movielens
thanks.

I made sure no other nds are running:

root@c16d4c741902:/Merlin/examples/getting-started-movielens# jupyter notebook list
Currently running servers:

Before running the 02-ETL-with-NVTabular.ipynb GPU memory consumption was at 6.2%
I changed df_lib.read_parquet to pandas.read_parquet in 3 cell
Just before running workflow.fit(train_dataset) GPU memory consumption was at 13.4% because of the joined = userId + movieId >> JoinExternal(movies, on=["movieId"])

Unfortunately, the error still remains. Here is the full output:
/usr/local/lib/python3.8/dist-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.USER_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.USER: 'user'>, <Tags.ID: 'id'>].
  warnings.warn(
/usr/local/lib/python3.8/dist-packages/merlin/schema/tags.py:148: UserWarning: Compound tags like Tags.ITEM_ID have been deprecated and will be removed in a future version. Please use the atomic versions of these tags, like [<Tags.ITEM: 'item'>, <Tags.ID: 'id'>].
  warnings.warn(
Failed to transform operator <nvtabular.ops.categorify.Categorify object at 0x7f0314138190>
Traceback (most recent call last):
  File "/usr/local/lib/python3.8/dist-packages/nvtabular/ops/categorify.py", line 463, in transform
    encoded = _encode(
  File "/usr/local/lib/python3.8/dist-packages/nvtabular/ops/categorify.py", line 1427, in _encode
    labels = codes.merge(
  File "/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py", line 101, in inner
    result = func(*args, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py", line 3759, in merge
    return merge_cls(
  File "/usr/local/lib/python3.8/dist-packages/cudf/core/join/join.py", line 200, in perform_merge
    self.rhs._gather(gather_map=right_rows, **gather_kwargs)
  File "/usr/local/lib/python3.8/dist-packages/cudf/core/indexed_frame.py", line 1506, in _gather
    libcudf.copying.gather(
  File "copying.pyx", line 185, in cudf._lib.copying.gather
MemoryError: std::bad_alloc: out_of_memory: CUDA error at: /usr/local/include/rmm/mr/device/cuda_memory_resource.hpp:70: cudaErrorMemoryAllocation out of memory

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/usr/local/lib/python3.8/dist-packages/merlin/dag/executors.py", line 183, in _transform_data
    output_data = node.op.transform(selection, input_data)
  File "/usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py", line 101, in inner
    result = func(*args, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/nvtabular/ops/categorify.py", line 483, in transform
    raise RuntimeError(f"Failed to categorical encode column {name}") from e
RuntimeError: Failed to categorical encode column genres

---------------------------------------------------------------------------
MemoryError                               Traceback (most recent call last)
File /usr/local/lib/python3.8/dist-packages/nvtabular/ops/categorify.py:463, in Categorify.transform(self, col_selector, df)
    461 path = self.categories[storage_name]
--> 463 encoded = _encode(
    464     use_name,
    465     storage_name,
    466     path,
    467     df,
    468     self.cat_cache,
    469     na_sentinel=self.na_sentinel,
    470     freq_threshold=self.freq_threshold[name]
    471     if isinstance(self.freq_threshold, dict)
    472     else self.freq_threshold,
    473     search_sorted=self.search_sorted,
    474     buckets=self.num_buckets,
    475     encode_type=self.encode_type,
    476     cat_names=column_names,
    477     max_size=self.max_size,
    478     dtype=self.output_dtype,
    479     start_index=self.start_index,
    480 )
    481 new_df[name] = encoded

File /usr/local/lib/python3.8/dist-packages/nvtabular/ops/categorify.py:1427, in _encode(name, storage_name, path, df, cat_cache, na_sentinel, freq_threshold, search_sorted, buckets, encode_type, cat_names, max_size, dtype, start_index)
   1426 na_sentinel = 0
-> 1427 labels = codes.merge(
   1428     value, left_on=selection_l.names, right_on=selection_r.names, how="left"
   1429 ).sort_values("order")["labels"]
   1430 labels.fillna(na_sentinel, inplace=True)

File /usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101, in annotate.__call__.<locals>.inner(*args, **kwargs)
    100 libnvtx_push_range(self.attributes, self.domain.handle)
--> 101 result = func(*args, **kwargs)
    102 libnvtx_pop_range(self.domain.handle)

File /usr/local/lib/python3.8/dist-packages/cudf/core/dataframe.py:3759, in DataFrame.merge(self, right, on, left_on, right_on, left_index, right_index, how, sort, lsuffix, rsuffix, indicator, suffixes)
   3757     merge_cls = MergeSemi
-> 3759 return merge_cls(
   3760     lhs,
   3761     rhs,
   3762     on=on,
   3763     left_on=left_on,
   3764     right_on=right_on,
   3765     left_index=left_index,
   3766     right_index=right_index,
   3767     how=how,
   3768     sort=sort,
   3769     indicator=indicator,
   3770     suffixes=suffixes,
   3771 ).perform_merge()

File /usr/local/lib/python3.8/dist-packages/cudf/core/join/join.py:200, in Merge.perform_merge(self)
    194 left_result = (
    195     self.lhs._gather(gather_map=left_rows, **gather_kwargs)
    196     if left_rows is not None
    197     else cudf.DataFrame._from_data({})
    198 )
    199 right_result = (
--> 200     self.rhs._gather(gather_map=right_rows, **gather_kwargs)
    201     if right_rows is not None
    202     else cudf.DataFrame._from_data({})
    203 )
    205 result = cudf.DataFrame._from_data(
    206     *self._merge_results(left_result, right_result)
    207 )

File /usr/local/lib/python3.8/dist-packages/cudf/core/indexed_frame.py:1506, in IndexedFrame._gather(self, gather_map, keep_index, nullify, check_bounds)
   1503     raise IndexError("Gather map index is out of bounds.")
   1505 return self._from_columns_like_self(
-> 1506     libcudf.copying.gather(
   1507         list(self._index._columns + self._columns)
   1508         if keep_index
   1509         else list(self._columns),
   1510         gather_map,
   1511         nullify=nullify,
   1512     ),
   1513     self._column_names,
   1514     self._index.names if keep_index else None,
   1515 )

File copying.pyx:185, in cudf._lib.copying.gather()

MemoryError: std::bad_alloc: out_of_memory: CUDA error at: /usr/local/include/rmm/mr/device/cuda_memory_resource.hpp:70: cudaErrorMemoryAllocation out of memory

The above exception was the direct cause of the following exception:

RuntimeError                              Traceback (most recent call last)
File <timed eval>:1

File /usr/local/lib/python3.8/dist-packages/nvtabular/workflow/workflow.py:213, in Workflow.fit(self, dataset)
    209         dependencies.difference_update(current_phase)
    211 # This captures the output dtypes of operators like LambdaOp where
    212 # the dtype can't be determined without running the transform
--> 213 self._transform_impl(dataset, capture_dtypes=True).sample_dtypes()
    214 self.graph.construct_schema(dataset.schema, preserve_dtypes=True)
    216 return self

File /usr/local/lib/python3.8/dist-packages/merlin/io/dataset.py:1155, in Dataset.sample_dtypes(self, n, annotate_lists)
   1148 """Return the real dtypes of the Dataset
   1149
   1150 Use cached metadata if this operation was
   1151 already performed. Otherwise, call down to the
   1152 underlying engine for sampling logic.
   1153 """
   1154 if self._real_meta.get(n, None) is None:
-> 1155     _real_meta = self.engine.sample_data(n=n)
   1156     if self.dtypes:
   1157         _real_meta = _set_dtypes(_real_meta, self.dtypes)

File /usr/local/lib/python3.8/dist-packages/merlin/io/dataset_engine.py:71, in DatasetEngine.sample_data(self, n)
     69 _ddf = self.to_ddf()
     70 for partition_index in range(_ddf.npartitions):
---> 71     _head = _ddf.partitions[partition_index].head(n)
     72     if len(_head):
     73         return _head

File /usr/local/lib/python3.8/dist-packages/dask/dataframe/core.py:1256, in _Frame.head(self, n, npartitions, compute)
   1254 # No need to warn if we're already looking at all partitions
   1255 safe = npartitions != self.npartitions
-> 1256 return self._head(n=n, npartitions=npartitions, compute=compute, safe=safe)

File /usr/local/lib/python3.8/dist-packages/dask/dataframe/core.py:1290, in _Frame._head(self, n, npartitions, compute, safe)
   1285 result = new_dd_object(
   1286     graph, name, self._meta, [self.divisions[0], self.divisions[npartitions]]
   1287 )
   1289 if compute:
-> 1290     result = result.compute()
   1291 return result

File /usr/local/lib/python3.8/dist-packages/dask/base.py:315, in DaskMethodsMixin.compute(self, **kwargs)
    291 def compute(self, **kwargs):
    292     """Compute this dask collection
    293
    294     This turns a lazy Dask collection into its in-memory equivalent.
   (...)
    313     dask.base.compute
    314     """
--> 315     (result,) = compute(self, traverse=False, **kwargs)
    316     return result

File /usr/local/lib/python3.8/dist-packages/dask/base.py:598, in compute(traverse, optimize_graph, scheduler, get, *args, **kwargs)
    595     keys.append(x.__dask_keys__())
    596     postcomputes.append(x.__dask_postcompute__())
--> 598 results = schedule(dsk, keys, **kwargs)
    599 return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])

File /usr/local/lib/python3.8/dist-packages/dask/local.py:557, in get_sync(dsk, keys, **kwargs)
    552 """A naive synchronous version of get_async
    553
    554 Can be useful for debugging.
    555 """
    556 kwargs.pop("num_workers", None)  # if num_workers present, remove it
--> 557 return get_async(
    558     synchronous_executor.submit,
    559     synchronous_executor._max_workers,
    560     dsk,
    561     keys,
    562     **kwargs,
    563 )

File /usr/local/lib/python3.8/dist-packages/dask/local.py:500, in get_async(submit, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, chunksize, **kwargs)
    498 while state["waiting"] or state["ready"] or state["running"]:
    499     fire_tasks(chunksize)
--> 500     for key, res_info, failed in queue_get(queue).result():
    501         if failed:
    502             exc, tb = loads(res_info)

File /usr/lib/python3.8/concurrent/futures/_base.py:437, in Future.result(self, timeout)
    435     raise CancelledError()
    436 elif self._state == FINISHED:
--> 437     return self.__get_result()
    439 self._condition.wait(timeout)
    441 if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:

File /usr/lib/python3.8/concurrent/futures/_base.py:389, in Future.__get_result(self)
    387 if self._exception:
    388     try:
--> 389         raise self._exception
    390     finally:
    391         # Break a reference cycle with the exception in self._exception
    392         self = None

File /usr/local/lib/python3.8/dist-packages/dask/local.py:542, in SynchronousExecutor.submit(self, fn, *args, **kwargs)
    540 fut = Future()
    541 try:
--> 542     fut.set_result(fn(*args, **kwargs))
    543 except BaseException as e:
    544     fut.set_exception(e)

File /usr/local/lib/python3.8/dist-packages/dask/local.py:238, in batch_execute_tasks(it)
    234 def batch_execute_tasks(it):
    235     """
    236     Batch computing of multiple tasks with `execute_task`
    237     """
--> 238     return [execute_task(*a) for a in it]

File /usr/local/lib/python3.8/dist-packages/dask/local.py:238, in <listcomp>(.0)
    234 def batch_execute_tasks(it):
    235     """
    236     Batch computing of multiple tasks with `execute_task`
    237     """
--> 238     return [execute_task(*a) for a in it]

File /usr/local/lib/python3.8/dist-packages/dask/local.py:229, in execute_task(key, task_info, dumps, loads, get_id, pack_exception)
    227     failed = False
    228 except BaseException as e:
--> 229     result = pack_exception(e, dumps)
    230     failed = True
    231 return key, result, failed

File /usr/local/lib/python3.8/dist-packages/dask/local.py:224, in execute_task(key, task_info, dumps, loads, get_id, pack_exception)
    222 try:
    223     task, data = loads(task_info)
--> 224     result = _execute_task(task, data)
    225     id = get_id()
    226     result = dumps((result, id))

File /usr/local/lib/python3.8/dist-packages/dask/core.py:119, in _execute_task(arg, cache, dsk)
    115     func, args = arg[0], arg[1:]
    116     # Note: Don't assign the subtask results to a variable. numpy detects
    117     # temporaries by their reference count and can execute certain
    118     # operations in-place.
--> 119     return func(*(_execute_task(a, cache) for a in args))
    120 elif not ishashable(arg):
    121     return arg

File /usr/local/lib/python3.8/dist-packages/dask/optimization.py:990, in SubgraphCallable.__call__(self, *args)
    988 if not len(args) == len(self.inkeys):
    989     raise ValueError("Expected %d args, got %d" % (len(self.inkeys), len(args)))
--> 990 return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args)))

File /usr/local/lib/python3.8/dist-packages/dask/core.py:149, in get(dsk, out, cache)
    147 for key in toposort(dsk):
    148     task = dsk[key]
--> 149     result = _execute_task(task, cache)
    150     cache[key] = result
    151 result = _execute_task(out, cache)

File /usr/local/lib/python3.8/dist-packages/dask/core.py:119, in _execute_task(arg, cache, dsk)
    115     func, args = arg[0], arg[1:]
    116     # Note: Don't assign the subtask results to a variable. numpy detects
    117     # temporaries by their reference count and can execute certain
    118     # operations in-place.
--> 119     return func(*(_execute_task(a, cache) for a in args))
    120 elif not ishashable(arg):
    121     return arg

File /usr/local/lib/python3.8/dist-packages/dask/utils.py:41, in apply(func, args, kwargs)
     39 def apply(func, args, kwargs=None):
     40     if kwargs:
---> 41         return func(*args, **kwargs)
     42     else:
     43         return func(*args)

File /usr/local/lib/python3.8/dist-packages/merlin/dag/executors.py:72, in LocalExecutor.transform(self, transformable, graph, output_dtypes, additional_columns, capture_dtypes, validate_dtypes)
     69 output_data = None
     71 for node in nodes:
---> 72     input_data = self._build_input_data(
     73         node, transformable, capture_dtypes=capture_dtypes, validate_dtypes=validate_dtypes
     74     )
     76     if node.op:
     77         transformed_data = self._transform_data(
     78             node, input_data, capture_dtypes=capture_dtypes, validate_dtypes=validate_dtypes
     79         )

File /usr/local/lib/python3.8/dist-packages/merlin/dag/executors.py:121, in LocalExecutor._build_input_data(self, node, transformable, capture_dtypes, validate_dtypes)
    119 for parent in node.parents_with_dependencies:
    120     parent_output_cols = _get_unique(parent.output_schema.column_names)
--> 121     parent_data = self.transform(
    122         transformable,
    123         [parent],
    124         capture_dtypes=capture_dtypes,
    125         validate_dtypes=validate_dtypes,
    126     )
    127     if input_data is None or not len(input_data):
    128         input_data = parent_data[parent_output_cols]

File /usr/local/lib/python3.8/dist-packages/merlin/dag/executors.py:77, in LocalExecutor.transform(self, transformable, graph, output_dtypes, additional_columns, capture_dtypes, validate_dtypes)
     72 input_data = self._build_input_data(
     73     node, transformable, capture_dtypes=capture_dtypes, validate_dtypes=validate_dtypes
     74 )
     76 if node.op:
---> 77     transformed_data = self._transform_data(
     78         node, input_data, capture_dtypes=capture_dtypes, validate_dtypes=validate_dtypes
     79     )
     80 else:
     81     transformed_data = input_data

File /usr/local/lib/python3.8/dist-packages/merlin/dag/executors.py:183, in LocalExecutor._transform_data(self, node, input_data, capture_dtypes, validate_dtypes)
    180 try:
    181     # use input_columns to ensure correct grouping (subgroups)
    182     selection = node.input_columns.resolve(node.input_schema)
--> 183     output_data = node.op.transform(selection, input_data)
    185     # Update or validate output_data dtypes
    186     if capture_dtypes or validate_dtypes:

File /usr/local/lib/python3.8/dist-packages/nvtx/nvtx.py:101, in annotate.__call__.<locals>.inner(*args, **kwargs)
     98 @wraps(func)
     99 def inner(*args, **kwargs):
    100     libnvtx_push_range(self.attributes, self.domain.handle)
--> 101     result = func(*args, **kwargs)
    102     libnvtx_pop_range(self.domain.handle)
    103     return result

File /usr/local/lib/python3.8/dist-packages/nvtabular/ops/categorify.py:483, in Categorify.transform(self, col_selector, df)
    481         new_df[name] = encoded
    482     except Exception as e:
--> 483         raise RuntimeError(f"Failed to categorical encode column {name}") from e
    485 return new_df

RuntimeError: Failed to categorical encode column genres

I ran the notebooks in jupyterlab and got the same error. I saw that my GPU memory was near full because the previous kernel was still running, I just went to that notebook and killed the kernel that freed up the memory and I also limited the memory to 128 MB.
train_dataset = nvt.Dataset([os.path.join(INPUT_DATA_DIR, "train.parquet")], part_size='128MB')
valid_dataset = nvt.Dataset([os.path.join(INPUT_DATA_DIR, "valid.parquet")], part_size='128MB')


Proper locking

Currently we are not locking around data structures that are manipulated in a non-atomic way.  There are minimal downsides to this, when a configuration-set is changed we may have some workers that are misconfigured for 5 seconds.  Still, it would be best to handle this in a more proper way.

We need to get proper locking in place for qtrix operations.
These should be at the facade level.  So any public operation of the Qtrix module should block until they can obtain a lock, then release it when they are done.
Possible options include this or this

Fixed by #17


Creating a second slice replaces default device group

Describe the bug
Default device group is overwritten every time a slice is created
To Reproduce

Create a slice
Delete the default device group
Create a new default device group with different values
Confirm new values are present
Create a new slice
Reload the page and note the reset in slice 1's default

Expected behavior

Screenshots
First slice

Second slice, both defaults are set back to initial values

After https://github.com/canonical/sdcore-nms/pull/226 the default Device Group is no longer called default. So it should help with this issue.
I agree we should check whether the DG exist before creating it. It's in  the backlog


Documenting witch part of the HAR format is implemented

It would be very nice to know witch part of the the HAR format is implemented and what is the result of each non-evident options.

:+1: good point.


FIX #3 Command ./bin/dockerhub_run.sh fails

ping @busycalibrating :-)

Hmm when I test this locally, I still seem to get the error:
Could not find jekyll-4.3.2, jekyll-4.3.2, jekyll-scholar-7.1.3, jekyll-scholar-7.1.3, jekyll-target-blank-2.0.2, jekyll-target-blank-2.0.2, mini_racer-0.8.0, mini_racer-0.8.0, webrick-1.8.1, webrick-1.8.1, addressable-2.8.5, addressable-2.8.5, i18n-1.14.1, i18n-1.14.1, rouge-4.1.3, rouge-4.1.3, nokogiri-1.15.4-x86_64-linux, nokogiri-1.15.4-x86_64-linux, mini_mime-1.1.5, mini_mime-1.1.5, loofah-2.21.3, loofah-2.21.3, public_suffix-5.0.3, public_suffix-5.0.3, concurrent-ruby-1.2.2, concurrent-ruby-1.2.2, rexml-3.2.6, rexml-3.2.6, execjs-2.9.1, execjs-2.9.1, racc-1.7.1, racc-1.7.1 in locally installed gems
Run `bundle install` to install missing gems.

interesting. Do you get the same error without my "fix"?

I get a similar error (needing to run bundle install) but with different packages.

I cleared my docker cache and I can now reproduce the bug

Since the approach of running
./bin/docker_build_image.sh
./bin/docker_run.sh

seems to work fine, what do you think of featuring that approach in the instructions and README @busycalibrating  ?
We could also potentially merge both scripts into a single one, I'm not sure why they need to be separate scripts, the second time I call ./bin/docker_build_image.sh it finishes in less than a second

Yeah that sounds good to me! They can be merged I suppose, as they don't seem to be used elsewhere (namely in any of the GH actions)

great! I created a new pull request for that (https://github.com/iclr-blogposts/2024/pull/8)
please review that one instead @busycalibrating and I'll close this one


Issue with mapped types and enums

TypeScript Version:  2.4.1 /
Code
enum Things {
	ONE = "one",
	TWO = "two"
}

type ThingMap = { [TKey in Things]: any };

const thingMap: ThingMap = {
	one: null,
	two: null
};

function setThing(thing: Things, something: any) {
	thingMap[thing] = something;
}

Expected behavior:
Just like I can do thingMap[Things.ONE] = 'blah' without any errors, this should not throw an error.
Actual behavior:
src/test.ts(14,2): error TS7017: Element implicitly has an 'any' type because type 'ThingMap' has no index signature.

Seems related to https://github.com/Microsoft/TypeScript/issues/16687

I encountered that too but it's not quite the same thing.

Actually duplicate of https://github.com/Microsoft/TypeScript/issues/16760, and should be fixed by https://github.com/Microsoft/TypeScript/pull/18029


Add data from Muck Rock

Go to PDAP sources and search for source_url containing muckrock

More MuckRock data:

https://www.muckrock.com/foi/list/?page=4&per_page=25&q=police+data&status=done&sort=user&order=asc
https://www.muckrock.com/foi/list/?q=&status=done&user=2937&has_embargo=&has_crowdfund=&minimum_pages=&date_range_min=&date_range_max=&file_types=

MuckRock API:

https://palewi.re/docs/python-muckrock/index.html
https://github.com/palewire/python-muckrock/tree/main
More

Dealing with cert issues:

python find and download pem
https://stackoverflow.com/questions/51039393/get-or-build-pem-certificate-chain-in-python
https://stackoverflow.com/questions/19145097/getting-certificate-chain-with-python-3-3-ssl-module
https://www.ecosia.org/search?q=python getpeercertchain&addon=opensearch
https://stackoverflow.com/questions/7689941/how-can-i-retrieve-the-tls-ssl-peer-certificate-of-a-remote-host-using-python
https://www.digicert.com/kb/ssl-support/pem-ssl-creation.htm
https://learn.microsoft.com/en-us/azure/application-gateway/mutual-authentication-certificate-management
https://www.digicert.com/kb/digicert-root-certificates.htm
https://help.mulesoft.com/s/article/How-to-Download-Whole-Certificate-Chain-From-A-Remote-Host-and-Import-to-a-Trust-Store
https://www.avisi.nl/blog/2012/09/12/quick-way-to-retrieve-a-chain-of-ssl-certificates-from-a-server

@sowdm What is a good example of data that has the cert problem? From PDAP when I used https://www.muckrock.com/foi/pittsburgh-130/q1-2023-traffic-stops-144011/ and ran
r = requests.get('https://cdn.muckrock.com/foia_files/2023/05/10/TrafficStops_RTK04-02-2023_Chamberlain_With_additional_datasets..xlsx')
I got a 200 and was able to download it with
# Check if the request was successful
if r.status_code == 200:
    with open('output_file.xlsx', 'wb') as f:
        f.write(r.content)
else:
    print(f"Request failed with status code {r.status_code}")

Great! This one also seems to work for me now. Maybe something was fixed? Should we close this?
Have you tried the Chicago one?

Just did at the below worked?  Is it now working for you also?
url = "https://home.chicagopolice.org/wp-content/uploads/2022-ISR.zip"
storage_options = {'User-Agent': 'Mozilla/5.0'}
df = pd.read_csv(url, storage_options=storage_options)

Going to add https://www.muckrock.com/foi/pittsburgh-130/q1-2023-traffic-stops-144011/ following the Contribution guide and update the guide as necessary.

To access all available data files programmatically, follow the example code:
https://github.com/MuckRock/API-examples/blob/master/export_file_data.py
You will need to convert the code from Python 2.x to Python 3.x which is basically changing the print statements to functions and the unicodecsv module to csv.
Although you should not need an API token for most queries unless it is to access protected data, like your embargoed requests, to get a token follow the instructions at To add data https://www.muckrock.com/api/
Because of rate limiting the API (and generally, the entire site) is rate limited to one request per second, however you can burst these requests up to 20 per second for as long as the average runs less than 1 per second over a 20 second period. This can cause extremely slow requests. For example, https://github.com/MuckRock/API-examples/blob/master/export_file_data.py has been running for 12 hours and has not completed.
Also the API does not allow for file type filtering as discussed in https://github.com/MuckRock/API-examples/issues/13. Therefore you need to retrieve all the file names from the server and search through the response on the client.

This is at least partially redundant with #231. Keeping it open since there is some unique useful info in this issue.


Configuration#4:Step#1: simulating alpha_S=0.2, matter: q_0=1 | matterlbt: q_0=2: matter03

run the simulation with the above config by jetscape,
transfer the final state hadron to the related directory named as config-XX-final-state-hadrons
after doing step1 on all 12 simulations go to step 2 for the configurationX

port to Excel for overleaf


chat 功能正常，知识库报错：401 Unauthorized

chat 功能正常。
知识库报错如下：

Error: Failed to batch create run: 401 Unauthorized {"detail":"Need authorization header or api key"}

Any solution to this issue?

This is very likely that you don't have the LANGSMITH_API_KEY set in the .env.
Please refer to .env.example - https://github.com/sugarforever/chat-ollama/blob/main/.env.example
DISABLE_VERCEL_ANALYTICS=false
OPENAI_API_KEY=
DATABASE_URL=file:../../chatollama.sqlite
CHROMADB_URL=http://localhost:8000

LANGCHAIN_TRACING_V2=true
LANGCHAIN_API_KEY=
LANGCHAIN_PROJECT=chat-ollama

If you make a copy of .env from the example, the LANGCHAIN_TRACING_V2 is set to true by default while the API key is set to empty.
We included langsmith package in the bundle, so you will see the error above. Make sure you set LANGCHAIN_TRACING_V2 to false if you have no langsmith API key set.
I will update the example with LANGCHAIN_TRACING_V2 set to false by default.

This is very likely that you don't have the LANGSMITH_API_KEY set in the .env.
Please refer to .env.example - https://github.com/sugarforever/chat-ollama/blob/main/.env.example
DISABLE_VERCEL_ANALYTICS=false
OPENAI_API_KEY=
DATABASE_URL=file:../../chatollama.sqlite
CHROMADB_URL=http://localhost:8000

LANGCHAIN_TRACING_V2=true
LANGCHAIN_API_KEY=
LANGCHAIN_PROJECT=chat-ollama

If you make a copy of .env from the example, the LANGCHAIN_TRACING_V2 is set to true by default while the API key is set to empty.
We included langsmith package in the bundle, and ChatOllama knowledge base is using LangChain, so when you chat with knowledge base, it will be trying to chat with LangSmith. As there's no API key set, you saw the error above. Make sure you set LANGCHAIN_TRACING_V2 to false if you have no langsmith API key set.
I will update the example with LANGCHAIN_TRACING_V2 set to false by default.

重新拉取了docker image。在使用知识库时会报错另外一个404的错误：
chatollama-1  | Ollama:  {
chatollama-1  |   host: 'http://host.docker.internal:11434',
chatollama-1  |   username: 'null',
chatollama-1  |   password: 'null'
chatollama-1  | }
chatollama-1  | warn(prisma-client) This is the 10th instance of Prisma Client being started. Make sure this is intentional.
chatollama-1  | Created knowledge base RC oscillator: [object Object]
chromadb-1    | INFO:     [13-03-2024 08:07:18] <IP_ADDRESS>:44608 - "POST /api/v1/collections?tenant=default_tenant&database=default_database HTTP/1.1" 200
** chatollama-1  | [nuxt] [request error] [unhandled] [500] Request to Ollama server failed: 404 Not Found**
chatollama-1  |   at OllamaEmbeddings._request (./.output/server/node_modules/@langchain/community/dist/embeddings/ollama.js:121:19)

创建知识库使用的什么文本嵌入模型？确保输入框中输入的模型名前后没有空格。我记得这里目前还没有做处理。

nomic-embed-text
前后无空格。

低级问题，没有安装“nomic-embed-text”