Library compatibility matrix

Is your feature request related to a problem? Please describe.
I am trying to setup this library with sample application, but I can not figure out what's wrong with my Maven dependencies:
java.lang.UnsupportedOperationException: null
	at org.springframework.http.ReadOnlyHttpHeaders.set(ReadOnlyHttpHeaders.java:106) ~[spring-web-5.3.9.jar:5.3.9]
	at io.opentelemetry.extension.trace.propagation.B3PropagatorInjectorSingleHeader.inject(B3PropagatorInjectorSingleHeader.java:63) ~[opentelemetry-extension-trace-propagators-1.5.0.jar:1.5.0]
	at io.opentelemetry.extension.trace.propagation.B3Propagator.inject(B3Propagator.java:111) ~[opentelemetry-extension-trace-propagators-1.5.0.jar:1.5.0]
	at org.springframework.cloud.sleuth.otel.propagation.CompositeTextMapPropagator.lambda$inject$3(CompositeTextMapPropagator.java:113) ~[spring-cloud-sleuth-otel-1.1.0-M1.jar:1.1.0-M1]

There must be something incompatible between  opentelemetry and spring.
Describe the solution you'd like
I'd like to have a table showing which libraries versions are known to be compatible:

spring-cloud-sleuth-otel
spring-cloud
spring-core / spring-boot
opentelemetry

Describe alternatives you've considered
I am following the documentation https://spring-cloud-incubator.github.io/spring-cloud-sleuth-otel/docs/current/reference/html/getting-started.html#getting-started-first-application-pom but I don't want to set a parent project

@gquintana Instead of setting a parent, adding the Spring Boot BOM in the example and not setting versions should resolve this issue.
We do have a compatibility matrix between Spring Boot and Spring Cloud: https://spring.io/projects/spring-cloud#adding-spring-cloud-to-an-existing-spring-boot-application
Everything else is governed by the BOMs so you don't need to set versions for your dependencies, you only need to define versions for your BOMs:

Spring Boot BOM
Spring Cloud BOM
Spring Cloud Sleuth OTel BOM

Based on the above, you can use the following BOMs together, these will cover everything you mentioned above:

org.springframework.boot:spring-boot-dependencies:2.5.4
org.springframework.cloud:spring-cloud-dependencies:2020.0.3
org.springframework.cloud:spring-cloud-sleuth-otel-dependencies:1.0.0-M10

I'm going to add something like this to the readme of this project (this won't be needed after Sleuth OTel goes GA since it will be in the Spring Cloud BOM) and close this issue, please let me know if you want us to reopen:

spring-cloud-sleuth-otel 1.0.x is compatible with spring-cloud 2020.x
spring-cloud-sleuth-otel 1.1.x is compatible with spring-cloud 2021.x


python3Packages.faraday-plugins: 1.5.8 -> 1.5.9

Motivation for this change
Update to latest upstream release 1.5.9
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
22.05 Release Notes (or backporting 21.11 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module
[ ] (Release notes changes) Ran nixos/doc/manual/md-to-db.sh to update generated release notes

[x] Fits CONTRIBUTING.md.

Result of nixpkgs-review pr 152373 run on x86_64-linux 1

3 packages built:

faraday-cli
python38Packages.faraday-plugins
python39Packages.faraday-plugins


Feat/input merge

Are these compatible with the safari issue? or does the user of this component has to handle it separately?

Are these compatible with the safari issue? or does the user of this component has to handle it separately?
yes checked on safari on mac


Make settings.php manipulation optional

The Problem/Issue/Bug:
Our settings.php already has configuration for ddev and we'd prefer to own the responsibility of managing the file on our own.
How this PR Solves The Problem:
Allows users to opt out of settings file management by doing ddev config --omit-settings-php. Subsequent ddev configs will remember this and continue to not manipulate settings.php.
Probably still needs docs and tests, but I'm opening this PR early to see if this is a desired feature.
Manual Testing Instructions:
Run ddev config --omit-settings-php and verify the following:

settings.php isn't modified
settings.ddev.php isn't generated
sites/default/.gitignore isn't generated
omit_settings_php: true is included in .ddev/config.yaml
Another ddev config does all of those same things ^^

Automated Testing Overview:

No tests currently. Happy to add them if needed. Same with docs.
Related Issue Link(s):
n/a
Release/Deployment notes:

Why not just use project type 'php' and avoid this altogether?

I forgot that was a thing :sweat_smile:
Are there any other differences between the drupal8 project type and the php project type?

I think that drupal8 and php nginx configs are the same, but other than that there isn't any difference that I remember. Experienced people like you are probably better with php project type, just handle all settings yourself. Even if there is something you want to do in nginx, do it in custom nginx config, which you may want anyway.
There is a slight difference:
$ diff nginx_default.conf nginx_drupal8.conf
1d0
<
14c13
<         try_files $uri $uri/ /index.php?q=$uri&$args;
---
>         try_files $uri /index.php?$query_string; # For Drupal >= 7
29,30c28
<     location ~ \.php$ {
<         try_files $uri =404;
---
>     location ~ '\.php$|^/update.php' {
52,58d49
<     # Media: images, icons, video, audio, HTC
<     location ~* \.(?:jpg|jpeg|gif|png|ico|cur|gz|svg|svgz|mp4|ogg|ogv|webm|htc)$ {
<         expires 1M;
<         access_log off;
<         add_header Cache-Control "public";
<     }
<
81a73,79
>     }
>
>     # Media: images, icons, video, audio, HTC
>     location ~* \.(js|css|png|jpg|jpeg|gif|ico|svg)$ {
>         try_files $uri @rewrite;
>         expires max;
>         log_not_found off;

Meh, close enough. Thanks for the pointer!

Always nice to see you around here!


Configuration-service: TotalCount of number of projects is wrong

When querying the list of projects, the API returns the correct list of projects but the returned totalCount is wrong. See image

Good catch. Relevant piece of code:
https://github.com/keptn/keptn/blob/1c21207b95eb2aee430bd680de9b1ad45daad8f3/configuration-service/handlers/project.go#L25-L54

Addressed with https://github.com/keptn/keptn/pull/1651


implement inherited abstract method does not know the parameter types

TypeScript Version:  2.4.2
Code
Middleware.ts
import { Request, Response, NextFunction } from 'express'

export abstract class Middleware {
  public abstract handle(req: Request, res: Response, next: NextFunction);
}

Auth.ts
import { Middleware } from '.'

export class Auth extends Middleware {
  public handle(req, res, next) {

  }
}

Within the Auth class which extends Middleware the handle method has three parameters which are define in Middleware. In my vscode editor, within the Auth class those types are all any. I was expecting that those types would be read from the parent from which they were defined. However, they do not do this.
Since Auth knows if an abstract method has or has not been defined, shouldn't it also know the parameter types of the abstract method?

Duplicate of #1373.


deprecate std.stream and friends

deprecate

std.stream
std.socketstream
std.cstream

this needs to be pulled before https://github.com/D-Programming-Language/phobos/pull/3318

:+1:

Auto-merge toggled on

I thought the correct process was to first mark it as scheduled for deprecation on $date, not deprecate outright.

Let's undo this for the time being. First we need to warn that it'll be phased out. Also, this seems to break the documentation build.

I will check what part is broken, I hope it is only the deprecated module std.stream*

@burner thanks! Also: regarding the fate of std.stream, the main goal is to prevent newcomers to use it, not break old code. The best vehicle to achieve that is a warning at the beginning of the documentation. So a PR for that would be perfect for the time being. Thanks!

@andralex there has been a warning for three years now
https://github.com/D-Programming-Language/phobos/pull/3345

Let's undo this for the time being.

Was this done?

This pull request introduced a regression:
https://issues.dlang.org/show_bug.cgi?id=14712
Not only did this break compilation (which was fixed in #3412), the new code caused the download function to work incorrectly.


Switch from local copies of registry files to use Vulkan-Headers

This was hiding issues in the mock ICD due to the 75 header update.  Fixed that issue, renamed some files and moved to using vulkan registry files from the specified Vulkan-Headers repository.

Updated script name and pushed to Master.


How to control order of imports in generated JS

Summary
I have a bit of a strange setup.
I'm linking in a module with the module syntax:
#[wasm_bindgen(module = "src/js/web.js")]
extern "C" {
    pub type WebInterpreter;
}

And then I have an inline snippet down below:
#[wasm_bindgen(module = r#"class Interpreter extends WebInterpreter {}"#)]

However, when I go to load the page, the generated glue orders the inline snippet above the module, breaking the extends relationship.
import { JSChannel } from './snippets/dioxus-interpreter-js-dce332548ff09d6f/inline0.js';
import { setAttributeInner } from './snippets/dioxus-interpreter-js-dce332548ff09d6f/src/js/web.js';
import { get_form_data } from './snippets/dioxus-web-5003c04febee1e56/inline0.js';
import { get_select_data } from './snippets/dioxus-web-5003c04febee1e56/inline1.js';
import { Dioxus } from './snippets/dioxus-web-5003c04febee1e56/src/eval.js';

Notice how JSChannel from inline0.js is being imported before setAttributeInner in src/js/web.js. And yet in my Rust code they're ordered properly. Is there just no way of getting the order right?

I think they're sorted by the path you're importing from (the final one, e.g. ./snippets/dioxus-interpreter-js-dce332548ff09d6f/inline0.js). That's just for the sake of deterministic outputs though, not any kind of guarantee.
How come they have to be in two separate snippets in the first place?


I like to do a global update every 3 hours or so personally, so I get notified throughout my work day of new chapters. It's not a huge hassle to open it and do it myself, but having it do so automatically would be nice.
Other details
No response
Acknowledgements

[X] I have searched the existing issues and this is a new ticket, NOT a duplicate or related to another open or closed issue.
[X] I have written a short but informative title.
[X] If this is an issue with an official extension, I should be opening an issue in the extensions repository.
[X] I have updated the app to version 0.16.0.
[X] I will fill out all of the requested information in this form.

I think there did used to be more frequent update options, but they've been changed to reduce the load on extensions. Some sources would usually block extensions every few days because peoople using Tachi kept spamming updates, so changes such as reducing the number of updates per day and features such as not updating entries with unread chapters and the newer release predictions have been added to reduce the load on popular extensions.

No


Add URL string as supported input for nearImage()

Hey, we talked about this.
As file paths are a valid parameter for nearImage() search, could we add support for URLs, too?

could also extend this to the toBase64FromMedia() helper so it accepts URLs?


Does not import MVC4

I get the following error once I attempt to create and spread out the components to sub-components.

Everything worked in a single file called BlockStart.jsx, being called from the BlockWizard.cshtml file.
Created a second component called BlockBasic.jsx which is going to be a sub component to BlockStart.jsx.
Running everything I get the error below.
From what I understand in the ReactConfig.cs, I should not have to reference BlockBasic.jsx because BlockStart.jsx has an import.
Using the V8JsEngine if that matters.

Question(s)
Can I have sub-components , I would think I can because your examples show them but I cannot get the examples for MVC4 to run.
BlockBasic.jsx
export class BlockBasic extends React.Component {
    static propTypes = { block: PropTypes.block };

    render() {
        return (

Basic Information

                    Hello in Panel

                    {this.props.block.TenantBlockName}

        );
    }
}

BlockStart.jsx
import { BlockBasic } from './BlockBasic.jsx';

class BlockStart extends React.Component {
    static propTypes = { block : PropTypes.block };
    render() {
        return (

<BlockBasic block={this.props} />
                {this.props.TenantBlockName}

       );
    }
}

BlockWizard.cshtml
@model ApplicantCenter3.Admin.Models.TenantBlockViewModel
<!DOCTYPE html>

    <meta name="viewport" content="width=device-width" />
    <title>Block Wizard</title>

    @Html.React("BlockStart", Model)
    @Html.ReactInitJavaScript()

Error Message at runtime
React.Exceptions.ReactScriptLoadException
  HResult=0x80131500
  Message=Error while loading "~/Scripts/Block/Wizard/BlockBasic.jsx": SyntaxError: Unexpected token export
   at BlockBasic.jsx:199:1 -> export default BlockBasic;
  Source=<Cannot evaluate the exception source>
  StackTrace:
<Cannot evaluate the exception stack trace>

Inner Exception 1:
JsCompilationException: SyntaxError: Unexpected token export
   at BlockBasic.jsx:199:1 -> export default BlockBasic;

Inner Exception 2:
ScriptEngineException: SyntaxError: Unexpected token export

ES6 modules are not yet natively supported without webpack, you tried using that yet?

Since it doesn't look like this is a bug, I'm closing this issue. Please feel free to comment if you'd like some more help 👍


Connection API

How do I use the connection API? I am trying to use the connection.sendDigits() function. It throws me an error of undefined "connection" object.

How did you do that?


Support for SSL using self-signed certs

I tried to use this tool to fetch built structure meta data from a dev host which is reachable only via https, but has only self-signed dummy certs installed. I receive this message:
Unknown error: {"code":"DEPTH_ZERO_SELF_SIGNED_CERT"}
This seems to be a node.js problem but can be overcome using the right modules and implementation (as it seems).
Is it possible to extend liferay-ddmtool such that thid problem can be bypassed at least by explicit configuration? Something like "allowSelfSignedCerts : true"?

Additional resources:
https://github.com/request/request/issues/418

Looks like Node changed a bit around 0.10.x

rejectUnauthorized: If true, the server certificate is verified against the list of supplied CAs. An 'error' event is emitted if verification fails. Verification happens at the connection level, before the HTTP request is sent. Default true.

http://nodejs.org/docs/v0.10.4/api/https.html

Could you test one thing for me: Open the index.js and add the following line at the very top:
process.env.NODE_TLS_REJECT_UNAUTHORIZED = 0;

Does that solve it?

Thanks... result is:
Getting data from server
Downloading id's
Downloading list of sites
Error
Error: Could not find any sites
I interpret this as "yes, this problem is solved" (although having another one now...)

Ouch! Could I ask you to add a new issue (so I can keep this for implementing a nicer way of accepting self signed certs).

OK, I will try some title and content... I hope to meet your expectations ;-)

Just copy paste the previous message and I'm happy ;)

take a look...

or did you mean the full ddm-tool reply?

Haha, I meant the Error: Could not find any sites problem, as I think that's a separate issue, but no problems, let's do it here.
If you find me on skype: emil.oberg or hangout<EMAIL_ADDRESS>It might be easier to debug the problem.

I will come back as necessary, but I think that the problem is not caused by ddm-tool, but by my local setup. If that is succuessfully excluded as a possible reason, I will aks again here. Thanks for the offer however :-)

Perfect! Don't hesitate to come back if the error persist!


Tutorials no longer working

(most) tutorials being tested against CoreOS with using setup-network-environment doesn't seem to work. No longer pulling the correct IPv4 information and leaving it blank during setup.
cc @kelseyhightower

for me it works except what is described in #14
This issue also contains the cloudconfig I have used.


Add network id to EndpointSettings to identify the network

Related to docker/docker#19089
Signed-off-by: Wen Cheng Ma<EMAIL_ADDRESS>

@calavera PTAL

LGTM

Simple enough, looks good.


feat: add clean command

Types of changes

[ ] Bug fix (a non-breaking change which fixes an issue)
[x] New feature (a non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Description

Add a clean command so we can easily clean the nuxt folder. As currently only .nuxt* and dist folders are created during tests and/or builds, a simple find should suffice. If you want we could also separate between build:clean and test:clean but thought that would be too much abstraction
Better to use rimraf as find doesnt work on Windows.
Checklist:

[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly. (PR: #)
[ ] I have added tests to cover my changes (if not applicable, please state why)
[ ] All new and existing tests are passing.

Codecov Report

Merging #4176 into dev will not change coverage.
The diff coverage is n/a.

@@          Coverage Diff          @@
##             dev   #4176   +/-   ##
=====================================
  Coverage   81.8%   81.8%
=====================================
  Files         29      29
  Lines       1561    1561
  Branches     409     409
=====================================
  Hits        1277    1277
  Misses       224     224
  Partials      60      60

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
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Support for constant objects?

Regarding
{
  "react-refresh/only-export-components": [
    "warn",
    { "allowConstantExport": true }
  ]
}

Is there a way to also support objects? E.g.
export const documentProps = {
  // This title and description will override the defaults
  title: 'About SpaceX',
  description: 'Our mission is to explore the galaxy.'
}

I though about it during the implementation but this is very complex to handle if the objet contains reference to other variables. In the case of constant object like this, this should be possible, I will see what I can do (I need to work on upcoming Vite 4.4, so in a few weeks)

So I took a look at this and actually this would be very difficult to do because to be safe the object needs to never be updated from inside the module like this:
export const documentProps = {
  // This title and description will override the defaults
  title: 'About SpaceX',
  description: 'Our mission is to explore the galaxy.'
}

documentProps.title = "About NASA"

In that case the importers will still get the reference to the old export which will not received the modifications.
While this is feasible with static analysis, it's complex and this will need to also be done when transforming the React components. The second part is too independant of the plugin and complex if using SWC, so for now I'm on the side of making this pattern incompatible with FastRefresh.
If you have only two properties to export, is it feasible to se two string export? Is this documentProps coming from a framework?
Other idea that can be explored:

naming conventions: making exceptions for ALL_UPPERCASES object exports or adding a suffix to the object name
using an custom prop as a marker like __refreshStable: true to opt-in into a potential stale export

I use it for e.g. exporting meta data per page. In this case it would be feasible, and also possible to refactor the "problem" away.
Regarding the other ideas: if you think about tackling the issue, my feeling would be that it should work "natively".
Thanks for looking into it.


[Bug]: App crush when send request is too long. SmolChat-v0.0.2

Model: Llama 3.2 1B Q4
App: SmolChat-v0.0.2
Phone: Pixel 6a
OS: GrapheneOS (Android 15)
I push app to the limit and test summarize. I put long summarize text, and app crush.
1st l Characters: 17496
2nd l  Characters: 9903 (if I low to characters 7846 then app work and thinking but later crush)
3rd l  Characters: 3889
To check how long is text I use: https://www.charactercountonline.com/
I make 3 round. And every round I cut summarize text by 50%.
Only 3rd request work, when ask question is not too long.
Maybe app or model have limit and when limit is reaching then send error.
Some other test:

I check this on other app, only PocketPal new version work good.
ChatterUI don't see text and ask me what he can do to me.
SmolChat-v0.0.2 app crush when text is to long.

1st request. App crush. This is Transcript from YouTube
Give me key points:
do the numbers 19.5 67 and 45 mean anything to you stay tuned CU they're going to be important later now some of you may know my background essentially is in high performance Computing I started doing a little bit of the overclocking back in the late 2000s and moved on to uh theoretical chemistry where I used high performance Computing particularly gpus to get my work done now at the time we weren't really speaking about reduced Precision performance in the same way we're speaking about things like machine learning everything at that time and technically still today is all base around fp64 performance that's 64-bit performance the reason why you need that in scientific Fields is simply because of accuracy fp64 uses twice as many bits as fp32 and four times as many bits as fp6 to essentially give you the range and accuracy you need in your data types to to do these hardcore calculations and if you want to go really extreme you could perhaps even go to FP 128 or 256 the thing is in order to get high performance from those codes you need Hardware that natively supports it so native support for fp64 and 64bit processing naturally is more you know hand in hand it goes like that as we're seeing reduced Precision in machine learning we're seeing Hardware support now coming down to things like 16bit and 8 bit and we've covered a load on these Channel however there's one market that's not really getting much love and it's a 64bit market those numbers I gave you were the Tera flop numbers for the last three generations of Nvidia hardware and you noticed that the last one actually goes down showcasing that Nvidia is focusing a lot more on machine learning than it is on its traditional HPC Market but there is one company who is re trying to reinvigorate the HPC Market by providing a native 64-bit processor that's going to be faster than this in this video we're going to talk about next silicon Maverick 2 they're a startup that raised over $300 million of funding and they've got a new compute processor just for you in HPC what's your minimum specification so in this video we're going to go over the basics of what next silicon is going to offer they're going to be showcasing this new chip at supercomputing here in a couple of weeks so will perhaps reserve a more detailed video for that I'm also planning to interview their CEO elad Raz about this uh this chip and why they're going after the HPC Market um right now with all the focus and we're right in the middle of financials week on machine learning it does seem a little weird that here's a company that says we've got a chip that essentially makes your HPC your standard scientific HPC a lot better that's not the only weird thing here um their intelligent computer accelerator their a does something a bit different to compute in order to help accelerate HPC workflow and the idea is that you can do it with just a simple recompile of your software you can bring your C++ you can bring your Fortran um and you don't need to do much than just simply recompile for Target the intelligence in this a the smarts come from a mixture of the hardware and the software normally when we speak about CPUs gpus even even as6 we're talking about a pipeline of compute elements and you essentially build your software depending on whether you're building for CPU whether you're building for GPU whether you're building for Asic and you essentially have to know the architecture underlying it you have to know where what it's fast at what it's slow at and ideally transfer your or transmogrify your algorithms to meet it and next silicon are doing something a little bit different what they've designed isn't a CPU it isn't a GPU it isn't an Asic and it doesn't really fit in fpga either it's somewhere in the middle of all of those and it does this by intelligently looking at your compute workflow so a standard HPC algorithm or any code actually we typically see as a linear set of instructions that simply go from A to B and when we introduced multicore Computing we realized oh these two um compute processes this addition this multiplication we could separate do simultaneously and then bring together and what we get is the start of parallelism now parallelism has limits it's called armar law where it essentially says you can amplify all your parallel code um essentially to be uh the quickest it can be in reality and you're still limited by serial but on top of that we're now looking at HPC codes that might have um you know if then else and you have likely taken paths and unlikely taken paths however in HBC when we're talking about say weather modeling or physics simulations or F or even things like Eda you end up essentially taking the most likely path most of the time what NEX silicons architecture does and it's not necessarily a deep dive into how they're doing it here but just as a brief overview is they have systems that monitor your code and your workflow and it determines where the likely paths are and where the unlikely paths are changes the way that the chip computes your code computes your mathematics such that it spends more of the chip doing the more like code and less of the chip doing the less likely code right now if you take a CPU a GPU or even an Asic it has to be built for one of those and typically it's built for the most likely code when you get least likely code you know the branches that are less often taken that usually introduces an element that slows your HPC down and I want to go through next silicon slides here and this one in particular so here on slide 12 it's you know it shows that you have likely flow and what their compute chip doing here is a flow-based design so it looks at your compute in the same way it would do you know a graph Network and then it identifies where you're likely to be Computing and how you're where you're not likely to be Computing so it does this during compulation but also while your code is running and that's the key element here so right now you're looking you know at a chip where you'll have some likely flow some unlikely flow and depending on your memory bandwidth needs or compute needs um you know something like a GPU will naturally fall into that however with the Telemetry that is recorded as your code is run but also as part of that you know compile time knowledge that it gains it will change how much of the chip is dedicated towards the likely flow towards the parallel elements the unlikely flow can still do parallel stuff but it's unlikely so you don't need much silicon for it and as a result you end up with most of the chip going towards the likely flow and part of the chip the unlikely flow but the key thing here is it that it has the right balance needed gpus and CPUs and as6 are fixed their new architecture here essentially changes that Paradigm on its head but it has to be smart on the hardware and software level to be able to do that and you might think this just sounds like a an fpg GA that's um doing partial reconfigurations uh during uh runtime it's not that they've told me it's not that and we might hear more um at supercomputer supercomputing and then uh into next year as this chip rolls out a bit more but the idea is that if you know the flow you can essentially paralyze it across the compute elements of the chip now you may notice the chip here has hpms so if we go up to the top stack um the standard chip has you know one compute engine and four hbms there also that's on the PCI card they're also going to have an O form factor which is essentially double this with two compute chips and four 8 hbms and the key thing here is to go um back to those numbers that I gave you at the beginning the uh performance of modernday gpus I actually did some numbers here because people might think well is the HBC Market even worth going after at this point given machine learning so high so I was looking through the uh essentially the 2020 and the 2024 top top 500 supercomputing numbers and what we have here is that if we just look at um out of top 500 which of them are using accelerators in 2020 it's 146 and in 2024 it's 193 so it's there's a slow progression up to to using accelerators the reason why most supercomputers still CPU right now is because um of flexibility you're running Dynamic codes you're maybe changing things in Industry sometimes or especially with machine learning the computer you're doing is a known fixed Chunk in the HPC world it's constantly changing and you have to deal with that so the number of uh supercomputers here using accelerators is going up slowly over time uh and that right now they're still mostly focused on Nvidia and that's just due to the fact that Nvidia since 2007 2009 has been putting Cuda into the hands of academics um and the National Laboratories in the us if we go down to exactly what Nvidia gpus they're using in 2020 more than 100 were using Volta the V100 chip from 2017 uh we had our first incling of ampere at that point because ampere had just been launched and then we had some some you Dro down into Pascal and Kepler fast forward four years to the last top 500 um showcase and we're now more weighted heavily towards the newer chips there's still 48 systems running Volta but 82 systems running ampere a100 um or equivalent and the key thing here is that if we're looking at the fp64 performance of these chips you know it's still 19 and a half 30 um Tera flops of fp64 performance um that's using non-matrix math if you use Matrix math um Hopper 100 goes up to 60 next silicon's value prop here and I'll go back to the next silicon slides um is that they want to showcase that using their Hardware they can offer four times the performance per watt not only of the hopper systems here but of Blackwell um and then comparing that to CPUs there's a 20 X increase in performance you do use um next silicon's uh tool tool set but it should be more simply a recompile because of that smart layer inside their system and they're calling it here runtime adaptive acceleration so I want to show you this graph because this is perhaps the important one which we'll touch upon in a future video you start running your application and you get the sort of performance at the at the lower end here somewhere between a CPU and GPU and as your application runs and especially for some of these things like weather modeling um or physics simulations FEA nuclear these things run can run for weeks and weeks and weeks and weeks over time the chip and the runtime on the chip will change to better balance the likely paths versus the unlikely paths um and then so over time you end up with running essentially better power efficiency and more performance at the high end and they're showcasing this as an example with just the PCI card um at this time now one of the reasons they're doing this is that um AMD and Nvidia and Intel are you know in some manner of form always pitching to HPC by saying we have massive Vector engines we have Matrix engines and tensor cores you can run your compute on us the problem there is that most of that compute has to be um you have to spend you know anywhere up to three years or even more translating your code from what is the traditional CPU code into a GPU code so you have to know What GPU you're targeting you have to manage uh the memory buffers you have to get the most um how to get the best compute out of it one of the issues I had back in the day um was that I was doing memory reads across cach line so I was hitting a penalty there and I didn't realize that for six months with next silicon's design with this new Maverick chip and I'm looking forward to seeing it in action the point here is that it eliminates the need for a vendor specific language you just get your code that you've already done um I believe you just put in a couple of lines to say Target next silicon you add in the library and Away you go and over time it will adapt to your code and to your workflow um one of the key elements here is simply just time to deployment people looking at accelerators understand that when they deploy those systems and you know some of these systems take months maybe even years to stand up you need to spend that time um essentially building proof of Concepts to Showcase that your deployment was worth the investment here with this chip the goal is that the proof of concept is very easy to do and therefore the justification for building out lots of Hardware um you know perhaps at universities or Labs or in industry is pretty easy pretty easy um that you know that's that that's the argument here um they've also done this sort of benefit comparison and take it from it what you will and obviously single thread performance when you got a parallel ship is not going to be that high compared to a CPU but the point here is that it's compatible and portable like a CPU it's ease of use is like a CPU the flexibility is of a CPU however the power efficiency and the throughput are better than CPU and even better than GPU or fpga um these are some lofty claims um but it's going to be it's going to be interesting to see how it runs these are the form factors now you may be wondering why this is Maverick Gen 2 gen one was more of a test chip but on board you do have 100 Gig ethernet hbm3 there's multi-layer caches and embedded cores and PCI the Dual die design for oam that's going to go more into say the six 100 Watts side of the business and in terms of you know performance this is built on tsmc N5 I believe um the yeah I've already said 300 600 watts pc pc Gen 5 they will be giving ex you know numbers more so in the new year I should point that out um they are sampling chips to Partners today so obviously F trying to get the bugs out of the system or you know first silicon bring up for for partners is always going to be important like that they are using hbm 3E one of the key elements in HPC um the same with machine learning is memory capacity and memory bandwidth so they're also adding that into the mix and also node in Connect right now it's 100 Gig ethernet but you also have um the PCI connection to do a bit more what I really want to see and have is one of these cards in my hand which will probably happen at supercomputing so they were there last year and technically Maverick 2 was on display um here's a photo with me and the CEO from from then and yeah they were quite Hush Hush back then because you know they don't want to necessarily promote and public until they're ready and it sounds like they're going to be ready over the next few months in terms of their PR I'm reading here they're she already shipping to dozens of customers with volume beginning in early 25 to fulfill a strong backlog they have a variety of organizations from US Department of energy so the National Labs and leading academic but also in the commercial space such as Financial Services energy manufacturing and life science verticles they are initiating an early adopter program um through Partners like penguin Solutions and Dell Technologies so no doubt they will have some systems to show at supercomputing as well um and yeah they also highlight again they'll be at supercomputing Atlanta here in a couple of weeks so for full disclosure here um while this video wasn't sponsored at all or anything by next cicon they have just signed with me as a client so I'm going to be helping them craft this message um as it evolves as they go through volume deployment and then hopefully fingers crossed I convince them to do an architecture Deep dive at some point you know when it's fully rolled out they are most likely working towards you know next Generation stuff the way this architecture sounds I wonder what the benefit is um other than just just going to new process nodes do we need um better computer hbm support um is there a need for more networking as some of these codes evolve and honestly we do really have to ask where the machine learning aspect is here this chip they've said is fp64 focused so that might leave some lay of the lands that there may be other machine learning Focus chips in the future that'll be interesting to see I have seen some criticism online that um you know being smart through compilers is difficult and but the thing is next silicon here isn't doing it simply through the compiler it's also built into the design of the Chip And as it runs so um going to be interes see what the metrics are there and how it deals with that because if you suddenly go from a you know fixed Compu environment like a GPU to a more flexible environment that does likely paths and unlikely paths that may affect the power consumption and a power efficiency but you also have to manage that on the chip um so I wonder you know what they have um in line to manage with that there's also other questions such as you know virtualization and multi-tenant support and no doubt we'll get that in time but that's been the Maverick 2 um it's been announced now uh before supercomputing so they can get all the questions at the event and if you happen to be at supercomputing I will see you there if you like this content there are multiple ways to support the channel you can like And subscribe this video and many thanks for doing so there's also patreon which gives you access to our Discord there's a merchandise store and a newsletter links in the description for all of you who do contribute thank you you are keeping me well fed
This 2nd request make app crash too. I cut text about 50% smaller
Give me key points:
do the numbers 19.5 67 and 45 mean anything to you stay tuned CU they're going to be important later now some of you may know my background essentially is in high performance Computing I started doing a little bit of the overclocking back in the late 2000s and moved on to uh theoretical chemistry where I used high performance Computing particularly gpus to get my work done now at the time we weren't really speaking about reduced Precision performance in the same way we're speaking about things like machine learning everything at that time and technically still today is all base around fp64 performance that's 64-bit performance the reason why you need that in scientific Fields is simply because of accuracy fp64 uses twice as many bits as fp32 and four times as many bits as fp6 to essentially give you the range and accuracy you need in your data types to to do these hardcore calculations and if you want to go really extreme you could perhaps even go to FP 128 or 256 the thing is in order to get high performance from those codes you need Hardware that natively supports it so native support for fp64 and 64bit processing naturally is more you know hand in hand it goes like that as we're seeing reduced Precision in machine learning we're seeing Hardware support now coming down to things like 16bit and 8 bit and we've covered a load on these Channel however there's one market that's not really getting much love and it's a 64bit market those numbers I gave you were the Tera flop numbers for the last three generations of Nvidia hardware and you noticed that the last one actually goes down showcasing that Nvidia is focusing a lot more on machine learning than it is on its traditional HPC Market but there is one company who is re trying to reinvigorate the HPC Market by providing a native 64-bit processor that's going to be faster than this in this video we're going to talk about next silicon Maverick 2 they're a startup that raised over $300 million of funding and they've got a new compute processor just for you in HPC what's your minimum specification so in this video we're going to go over the basics of what next silicon is going to offer they're going to be showcasing this new chip at supercomputing here in a couple of weeks so will perhaps reserve a more detailed video for that I'm also planning to interview their CEO elad Raz about this uh this chip and why they're going after the HPC Market um right now with all the focus and we're right in the middle of financials week on machine learning it does seem a little weird that here's a company that says we've got a chip that essentially makes your HPC your standard scientific HPC a lot better that's not the only weird thing here um their intelligent computer accelerator their a does something a bit different to compute in order to help accelerate HPC workflow and the idea is that you can do it with just a simple recompile of your software you can bring your C++ you can bring your Fortran um and you don't need to do much than just simply recompile for Target the intelligence in this a the smarts come from a mixture of the hardware and the software normally when we speak about CPUs gpus even even as6 we're talking about a pipeline of compute elements and you essentially build your software depending on whether you're building for CPU whether you're building for GPU whether you're building for Asic and you essentially have to know the architecture underlying it you have to know where what it's fast at what it's slow at and ideally transfer your or transmogrify your algorithms to meet it and next silicon are doing something a little bit different what they've designed isn't a CPU it isn't a GPU it isn't an Asic and it doesn't really fit in fpga either it's somewhere in the middle of all of those and it does this by intelligently looking at your compute workflow so a standard HPC algorithm or any code actually we typically see as a linear set of instructions that simply go from A to B and when we introduced multicore Computing we realized oh these two um compute processes this addition this multiplication we could separate do simultaneously and then bring together and what we get is the start of parallelism now parallelism has limits it's called armar law where it essentially says you can amplify all your parallel code um essentially to be uh the quickest it can be in reality and you're still limited by serial but on top of that we're now looking at HPC codes that might have um you know if then else and you have likely taken paths and unlikely taken paths however in HBC when we're talking about say weather modeling or physics simulations or F or even things like Eda you end up essentially taking the most likely path most of the time what NEX silicons architecture does and it's not necessarily a deep dive into how they're doing it here but just as a brief overview is they have systems that monitor your code and your workflow and it determines where the likely paths are and where the unlikely paths are changes the way that the chip computes your code computes your mathematics such that it spends more of the chip doing the more like code and less of the chip doing the less likely code right now if you take a CPU a GPU or even an Asic it has to be built for one of those and typically it's built for the most likely code when you get least likely code you know the branches that are less often taken that usually introduces an element that slows your HPC down and I want to go through next silicon slides here and this one in particular so here on slide 12 it's you know it shows that you have likely flow and what their compute chip doing here is a flow-based design so it looks at your compute in the same way it would do you know a graph Network and then it identifies where you're likely to be Computing and how you're where you're not likely to be Computing so it does this during compulation but also while your code is running and that's the key element here so right now you're looking you know at a chip where you'll have some likely flow some unlikely flow and depending on your memory bandwidth needs or compute needs um you know something like a GPU will naturally fall into that however with the Telemetry that is recorded as your code is run but also as part of that you know compile time knowledge that it gains it will change how much of the chip is dedicated towards the likely flow towards the parallel elements the unlikely flow can still do parallel stuff but it's unlikely so you don't need much silicon for it and as a result you end up with most of the chip going towards the likely flow and part of the chip the unlikely flow but the key thing here is it that it has the right balance needed gpus and CPUs and as6 are fixed their new architecture here essentially changes that Paradigm on its head but it has to be smart on the hardware and software level to be able to do that and you might think this just sounds like a an fpg GA that's um doing partial reconfigurations uh during uh runtime it's not that they've told me it's not that and we might hear more um at supercomputer supercomputing and then uh into next year as this chip rolls out a bit more but the idea is that if you know the flow you can essentially paralyze it across the compute elements of the chip now you may notice the chip here has hpms so if we go up to the top stack um the standard chip has you know one compute engine and four hbms there also that's on the PCI card they're also going to have an O form factor which is essentially double this with two compute chips and four 8 hbms and the key thing here is to go um back to those numbers that I gave you at the beginning the uh performance of modernday gpus I actually did some numbers here because people might think well is the HBC Market even worth going after at this point given machine learning so high so I was looking through the uh essentially the 2020 and the 2024 top top 500 supercomputing numbers and what we have here is that if we just look at um out of top 500 which of them are using accelerators in 2020 it's 146 and in 2024 it's 193 so it's there's a slow progression up to to using accelerators the reason why most supercomputers still CPU right now is because um of flexibility you're running Dynamic codes you're maybe changing things in Industry sometimes or especially with machine learning the computer you're doing is a known fixed Chunk in the HPC world it's constantly changing and you have to deal with that so the number of uh supercomputers here using accelerators is going up slowly over time uh and that right now they're still mostly focused on Nvidia and that's just due to the fact that Nvidia since 2007 2009 has been putting Cuda into the hands of academics um and the National Laboratories in the us if we go down to exactly what Nvidia gpus they're using in 2020 more than 100 were using Volta the V100 chip from 2017 uh we had our first incling of ampere at that point because ampere had just been launched and then we had some some you Dro down into Pascal and Kepler fast forward four years to the last top 500 um showcase and we're now more weighted heavily towards the newer chips there's still 48 systems running Volta but 82 systems running ampere a100 um or equivalent and the key thing here is that if we're looking at the fp64 performance of these chips you know it's still 19 and a half 30 um Tera flops of fp64 performance um that's using non-matrix math if you use Matrix math um Hopper 100 goes up to 60 next silicon's value prop here and I'll go back to the next silicon slides um is that they want to showcase that using their Hardware they can offer four times the performance per watt not only of the hopper systems here but of Blackwell um and then comparing that to CPUs there's a 20 X increase in performance you do use um next silicon's
3rd request. If I cut this last summary by 50% then work:
Give me key points:
do the numbers 19.5 67 and 45 mean anything to you stay tuned CU they're going to be important later now some of you may know my background essentially is in high performance Computing I started doing a little bit of the overclocking back in the late 2000s and moved on to uh theoretical chemistry where I used high performance Computing particularly gpus to get my work done now at the time we weren't really speaking about reduced Precision performance in the same way we're speaking about things like machine learning everything at that time and technically still today is all base around fp64 performance that's 64-bit performance the reason why you need that in scientific Fields is simply because of accuracy fp64 uses twice as many bits as fp32 and four times as many bits as fp6 to essentially give you the range and accuracy you need in your data types to to do these hardcore calculations and if you want to go really extreme you could perhaps even go to FP 128 or 256 the thing is in order to get high performance from those codes you need Hardware that natively supports it so native support for fp64 and 64bit processing naturally is more you know hand in hand it goes like that as we're seeing reduced Precision in machine learning we're seeing Hardware support now coming down to things like 16bit and 8 bit and we've covered a load on these Channel however there's one market that's not really getting much love and it's a 64bit market those numbers I gave you were the Tera flop numbers for the last three generations of Nvidia hardware and you noticed that the last one actually goes down showcasing that Nvidia is focusing a lot more on machine learning than it is on its traditional HPC Market but there is one company who is re trying to reinvigorate the HPC Market by providing a native 64-bit processor that's going to be faster than this in this video we're going to talk about next silicon Maverick 2 they're a startup that raised over $300 million of funding and they've got a new compute processor just for you in HPC what's your minimum specification so in this video we're going to go over the basics of what next silicon is going to offer they're going to be showcasing this new chip at supercomputing here in a couple of weeks so will perhaps reserve a more detailed video for that I'm also planning to interview their CEO elad Raz about this uh this chip and why they're going after the HPC Market um right now with all the focus and we're right in the middle of financials week on machine learning it does seem a little weird that here's a company that says we've got a chip that essentially makes your HPC your standard scientific HPC a lot better that's not the only weird thing here um their intelligent computer accelerator their a does something a bit different to compute in order to help accelerate HPC workflow and the idea is that you can do it with just a simple recompile of your software you can bring your C++ you can bring your Fortran um and you don't need to do much than just simply recompile for Target the intelligence in this a the smarts come from a mixture of the hardware and the software normally when we speak about CPUs gpus even even as6 we're talking about a pipeline of compute elements and you essentially build your software depending on whether you're building for CPU whether you're building for GPU whether you're building for Asic and you essentially have to know the architecture underlying it you have to know where what it's fast at what it's slow at and ideally transfer your or transmogrify your algorithms to meet it and next silicon are doing something a little bit different what they've designed isn't a CPU it isn't a GPU it isn't an Asic and it doesn't really fit in fpga either it's somewhere in the middle of all of those and it does this by intelligently looking at your compute workflow

Thank you for highlighting the issue @bi4key!
Larger texts do not seem to fit in the model's context length, which might be the reason for the error. Also, there has to be some element on the screen which shows the context size of the current model.


Heroic Trial Does Not Show In Groupie Raid Lockout

When you do Trial of the Crusader on Heroic, your character's name is not listed in the Groupie lockout list.
For example, character A does Trial of the Crusader on normal.  When you check Groupie, under Trial of the Crusader, character A's name  is listed.  Now character B does Trial of the Crusader on heroic.  When you check Groupie, under Trial of the Crusader, character A's name  is listed but character B's name is not.

Hey @KicaMwMw ,
I don't play any more, but I think @TannerShmoog wanted to do a few updates.
I stopped playing back in April or so. It's not clear to me that very many people ever used this / still use it.
Just to set expectations, I don't think it's highly likely any updates are coming to this add-on.
Sorry mate.

As one of the people using this literally just for the raid lockout list across multiple characters, first of all thank you very much for your work. Any update fixing this issue would be awesome although I can totally understand if it's not happening if you don't play anymore. If you have an idea what could cause this issue or point me in the right direction to maybe fix it myself that would also be appreciated.
Thanks again for making this it has the best cross character lockout list out of all the different addons I tried.

Hi kathelas, could you run the following function for me on a character you're currently locked on and paste me the output that would help. The most likely issue is that the names given in the return of GetSavedInstanceInfo() are not listed anywhere and are for some reason different than localized names in every other location (i.e. The Sunwell instead of Sunwell Plateau is one we encountered in TBC). Unfortunately neither of us play anymore, so I can't run the command myself.
function()     for i = 1, GetNumSavedInstances() do         local ... = GetSavedInstanceInfo(i)         print(...)     end end

Thank you very much for the quick response.
Sorry this took a while, cause I wasn't home this week and have no lockouts for TOGC right now and had to ask someone in guild to do this for me. The function you gave me also didn't work (maybe I'm just too stupid), so I just manually called GetSavedInstanceInfo and printed all the output (looking at this: https://wowwiki-archive.fandom.com/wiki/API_GetSavedInstanceInfo)
25man heroic:

10man heroic:

If you would like anything else, like maybe the info for a non heroic I would have to look for someone who didn't do heroic this week.
Thank you for your help.

This should be all I need, I'll have a look at it tonight. Likely the issue is that we internally recognize heroic trial as "trial of the grand crusader". There's a method built for dealing with this just need to expand the data

Ive pushed a potential fix here 2e098cb846679ddceef81eb9e819d792d9f10555 I dont have a sub though, so before I make it an official build, do you mind installing the addon from the main branch of this repo manually and checking that the lockout now shows? Nothing else should have broken. Just log in to a character that has a lockout once you've done it this week and wait 3-5 seconds after login. If it looks good Ill push the build to curse

Yep, got it. Thank you.
My earliest TOGC 25m raid this week will be on Thursday, might be doing some 10m before. Will let you know ASAP.

Looks like it's working now.
Thank you!

Weird to call it "Heroic Trial of the Grand Crusader" isn't it?
https://www.wowhead.com/wotlk/zone=4722/trial-of-the-crusader
It's Trial of the Crusader, or "Heroic" Mode is "Trial of the Grand Crusader" -- but adding "Heroic Trial of the Grand Crusader" feels redundant.

I can fix that but it would just be a hard coded display only exception, fixing it properly requires a pretty big refactor as its coming from the data sheet where it is reffered to for disambiguation reasons internally like, everywhere in the entire addon


lnkd.in False Positive

The domain lnkd.in is just LinkedIn's URL shortener service, for serving shorter linkedin.com URLs.

Phishing.Database 👈 @funilrys

/move to Mitchellkrogza/Phishing.Database


Fix parsing of comma separated values in --crate-type flag

What does this PR try to resolve?
According to the documentation the --crate-type flag accepts a comma separated list of crate types. However, these are never actually split into individual items and passed verbatim to rustc.
Since cargo fails to associate cases such as 'staticlib,cdylib' to a specific crate type internally, it has to invoke rustc to determine the output file types for this unknown crate type, which returns only the first file type of the first crate type in the list. Consequently cargo will be looking only for a single '.a' artifact on Linux to be copied to the target directory.
Fix this by splitting the list of provided crate types into individual items before further processing them.
Fixes #14498
How should we test and review this PR?
Updated corresponding test cases
Additional information

@bors r+

:pushpin: Commit fb672fa2a9a59eefbb7b7fdf63f9f264a37a0578 has been approved by weihanglo
It is now in the queue for this repository.

:hourglass: Testing commit fb672fa2a9a59eefbb7b7fdf63f9f264a37a0578 with merge 0b390cd484749424a81ec97881d75aeb09f62146...

:sunny: Test successful - checks-actions
Approved by: weihanglo
Pushing 0b390cd484749424a81ec97881d75aeb09f62146 to master...

:sunny: Test successful - checks-actions
Approved by: weihanglo
Pushing 0b390cd484749424a81ec97881d75aeb09f62146 to master...

:eyes: Test was successful, but fast-forwarding failed: 422 Changes must be made through a pull request.


git clean should do git clean -n

Currently, typing git clean is not sufficient. One needs to either give it -n or -f . The question then is, why does -n have to be specified explicitly?
In terms of usability, it would make sense to have git clean simply show what would be removed, which would be the same as git clean -n. If the user indeed wants to remove the files, they can specify -f flag (same as current behavior)
Is there any particular reason for why this is not the case?

Never mind,  fixed by doing git config clean.requireForce false
Sorry for the noise


Use different rt_compare for functions generated from dcmpl and fcmpl

In case when dcmpl or fcmpl is present in bytecode, use
function $rt_compare_l(a, b) {
    return a > b ? 1 : a < b ? -1 : a === b ? 0 : -1;
}

instead of rt_compare (which is used for translating dcmpg and fcmpg.

I don't think it's very important and that many apps depend on this subtle difference between dcmpg/dmpgl opcodes. There are many examples of TeaVM not behaving exactly like JVM, and it's still does not make much difference in practical cases.


Default slippage tolerance (tested in incognito) is a custom 5%

Should be set to the 0.5% option

Fixed here

Fixed here


No parameter named "graph_configs" in LlamaToolkit

Hello, I followed the example here, but currently we don't have any attribute graph_configs in LlamaToolkit class. This class only support index_configs

Ah looks like the notebook is somewhat outdated. Will update this!

I can do it if you want. please refer me to good resources to make contribution. thanks.

I have faced the same issue. Hey @Disiok if graph_configs is removed, Is there an alternative way to pass that to LlamaToolkit now?
toolkit = LlamaToolkit(
    index_configs=index_configs,
    graph_configs=[graph_config]
)


Complete Zomato Landing Page clone

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

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

Expected behavior
A clear and concise description of what you expected to happen.
Screenshots
If applicable, add screenshots to help explain your problem.
Desktop (please complete the following information):

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

Smartphone (please complete the following information):

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

Additional context
Add any other context about the problem here.
I would like to complete the landing page clone of Zomato as I have proper knowledge of html and css .Please assign it to me @TusharKesarwani

Hey @Tusharjoshi1703 I can do this can you please assign this task to me.
I have knowledge of Html5 and CSS3.


Savage Worlds exploding dice +wild die

Is it possible to have dice explode (if the result is the highest number on the die roll it again and add them together)? right now when you type explode it adds a d6 which doesn't explode and adds it to your total.
I would also like to see an option to roll two dice, 1d8 and 1d6 for example, and take the higher result for the Savage Worlds wild die mechanic.


Try to build suggested type

Attempts to resolve query comment from #476  But I am unsure if I can make the syntax any easier than it is now.
Just posted if anyone else is attempting this

Closing this. Going to leave it as it is.


Development of GPy docs

Some initial proposed changes to the GPy docs (relates to #820). Not sure whether this is too incremental for a PR, at present. It's still work in progress and I'm mostly putting it up as a vehicle to get some internal feedback from my team.

Here's a link to the WIP built docs on readthedocs:
https://rse-sheffield-gpy.readthedocs.io/en/docs/

Codecov Report

Merging #822 into devel will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##            devel     #822   +/-   ##
=======================================
  Coverage   54.07%   54.07%
=======================================
  Files         210      210
  Lines       21365    21365
  Branches     2889     2889
=======================================
  Hits        11553    11553
  Misses       9262     9262
  Partials      550      550


[HELP] App never connects to the league client

I downloaded the latest release and ran the LeagueBrodcast.exe. But the app always says I'm disconnected from the client even after going into a game.

Please use the issue template


Placeholder selector is not vendor prefixed

It seems placeholder styles are not working in Chrome, seemingly because the selector ::placeholder is not supported (needs to be ::-webkit-input-placeholder) and as far as I could tell from a quick look through the code, the selectors are not processed by the prefixer, only rules are.
Question is, since the cases where the selector needs to be prefixed somehow are quite rare and tricky to handle in a generic way (for example, to get placeholder styling to work cross-browser you need to duplicate the rule blocks iirc), is it better to handle these things case by case or find some more generic solution (i.e pass all selectors through a prefixer)?

Good catch, I didn't know this. I should be able to add it. As a workaround for now, try this undocumented method - add(':-webkit-input-placeholder', style) (note the single colon, not double)

Cool! I ended up with this:
const placeholder = (x) => ({
  ...add(':placeholder', x),
  ...add(':-webkit-input-placeholder', x),
  ...add(':-moz-placeholder', x),
  ...add(':-ms-input-placeholder', x),
})

✌

the next version of glamor should do this automatically

Placeholder is still not vendor prefixing:
import React from 'react'
import {css} from 'glamor'

const styles = {
  '::placeholder': {
    color: 'red'
  }
}

export default () => (
  <input className={css(styles)} placeholder='Test' />
)

Results in this output in the head stylesheet:
.css-f6kjmy::placeholder,[data-css-f6kjmy]::placeholder,.css-f6kjmy[data-simulate-placeholder],[data-css-f6kjmy][data-simulate-placeholder]{color:red;}

ah, it doesn't do it for the nested version, only when using the helper. will fix.

fixed in 2.20.14

It isn't working right now.
Glamor put all vendor prefixes in a single comma separated rule: https://github.com/threepointone/glamor/blob/09dd49dac0ca7c96c45da4dad420ece6e82379de/src/index.js#L322-L325
But it doesn't work. I found why here: http://stackoverflow.com/a/23338422/2379685

...if any selector in your comma separated list is not recognized by your browser, it skips the whole rule and goes on to the next.

You can test it in this fiddle using chrome:
https://jsfiddle.net/Lcjfkrb2/
Also, you can go to https://autoprefixer.github.io/ and paste:
input::placeholder {
  color: red
}

The result will be:
input::-webkit-input-placeholder {
  color: red
}
input::-moz-placeholder {
  color: red
}
input:-ms-input-placeholder {
  color: red
}
input::placeholder {
  color: red
}

Couldn't this be handled by autoprefixer instead of hard coded?

Done!


Getting unsigned values for INT column

Set up to use row-format replication from MySQL 5.6.5, I'm getting large positive values in place of small negative ones for a column defined as INT which should be 32-bit signed. Here's a part of the debug log:
2016/01/07 20:04:27 [DEBUG] === UpdateRowsEventV2 ===
Date: 2016-01-07 15:48:58
Log position: 1007
Event size: 72
TableID: 74
Flags: 1
Column count: 4
Values:
--
0:566
1:2379
2:4294967295
3:"2016-01-07 15:44:32"
--
0:566
1:2379
2:4294967294
3:"2016-01-07 15:44:32"

The column '2' value was changed from -1 (received as<PHONE_NUMBER>) to -2 (received as<PHONE_NUMBER>).
I looked at the TableMapEvent for this table and didn't see anywhere that an unsigned 'meta' bit was set.
I even changed the schema of column '1' to be unsigned and I still didn't see any unsigned 'meta' bit in the debug output. There's a lot of binary data and it's possible I missed it, but the first case of an INT field -1 => -2 being reported as<PHONE_NUMBER> =><PHONE_NUMBER> stands.

I think what's going on here is with binary replication the 'bits' are meant to be transferred and applied, as signed/unsigned have the same bit pattern, no problem. What the library is doing is being helpful returning int64 for all integral types to reduce the number of type cases to handle. Where this goes off is widening an 8, 16, 24, or 32 signed value.
e.g. return int64(binary.LittleEndian.Uint32(data)) will return values like<PHONE_NUMBER> for -1.
I tested some changes in a fork to always sign-extend while widening (even for the INT24 case to int32 then int64). This worked much better.
I continued on to then return the various int8 thru int64 interface{} types meaning the user will need to expect these. The advantage is that there's no possibility of data mangling (-1 -><PHONE_NUMBER>) and if you want the unsigned version a cast will convert.
I'll see about making a Pull Request to see this. My branch has import package renaming (not yet using Go 1.5 vendor'ing feature) that needs to be tidied before I do so.
Note: There might be a similar issue with date handling for (negative) dates before Jan. 1, 1970, but I didn't really look into that.

Can we close it now?

Thanks for accepting PR#27, we can close the PR. Please also consider PR#28 as well before closing the issue.
The follow-up PR https://github.com/siddontang/go-mysql/pull/28 returns smaller (and unsigned) integer or float32 types for interface{}. There's notes there for pros/cons. I think the upside is greater with a slight non-backward compatibility (users have to also handle int8, uint8, float32, etc in addition to int64 and float64).

Thanks, I will close it and move another. :-)


Wait for webview to finish load content

Largs html documents is now fully loaded when UIPrintInteractionController is presented. This makes the plugin work with large html as well. Before, only e.g. 67/92 pages was presented and printed.

Thanks @ErikWallin, this adjustment saved me a headache!


Execution fails when there is blank space in filepath

Can we add quotes to the ${args.join(' ')} part? When the path has blank spaces it fails to find the file.

Originally posted by @CanCodes in 0a40aea

This is what gets ran behind:
$ effekt some-path-here/tasks and dance/main.effekt --backend js --includes /some-path-here/
some-path-here/tasks (No such file or directory)
and (No such file or directory)
dance/main.effekt (No such file or directory)

since there are spaces instead of \ , i think it detects each as a different route here. I have fixed this manually by either by replacing blank spaces with \ or putting the path in double quotes.


nsd_pycortex_db error, Missing the the related matrices.xfms for subj01-8"

How to solove the inconsistency with the different db?

The db you provided:

The source db:

Error info:
/home/jack/anaconda3/envs/brainnet/bin/python3.9 /mnt/d/github projects/clip2brain-main/src/visualize_in_pycortex.py
Namespace(subj=1, mask_sig=True, sig_method='negtail_fdr', alpha=0.05, show_pcs=False, show_clustering=False, show_more=False, show_repr_sim=False, vis_method='quickflat')
Traceback (most recent call last):
File "/mnt/d/github projects/clip2brain-main/src/visualize_in_pycortex.py", line 510, in
volumes["clip-ViT-last R^2 NC"] = make_volume(
File "/mnt/d/github projects/clip2brain-main/src/visualize_in_pycortex.py", line 136, in make_volume
mask = cortex.utils.get_cortical_mask(
File "/home/jack/anaconda3/envs/brainnet/lib/python3.9/site-packages/cortex/utils.py", line 184, in get_cortical_mask
return get_mapper(subject, xfmname, type=type).mask
File "/home/jack/anaconda3/envs/brainnet/lib/python3.9/site-packages/cortex/utils.py", line 32, in call
return self._load()(*args, **kwargs)
File "/home/jack/anaconda3/envs/brainnet/lib/python3.9/site-packages/cortex/mapper/init.py", line 32, in get_mapper
xfmfile = db.get_paths(subject)['xfmdir'].format(xfmname=xfmname)
File "/home/jack/anaconda3/envs/brainnet/lib/python3.9/site-packages/cortex/database.py", line 672, in get_paths
for surf in os.listdir(surfpath):
FileNotFoundError: [Errno 2] No such file or directory: '/home/jack/anaconda3/envs/brainnet/share/pycortex/db/subj01/surfaces'
Process finished with exit code 1

running the visualize_in_pycortex.py with the error - Missing the matrices.xfm?:
 vol_data = cortex.dataset.Volume(      all_vals,      "subj%02d" % subj,      "func1pt0_to_anat0pt8_autoFSbbr",      mask=mask,      cmap=cmap,      vmin=vmin,      vmax=vmax,  )

Errof info:
Traceback (most recent call last):
File "/mnt/d/github projects/clip2brain-main/src/visualize_in_pycortex.py", line 461, in
volumes["clip-laion2b R^2"] = make_volume(
File "/mnt/d/github projects/clip2brain-main/src/visualize_in_pycortex.py", line 229, in make_volume
vol_data = cortex.dataset.Volume(
File "/home/jack/anaconda3/envs/brainnet/lib/python3.9/site-packages/cortex/dataset/views.py", line 283, in init
super(Volume, self).init(data, subject, xfmname, mask=mask,
File "/home/jack/anaconda3/envs/brainnet/lib/python3.9/site-packages/cortex/dataset/braindata.py", line 146, in init
self._check_size(mask)
File "/home/jack/anaconda3/envs/brainnet/lib/python3.9/site-packages/cortex/dataset/braindata.py", line 240, in _check_size
xfm = db.get_xfm(self.subject, self.xfmname)
File "/home/jack/anaconda3/envs/brainnet/lib/python3.9/site-packages/cortex/database.py", line 463, in get_xfm
with open(fname) as f:
FileNotFoundError: [Errno 2] No such file or directory: '/home/jack/anaconda3/envs/brainnet/share/pycortex/db/subj01/transforms/func1pt0_to_anat0pt8_autoFSbbr/matrices.xfm'

Everything works fine, note that download the individual files of each subject rather than merge the whole files. I lost the .xfm files while uncompressing the whole .zip with goggle cloud.


⚠ Bofrost.lu has degraded performance

In 0db2b08, Bofrost.lu (https://www.bofrost.lu) experienced degraded performance:

HTTP code: 200
Response time: 1129 ms

Resolved: Bofrost.lu performance has improved in edc79b0 after 6 minutes.


Add FreshmintQueue contract

This PR introduces the FreshmintQueue contract, which provides a Queue interface for storing and distributing NFTs via a queue.
It also includes CollectionQueue, an implementation of Queue that is backed by a standard NonFungibleToken.Collection resource.
This contract can be used to distribute NFTs in the same order in which they are minted, which is an important feature for Freshmint.

one addition to consider is to add a function that adds all IDs from the underlying collection, rather than having a single insertID
I can understand if its a worry that this function may almost always exceed gas limits though, so i'm okay with this not being added as well if that is a concern.

@aishairzay Could this be a function that takes a list of IDs? I'm not sure its useful to automatically grab the IDs from the collection because they won't be ordered, which I think is undesirable in most cases.
pub fun insertIDs(ids: [UInt64]) {
  self.ids = self.ids.concat(ids)
}

I think this could be useful if self.ids.concat(id) is cheaper than for id in ids { self.ids.push(id) }.
Then for small collections you can do queue.insertIDs(collection.getIDs()).
But I think I'll add that later if there is a need.

Will the claim nft transaction change as a result of this PR?

@fkenji No, the claim transaction stays the same.


PR: Update to #6

Continuing the work in #6.

Updated reports
Updated database schema

Closed due to incorrect merging branch


Support for events

Are there any plans to support discrete events a la https://openreview.net/forum?id=kW_zpEmMLdP ?

I don't have any plans for that at the moment but would be open for a PR that does implement them.


More bad words

I added some french words and reworked some items.
Simplification examples:

merde -> merdeuse + merdeux
branle -> branler, branlette, branleur, branleuse

Some Quebec bad words

Calis -> Calisse
Osti -> Ostie
Plotte
Anus
Marde (same a merde but different spelling they use in Québec)

I'm bad at Git and I'm using Git Graph in VSCode, I don't know how to "delete" commited changes. Sorry for the mess.

All good on the commits. Thank you for the changes, very helpful 👍


Generate dynamically SPAN id's using rangy highlighter module

Hi
I am using rangy serialization and highlighter module to select and highlight text on HTML file. Currently I am using below code to highlight the content of HTML file -
applier = rangy.createClassApplier("highlight", {
ignoreWhiteSpace : true,
tagNames : [ "span", "a" ]
applier.applyToSelection(frame.contentWindow);
Now my requirement is to add tooltip on this highlightion.? How can I achieve that ??
One thing I was thinking since I am passing span tag to highlight the content , I can add tooltip on this span element itself. But currently they don't have any unqiue id to identity the content. I need to add id's on these span elements so that i can add tooltip on them .Is it possible to add dynamic id's on these span elements?  If so how to achieve the same ??

Hi
For this case, you can add elementsAttributes in the "classApplier" code.
for Ex:
this.highlighter.addClassApplier(rangy.createClassApplier("highlight", {
ignoreWhiteSpace: true,
tagNames: ["span","a"],
elementAttributes " {
"id" = "Unique-Id",
"onClick" = "onClickHighlight(this);"
}));

Hey, unfortunately it's not clear how to apply really unique attribute as we use addClassApplier on initialization.
Any thoughts? Thx!


refactor: use ya.sync to simplify the code

Needs the latest main branch of Yazi at the moment.

Hi, I reverted the commit because I can't get it working on my end.
I installed the git version from cargo, so I'm in
❯ yazi --version
yazi 0.2.3 (dc1718f 2024-02-09)

That's so weird, have you changed the plugin command by removing the --sync option?

Yeah, however the issue now is about the folder used in save_bookmarks. It's nil for some reason.


migaloo-chain Cosmos Subql Starter

Caution. Check sources. Network USE now ONLY default cosmos protobuf NO custom.

@web3cdnservices,
What does this mean? "Caution. Check sources. Network USE now ONLY default cosmos protobuf NO custom."
Also, can you use a mainnet endpoint instead of testnet?
Thanks.

Also, can you use a mainnet endpoint instead of testnet?
 **READY**
What does this mean? "Caution. Check sources. Network USE now ONLY default cosmos protobuf NO custom."
The network uses only standard protobuf. No custom

@web3cdnservices you always miss two important files (potentially becuase you are on windows and dont see hidden files)
Please make sure to include the .github directory and the .gitignore - they are exactly the same for all chains


[SPARK-10979] [SparkR] Sparkrmerge: Add merge to DataFrame with R signature

Add merge function to DataFrame, which supports R signature.
https://stat.ethz.ch/R-manual/R-devel/library/base/html/merge.html

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This breaks an existing API signature though, is it a good idea to incompatible API change?

cc @sun-rui @falaki

Hi @felixcheung,
what do you mean by "it breaks an existing api" ?
I can call both merge from base and from SparkR ....
it is similar to arrange, summary, ... etc.

I mean for a SparkR user who has code written to call merge like
merge(df, df2, df$name == df2$name, "outer")

would no longer work right?

Hi Felix, true. The merge was added recently for the purpose to make it more R-friendly, but since it's signature is very different from R's I have decided to change it. We discussed it in jiras.
Well, I can still also keep the old signature and make it deprecated.
https://issues.apache.org/jira/browse/SPARK-9318
https://issues.apache.org/jira/browse/SPARK-10979

I'd let others to chime in, IMO we should not have breaking API changes but instead deprecate and remove only in a later release.

Personally, I think it is better to support merge() with R signature than support merge() with scala DataFrame signature (where only name is familiar to R users but not its signature). So my proposal is:
Remove current merge() definition and implementation;
Note there is no need to define merge() , as merge() is an existing S3 generic function defined in the R base package;
Implement merge() as an S3 method in a new separate R file, maybe RDataFrame.R (can anyone propose a better name). DataFrame.R is expected to contain R wrappers for Scala DataFrame functions, while the new R file is expected to contain R functions with R signature operating on DataFrame.

+1 on R-like signature, just want to call out we should be careful with breaking API changes

I think if we add a new RDataFrame.R file, we will need to consider to move some of the functions from DataFrame.R  to RDataFrame.R too. Sometimes it might be hard to figure out if a function should be in DataFrame.R or in RDataFrame.R.

Hmm I'm not fully convinced we need a new file RDataFrame.R -- We already have a bunch of functions like [ and $<- which are not in the Scala API. I think thats fine. If this file is getting too long / unwieldy we can break it up more semantically like SelectFuncions.R etc. Lets not do that in this change however.

Also I think its fine to break backwards compatibility on rare occasions -- SparkR is still marked as an alpha component, so minor changes are fine. But we should note this down in the documentation & include it in the release notes etc.
@NarineK Could you open a new JIRA for including this documentation changes ? You can assign it to me or @rxin

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I see. I can remove the check

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yes, I'll do that. Let me know if you have any more comments ...

@NarineK Could you also bring this up to date with master branch ?

Hi @felixcheung,
thanks for your comments.

I'm a bit confused - why create a seq of indices? instead can't we use lapply on allColNames?
yes, that's true. I could have used smth like:
lapply(allColNames, function(colNames)){
colName ...
...
})

Thnx!
Also, nit, why pass allColNames if we could just do names(x) here?
yes, I can do names(x) and names(y) in the method.

what if colName is "test", suffix is "_x" but there is already a column with the name "test_x"?
I think that's not good. I could check if the alias names already exist in the dataframe.
If they do, I can show an error telling the user to use a different suffix.

does the suffix to be used here depends on the type of join?
No, the suffix doesn't depend on join type

please add a test sort = T
yes, I'll add that

Hi @felixcheung,
thanks for your comments.

I'm a bit confused - why create a seq of indices? instead can't we use lapply on allColNames?
yes, that's true. I could have used smth like:
lapply(allColNames, function(colNames)){
colName ...
...
})

Thnx!

Also, nit, why pass allColNames if we could just do names(x) here?
yes, I can do names(x) and names(y) in the method.

what if colName is "test", suffix is "_x" but there is already a column with the name "test_x"? I think that's not good. I could check if the alias names already exist in the dataframe. If they do, I can show an error telling the user to use a different suffix.

does the suffix to be used here depends on the type of join?
No, the suffix doesn't depend on join type

please add a test sort = T yes, I'll add that

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Hi @felixcheung  and @sun-rui , I've worked on your suggestions! Thanks!
Also, I've noticed that the Cartesian product has in general a problem:
let's say my df is:
age    name_a
1  NA Michael
2  30    Andy
3  19  Justin
df2 is:
name_b test

1 Michael  yes
2    Andy   no
3  Justin  yes
4     Bob  yes
when I do join(df, df2), I expect to see Cartesian product.  That is -  the output has to have nrow(df)*nrow(df2) rows - see also https://stat.ethz.ch/R-manual/R-devel/library/base/html/merge.html
but what I see is:
age    name test
1  NA Michael  yes
2  NA    Andy   no
3  NA  Justin  yes
4  NA     Bob  yes
5  30 Michael  yes
6  30    Andy   no
This is less than expected.
Could you please verify this ?
Thanks,
Narine

@NarineK , I verified that cartesian works fine. Did you use head() to print rows of the join result? Note that head() by default only prints the first 6 rows.

Thanks for verifying @sun-rui, 6 is my unlucky number. But why 6 and not 5 or maybe 10 :)))

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Added all suggestions. thanks!

looks good

Created: https://issues.apache.org/jira/browse/SPARK-11238 for the documentation change.
@shivaram @rxin - Would you, please, take a look at it ?

Thanks @NarineK LGTM and I just had one minor inline comment.
@sun-rui Any other comments ?

+1 for more R-like merge signature. Thanks for doing it.

cool! I can help you with scala and python :)

Created https://issues.apache.org/jira/browse/SPARK-11250

if Scala side can support this, R implementation can be simplified later.

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added documentation

Thanks @NarineK -- LGTM. Merging this


[wip] support binary artifact archives that require first level component stripping

motivation: it is common for archives to include top level directory, e.g. GitHub release archives
changes:

when downloading binary artifacts archives, perform first level component stripping if deemed necessary
add informational diagnostics to help debug binary artifacts downloads
add tests

@swift-ci please smoke test

@swift-ci please smoke test

@swift-ci please smoke test

@swift-ci please smoke test


Fixing typo in README

Thank you for the pull request, however the use of the British/Non-American spelling is deliberate :)

It's still missing an a in that case, you have authoristion as opposed to authorisation

Right you are!

Thanks :)


Add "see full code" links

See ASA page. Add full code links under each snippet to signal where the context is.

https://github.com/algorand/docs/commit/55e4918737357cab3ee5142dd325e8be02199a83


Emails attached from Outlook to Salesforce (using my email to Salesforce Link) is not rolled Up

I have created a roll up Field Last activity for Zycus in the Accounts object. This field is a date field. Basically we have divided activities in two categories valid and invalid. This field rolls up the latest valid activity date. However from past 15 - 20 days this field does not count the emails that are attached from Outlook to Salesforce from the my email to salesforce link. Please check the issue asap.

Hi @preetishetty25, i am afraid i am not familar with that functionality in Salesforce, nor do i have Outlook / Exchange server to test it. Is their anything else difference between the emails that are and are not getting counted? Does it count if you manually run the rollup via the Calculate button on the rollup? Also what happens if you use the All Rows field on the rollup?

Hi @afawcett This happens only with emails that are attached from Outlook. It doesnt count even if I manually run the roll up.

@preetishetty25 are you rolling up activity or email message? Which outlook connector are you using?

Both email message and activities appear in the object "activities". So I am rolling up both email messages and activities. This was not a problem before but suddenly emails which are attached from Outlook using "My emails to Salesforce link" are not being rolled up.
I am attaching the screenshot for your reference.

any update on this @afawcett

I am wondering if the Apex Trigger is not being run by the platform when the Outlook integration is used? Not sure why it would not tbh. But if you can enable Apex Debug logs and do some testing that might help confirm this either way.

@preetishetty25 Let me know if this is still an issue?


Only run satellite test in Enterprise mode

This PR just deactivates a test in Community version, as the tested feature is only available enterprise.
No Production change included.

Jenkins:
http://jenkins.arangodb.biz:8080/view/PR/job/arangodb-matrix-pr/13478/

Jenkins:
http://jenkins.arangodb.biz:8080/view/PR/job/arangodb-matrix-pr/13478/

Jenkins Blue

Jenkins Blue


Problem running constant pool checker over Java8 code

If the ConstantPoolChecker is in use, it can't cope with Java8 elements. For example: https://github.com/ratpack/example-ratpack-gradle-java-app

:+1: would love to have this working :)

:+1:

:+1:

+1

:+1:


When will code be available?

Hey there! The paper is very interesting, and congratulations on being published at CVPR!
Now that CVPR is over, can we expect that the code release is imminent?

Hi, thanks for your interest in our work. The code is now released

Great! Thanks


⚠ Adacta-fintech.com has degraded performance

In c70173a, Adacta-fintech.com (https://www.adacta-fintech.com) experienced degraded performance:

HTTP code: 200
Response time: 1416 ms

Resolved: Adacta-fintech.com performance has improved in 3f3232a.


fixed small typo in tutorial

Small Typo
I have removed a redundant extra word within docs/tutorials/extra-models.md
Current:

The output model should do not have a password

Proposed:

The output model should not have a password

A very minor typo. Thanks for the great tutorial and effort that has gone into creating the documentation. :100:

Oops... Thanks! Good catch.
I'm glad you're enjoying it!


Handle clickable [url] tags in print_rich() editor output log

Since this uses OS.shell_open(), this allows the use of any standard URL including file:// paths, mailto:, custom protocols set up by the user, etc.

This closes https://github.com/godotengine/godot-proposals/issues/8879.

Testing project: test_editor_print_rich_meta.zip

Thanks!


Could do with some examples

Hey there!
Short of your tests, I'm kinda in the dark about how you use this code.
I'd happily work with you to come up with some examples - perhaps you could share a couple of really simple ones and we can work together to illuminate the features of Weaver from there?

Hi!
Yeah, that'd be good. Thanks!
The primary reason I made this library was for working with docker/kubernetes deployment configuration in albatross. The main use case there is for having separate templates which share a common weaver config in order to keep shared data in sync (e.g. referencing a stateful set's name from a service, using a generated docker image tag from a kubernetes stateful set, sharing as much config as possible between dev and prod deployments...).
I use these libraries for primarily closed-source work at my full-time job, but I can pull some stuff in and remove any sensitive data.
I also think that the pattern of templating data could be useful in many other contexts as well, so I'll include some examples for custom tags as well.
I haven't done much work to make this library accessible, but I'm happy to step it up a bit if people like you find it useful or interesting.
Are there any specific features that you're looking for information on, or any specific things you're trying to accomplish with weaver?

I watched your talk about scripting Kubernetes and thought this would be a
far better way to create k8s objects than Helm or something else that tries
to template YAML. So I think we're on the same page :)
On Sun, 21 Jul 2019, 20:09 Scot Brown<EMAIL_ADDRESS>wrote:

Hi!
Yeah, that'd be good. Thanks!
The primary reason I made this library was for working with
docker/kubernetes deployment configuration in albatross
https://github.com/SVMBrown/albatross. The main use case there is for
having separate templates which share a common weaver config in order to
keep shared data in sync (e.g. referencing a stateful set's name from a
service, using a generated docker image tag from a kubernetes stateful set,
sharing as much config as possible between dev and prod deployments...).
I use these libraries for primarily closed-source work at my full-time
job, but I can pull some stuff in and remove any sensitive data.
I also think that the pattern of templating data could be useful in many
other contexts as well, so I'll include some examples for custom tags as
well.
I haven't done much work to make this library accessible, but I'm happy to
step it up a bit if people like you find it useful or interesting.
Are there any specific features that you're looking for information on, or
any specific things you're trying to accomplish with weaver?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/SVMBrown/weaver/issues/2?email_source=notifications&email_token=ABXBZYHKX7IBKJ3N3PKBRKTQASQ43A5CNFSM4IFSZ5Q2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD2OIUXQ#issuecomment-513575518,
or mute the thread
https://github.com/notifications/unsubscribe-auth/ABXBZYEL3Y3ZFPEXL6CC4RDQASQ43ANCNFSM4IFSZ5QQ
.


[GOBBLIN-937] fix help text and align it with variable names

Dear Gobblin maintainers,
Please accept this PR. I understand that it will not be reviewed until I have checked off all the steps below!
JIRA

[x] My PR addresses the following Gobblin JIRA issues and references them in the PR title. For example, "[GOBBLIN-XXX] My Gobblin PR"

https://issues.apache.org/jira/browse/GOBBLIN-937

Description

[x] Here are some details about my PR, including screenshots (if applicable):
fix help text and align it with variable names

Tests

[ ] My PR adds the following unit tests OR does not need testing for this extremely good reason: N/A

Commits

[x] My commits all reference JIRA issues in their subject lines, and I have squashed multiple commits if they address the same issue. In addition, my commits follow the guidelines from "How to write a good git commit message":

Subject is separated from body by a blank line
Subject is limited to 50 characters
Subject does not end with a period
Subject uses the imperative mood ("add", not "adding")
Body wraps at 72 characters
Body explains "what" and "why", not "how"

@Will-Lo , @sv2000 , can u pls review and merge this? Thanks

Codecov Report

Merging #2786 into master will increase coverage by <.01%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##             master    #2786      +/-   ##
============================================
+ Coverage     45.32%   45.33%   +<.01%
- Complexity     8858     8861       +3
============================================
  Files          1894     1894
  Lines         70874    70874
  Branches       7794     7794
============================================
+ Hits          32123    32129       +6
+ Misses        35788    35779       -9
- Partials       2963     2966       +3

Impacted Files
Coverage Δ
Complexity Δ

...lin/util/filesystem/FileSystemInstrumentation.java
85.71% <0%> (-7.15%)
3% <0%> (ø)

...main/java/org/apache/gobblin/yarn/YarnService.java
15.68% <0%> (+0.84%)
4% <0%> (+1%)
:arrow_up:

...e/gobblin/runtime/locks/ZookeeperBasedJobLock.java
64.44% <0%> (+1.11%)
16% <0%> (+1%)
:arrow_up:

...in/java/org/apache/gobblin/cluster/HelixUtils.java
35.51% <0%> (+2.8%)
12% <0%> (+1%)
:arrow_up:

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