Setting autoConnect to false prevents login with setVisible(true)

Describe the bug
Setting autoConnect to false from WalletProvider prevents PhantonWallet from getting presented. Setting it to true, fixes it.
To Reproduce

Set autoConnect to false.
Set isVisible(true)
Tap Phantom Wallet
See that nothing happened.
Setup in a default Next.js example app.

Expected behavior
Should prompt the user to login; similar to when autoConnect is set to true.
Screenshots
If applicable, add screenshots to help explain your problem.
Desktop (please complete the following information):

OS: Mac OSX
Browser: Chrome
Version: 98

Additional context
"@solana/wallet-adapter-base": "^0.9.3",
"@solana/wallet-adapter-react": "^0.15.2",
"@solana/wallet-adapter-react-ui": "^0.9.3",
"@solana/wallet-adapter-wallets": "^0.14.2",

Here is an example custom button I am building:
import { useWallet } from "@solana/wallet-adapter-react";
import { useWalletModal } from "@solana/wallet-adapter-react-ui";
import Button, { ButtonStyle } from "./Button";
import { useMemo } from "react";
import { truncateAddress } from "../utils/address-utils";

const WalletButton = () => {
  const { connected, publicKey, disconnect, select, connect } = useWallet();
  const { setVisible } = useWalletModal();
  const base58 = useMemo(() => publicKey?.toBase58(), [publicKey]);
  const walletName = useMemo(() => {
    if (base58) {
      return truncateAddress(base58);
    }
  }, [base58]);

  async function didTapWalletButton() {
    if (connected) {
      await navigator.clipboard.writeText(base58!);
      await disconnect()
    } else {
      setVisible(true);
    }
  }

  return (
    <Button
      title={walletName || "Connect Wallet"}
      didTapButton={didTapWalletButton}
      style={ButtonStyle.Small}
    />
  );
};

WalletButton.defaultProps = {};

export default WalletButton;

Here is the main wrapper inside _app.tsx
import { WalletAdapterNetwork } from "@solana/wallet-adapter-base";
import {
  ConnectionProvider,
  WalletProvider,
} from "@solana/wallet-adapter-react";
import { WalletModalProvider } from "@solana/wallet-adapter-react-ui";
import {
  LedgerWalletAdapter,
  PhantomWalletAdapter,
  SlopeWalletAdapter,
  SolflareWalletAdapter,
  SolletExtensionWalletAdapter,
  SolletWalletAdapter,
  TorusWalletAdapter,
} from "@solana/wallet-adapter-wallets";
import { clusterApiUrl } from<EMAIL_ADDRESS>import { AppProps } from "next/app";
import { FC, useMemo } from "react";

require("@solana/wallet-adapter-react-ui/styles.css");
require("../styles/globals.css");

const App: FC<AppProps> = ({ Component, pageProps }) => {
  const network = WalletAdapterNetwork.Devnet;
  const endpoint = useMemo(() => clusterApiUrl(network), [network]);
  const wallets = useMemo(
    () => [
      new PhantomWalletAdapter(),
      new SolflareWalletAdapter(),
      new SlopeWalletAdapter(),
      new TorusWalletAdapter(),
      new LedgerWalletAdapter(),
      new SolletWalletAdapter({ network }),
      new SolletExtensionWalletAdapter({ network }),
    ],
    [network]
  );

  return (
    <>
      <ConnectionProvider endpoint={endpoint}>
        <WalletProvider wallets={wallets} autoConnect={false}>
          <WalletModalProvider>
            <Component {...pageProps} />
          </WalletModalProvider>
        </WalletProvider>
      </ConnectionProvider>
    </>
  );
};

export default App;

This isn't what autoConnect does. It's not related in any way to the modal being visible. Please check the code.

Related: https://github.com/solana-labs/wallet-adapter/issues/273#issuecomment-1017061229
If you don't set autoConnect (it's false by default) you are responsible for calling connect after the wallet is selected.

See implementation: https://github.com/solana-labs/wallet-adapter/blob/fd543782d9fed22c564855308216dacfc75c0c32/packages/core/react/src/WalletProvider.tsx#L99-L125

hey @zkhalapyan did you figure out how to make phantom not auto-popup until the user clicks connect?

My guess is that it's from Phantom, not from wallet adapter. @jordansexton there isn't an eager connect logic built in, correct?

Please read the implementation 🙂 The auto connect functionality is more nuanced than most aspects of the React lib.

For context, the symptom that @scottwilson312  and I have are trying to debug is phantom wallet randomly/automatically popping up when the user comes back to the site after they have initially authenticated.
Looking at the autoConnect use above, there are a lot of states being checked, so could be from this path. @scottwilson312  would fork this repo, place a breakpoint and see if you can debug this path.
My question was if there is another code path outside of autoConnect that is responsible for eagerly connecting.

Alrighty, so I got this working how I want with Phantom @zkhalapyan. Turning off autoConnect succesfully got rid of phantom  auto-popping up. However, the side effect of that is after you click Phantom from the list of wallets on the modal, the WalletMultiButton changes from "select wallet" to "connect", and the user needs to press the changed button to connect.
If you don't want the user to have to do the two clicks, you can grab wallet from the useWallet hook and throw that into a useEffect and call `connect when you see wallet become not-null.
However, if they have already selected Phantom and that's saved in localStorage, then we're back at the Popup problem. My solution was to extend WalletMultiButton, and set a global variable once they click for the first time, and only run the above stuff in useEffect if they've already clicked.
import { WalletModalProvider, WalletMultiButton, WalletConnectButton } from '@solana/wallet-adapter-react-ui';
import { useWallet } from '@solana/wallet-adapter-react';
import  Waves from "./assets/icons/Waves"
import {
    WalletReadyState,
} from '@solana/wallet-adapter-base';

require('@solana/wallet-adapter-react-ui/styles.css');

const WalletButton = (props) => {

  const { name, readyState, wallet, connect, connecting, connected } = useWallet();

  const content = useMemo(() => {
      if (connecting) return 'Connecting ...';
      if (connected) {
        props.cart.onWalletConnected()
        return 'Connected';
      }
      if (wallet) return 'Connect';
      return 'Connect Wallet';
  }, [connecting, connected, wallet]);

  useEffect(() => {
    if(wallet && window.CLICKED_WALLET){
      connect().catch(() => {}); // Ignore this error because it'll be handled by the provider
    }
  }, [wallet]);

  return (
    <WalletMultiButton>
      <div className='button' onClick={()=>window.CLICKED_WALLET = true}>
        {content}
        <Waves/>
      </div>
    </WalletMultiButton>
  )

}

window.CLICKED_WALLET = true

It's not meant to be pretty or an example of good code 🤣🤣🤣


Does not work with React Native Web / Expo Web

Cool component, will you add web support?

+1

Yes. It would be great.


Trying to sign in with deactivated user, doesn't throw error

Rancher versions: 2.0 master 7/23
Steps to Reproduce:

Create a local user
Deactivate local user
Try to log in as deactivated user

Results:  The login screen flashes and password field resets, but there is no error saying unauthorized.

Version - 2.0 master 7/26
Verified


plugins(jwt): support more algorithms

Description
Update docs to reflect recent changes in the JWT plugins.
Added support for:

ES512
PS256
PS384
PS512
EdDSA

@kong-docs Should we restructure the docs a bit to use Conditional version tags more effectively?
Checklist

[x] Review label added
[ ] Conditional version tags added, if applicable.

Jira: https://konghq.atlassian.net/browse/KAG-4029

@jschmid1 we definitely can, what do you have in mind? What issues are you facing?

@fabianrbz The list of supported algorithms is dependent on the kong version. Currently the list is maintained as an inline string which makes it awkward to conditionally render this list. How about maintaining the list somewhere and render the string containing the supported algorithms? Alternatively, we could pull this information from the schema description?

oh! Yeah, that would be great, I didn't realize we were updating that table manually.
Unfortunately, I don't think those fields are returned in the API response.
It looks like they are not defined in the schema.lua  but in a daos.lua

This can expose it http :8001/schemas/jwt_secrets Would that be possible?

I've created a Jira ticket to track that work, we should review/merge this PR in the meantime though


Generalise toposort to LinkView

Sorry, messed up my git manip, will be ready soon!

It's ready now!

Side note: this could also be implemented on any petgraph, but thought that it would be odd to have a petgraph-only algo in portgraph, so I prefered the LinkView-implementation.


Adds a how-to page for promoting css changes

Why are these changes being introduced:

The process of making sure that CSS changes take effect quickly, and identifying whether a deploy has been successful, is somewhat tricky because of the SCSS compilation process, combined with aggressive browser caching.

Relevant ticket(s):

https://mitlibraries.atlassian.net/browse/lm-278

How does this address that need:

This documents the best workflow we've yet found for promoting CSS changes and forcing them to take effect on the Test and Live tiers.
The how-to document also includes a brief discussion of some future process changes that we could adopt, which might make these steps less necessary in the future.

Document any side effects to this change:

This is just documentation changes, so there should be no side effects.

Developer
Secrets

[ ] No secrets are affected

Documentation

[ ] Project documentation has been updated

Accessibility

[ ] There are no accessibility-related changes (documentation only)

Stakeholder approval

[ ] Stakeholder approval is not needed

Dependencies
NO dependencies are updated
Code Reviewer

[ ] The commit message is clear and follows our guidelines
(not just this pull request message)
[ ] The changes have been verified
[ ] The documentation has been updated or is unnecessary
[ ] New dependencies are appropriate or there were no changes

Okay @JPrevost - could you take another look at this change please?


Simplify welcome layouts

Description
Works on #2643
What changes did you make and why?
Refactored welcome layouts so they're much more structurally similar, moved repeatedly used bullet to it's own file, removed a load of unused xml properties.
Tests performed
Tested 2.10.1-debug-refactor-welcome-layouts~c8f018810 in portrait mode
TODO
Landscape mode

Codecov Report

Merging #2741 into master will increase coverage by <.01%.
The diff coverage is 0%.

@@            Coverage Diff            @@
##           master   #2741      +/-   ##
=========================================
+ Coverage    2.72%   2.72%   +<.01%
=========================================
  Files         267     267
  Lines       12801   12790      -11
  Branches     1137    1137
=========================================
  Hits          349     349
+ Misses      12426   12415      -11
  Partials       26      26

Impacted Files
Coverage Δ

...main/java/fr/free/nrw/commons/WelcomeActivity.java
0% <ø> (ø)
:arrow_up:

.../java/fr/free/nrw/commons/WelcomePagerAdapter.java
0% <0%> (ø)
:arrow_up:

Continue to review full report at Codecov.

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Files that might be useful for people in the future looking at this PR, that I compiled from older versions of the app

Tested 2.10.1-debug-refactor-welcome-layouts~c23e6c82f
Welcome activity works
Beta Commons Upload
All automated tests pass

@neslihanturan Thanks for merging!


Should give a message if curl fails to install.

Thank you for your contribution to slacktee! Your PR looks good!


Print out nested Cloud Build test commands

This will allow for easier test failure reproduction. Also, move the ODA test to use us-west1-a, as it consistently fails in us-east1-b.

/gcbrun

/gcbrun


Include liquidity pool trades in trades endpoint

https://github.com/stellar/go/issues/3810 will implement ingestion of liquidity pool trades. After that is complete we want to include liquidity pool trades in the trades response.
We will add an extra query parameter to the trades endpoint, trade_type, which defaults to all.
GET /trades?trade_type={orderbook,liquidity_pools,all}
The trade_type filter will work in addition to the base and counter asset pair filters. However, Horizon will reject requests which attempt to set trade_type=liquidity_pools when using the offer id filter.
The JSON definition of a trade will contain an extra field trade_type which indicates whether the trade occurred against the DEX or on a liquidity pool.
Orderbook Trade JSON
The price fraction will represent its numerator and denominator values as strings to be consistent with the liquidity pool trade JSON object.
{
"id": "157235845014249474-0",
"paging_token": "157235845014249474-0",
"ledger_close_time": "2021-07-29T21:10:53Z",
"offer_id": "738916928",
"trade_type": "orderbook",
"base_offer_id": "4768921863441637378",
"base_account": "GAPP4CS5KSZSHF6A24JWZ2W6MZKPCQKCAW44Y7FFX46WS76WMBDYWKWH",
"base_amount": "0.0002007",
"base_asset_type": "native",
"counter_offer_id": "738916928",
"counter_account": "GDW634JZX3VMEF2RZTCJTT34RITIMNX46QOGTYHCJEJL3MM7BLOQ6HOW",
"counter_amount": "0.0022300",
"counter_asset_type": "credit_alphanum4",
"counter_asset_code": "VZT",
"counter_asset_issuer": "GBENYXZDFFR2J4F4DB3YPBBAM244TXYOTIOOUQI5DBT3OKUU4ZJ2M7NO",
"base_is_seller": false,
"price": {
"n": “10000000”,
"d": “899997”
}
}
Liquidity Pool Trade JSON
The price fraction will represent its numerator and denominator values as strings because they will be 64 bit integers.
Fields that refer to offer ids (e.g. base_offer_id or counter_offer_id) are removed from the response object.
Only one side of the trade will be executed by an account (either base_account or counter_account). The other side of the trade will be executed against a liquidity pool (either base_liquidity_pool_id or counter_liquidity_pool_id).
{
  "id": "157235845014249474-0",
  "paging_token": "157235845014249474-0",
  "ledger_close_time": "2021-07-29T21:10:53Z",
  "trade_type": "liquidity_pool",
  "base_liquidity_pool_id": "abcdef",
  "liquidity_pool_fee_bp": 30,
  "base_amount": "0.0002007",
  "base_asset_type": "native",
  "counter_account": "GDW634JZX3VMEF2RZTCJTT34RITIMNX46QOGTYHCJEJL3MM7BLOQ6HOW",
  "counter_amount": "0.0022300",
  "counter_asset_type": "credit_alphanum4",
  "counter_asset_code": "VZT",
  "counter_asset_issuer": "GBENYXZDFFR2J4F4DB3YPBBAM244TXYOTIOOUQI5DBT3OKUU4ZJ2M7NO",
  "base_is_seller": false,
  "price": {
    "n": “10000000”,
    "d": “899997”
  }
}

Horizon will also provide an endpoint for retrieving all trades for a given liquidity pool:
GET /liquidity_pools/<pool-id>/trades
The response for this endpoint will only contain trade objects of type “liquidity_pool.”
More details about this API can be found in https://docs.google.com/document/d/1pXL8kr1a2vfYSap9T67R-g72B_WWbaE1YsLMa04OgoU/edit#

I noticed that offer_id field has been removed in #3857 but it's present in the example response above. Any reason why?

@bartekn offer_id should be removed from the example response. It has been marked as deprecated for a while now:
https://developers.stellar.org/api/resources/trades/object/


Update Kangal cluster role and additionalPrinterColumns

Description:
ES - 4110
Current CRD configuration misses Age attribute to show how long the load test resource exists. It also misses a cluster role
to update LoadTest resource.
k get lt
NAME                   TYPE     PHASE      AGE
loadtest-funky-bison   JMeter   finished   8d

👍


canon-cups-ufr2 can't find rastertoufr2

Describe the bug
Installation of my Canon Color imageCLASS MF644Cdw results in the following error message within the cups interface, as well as a complete inability to print:
Idle - "File "/nix/store/lkgpynyyzfgg0r6bwh1l17r60vpgwq15-cups-progs/lib/cups/filter/rastertoufr2" not available: No such file or directory"

Steps To Reproduce
Steps to reproduce the behavior:

Have the following in configuration.nix on either unstable or staging-22.05 (the version of canon-cups-ufr2 in 21.05 is way too old to have support for my printer)

services.printing = {
    enable = true;
    drivers = with pkgs; [
      canon-cups-ufr2
    ];
  };

  # Enable avahi for printer discovery
  services.avahi = {
    enable = true;
    nssmdns = true;
  };

Attempt to install printer through cups using either autodiscovery or manually specifying the ip address, specifying canon for the make and ~Canon MF642C/643C/644C UFR II (en) for the model
Attempt to print something or visit the cups printer status page

Expected behavior
Cups is able to find the required filter
Additional context
rastertoufr2 is indeed not a part of cups-progs, from what I was able to figure out, it looks like its supposed to be provided by canon-cups-ufr2 but the required binary is either not installed properly, the drivers need a patch/workaround to find it on nixos, or both
Notify maintainers
@dmayle
Metadata
 - system: `"x86_64-linux"`
 - host os: `Linux 5.17.7-zen1, NixOS, 22.05 (Quokka), 22.05.20220525.1774dcc`
 - multi-user?: `yes`
 - sandbox: `yes`
 - version: `nix-env (Nix) 2.8.1`
 - channels(root): `"nixos, nixos-unstable"`
 - channels(nathan): `"nixpkgs-unstable"`
 - nixpkgs: `/nix/var/nix/profiles/per-user/root/channels/nixos`

I have essentially the identical issue with canon-cups-ufr2 as described by @nmccarty (my portion of configuration.nix is the same): cups finds and adds the printer (an imageCLASS MF445dw) and its Canon MF440 Series UFR II driver successfully, but then fails with status,
Idle - "File "/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertoufr2" not available: No such file or directory"

And the rastertoufr2 filter is indeed MIA:
$ find /nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs | grep rasterto
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/.rastertopclx-wrapped
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/.rastertops-wrapped
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertopwg
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertohp
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertopclx
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/.rastertopdf-wrapped
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertops
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/.rastertoescpx-wrapped
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/.rastertopclm-wrapped
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertoescpx
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertopdf
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertopclm
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertolabel
/nix/store/bj5s6j8bs4q692syp8cxi5y49yjj70hc-cups-progs/lib/cups/filter/rastertoepson

But I downloaded the latest driver from CANON (UFR II/UFRII LT Printer Driver for Linux V5.50) and the filter is indeed there:
$ tar --strip-components=3 -xf linux-UFRII-drv-v550-us-00.tar.gz linux-UFRII-drv-v550-us/x64/RPM/cnrdrvcups-ufr2-us-5.50-1.00.x86_64.rpm
$ rpm2targz cnrdrvcups-ufr2-us-5.50-1.00.x86_64.rpm
$ tar -tf ./cnrdrvcups-ufr2-us-5.50-1.00.x86_64.tar.gz | grep rastertoufr2
./usr/lib/cups/filter/rastertoufr2

My system:
$ sudo nix-info -m
 - system: `"x86_64-linux"`isn't included
 - host os: `Linux 5.15.49, NixOS, 22.05 (Quokka), 22.05.1257.cd90e773eae`
 - multi-user?: `yes`
 - sandbox: `yes`
 - version: `nix-env (Nix) 2.8.1`
 - nixpkgs: `/nix/var/nix/profiles/per-user/root/channels/nixos`

Thanks to all --

@SuperSandro2000 awesome, thank you :-)

@SuperSandro2000
Sorry for my ignorance, but could you point me to something explaining how to install your patch? or what file I should edit on an existing cups install? I'm a little lost when it comes to using the source code.  I've searched through cups source and everywhere I can think of trying to understand what file needs edited with your changes without asking like an idiot LOL

The easiest would be to use nixos-unstable.

canon-cups-ufr2 needs also the gutenprintBin driver. When both are installed it just works ™
 services.printing.drivers = [     pkgs.gutenprintBin     pkgs.canon-cups-ufr2   ];


Fixed link to updated placeholder tutorial

Q
A

content fix?
yes

New article?
no

Related issues?
none

What's in this Pull Request?
Fixed link to updated placeholder tutorial. There was an extra "." in the MD syntax that prevented the link from rendering.

@dannyjessee,
Thanks for having already signed the Contribution License Agreement. Your agreement was validated by Microsoft. We will now review your pull request.
Thanks,
Microsoft Pull Request Bot

thx Danny, appreciated.


Add NamedJavascriptFunction

Coverage increased (+0.7%) to 45.716% when pulling 71bdcb38b798b3a89ccc1082698cc076d0097ec7 on named_js_function into f3da7a31c66484d6a9a0d4042793a7de418f0d64 on master.


Issue with Cypress integration

Hi,
I am not able to integrate this package with Cypress. Getting an error 'Unexpected token '.'' while running 'npx cypress-msteams-reporter'
Steps what i followed:

I have my prerequisite installed and working fine i.e Allure/commandline
npm install cypress-msteams-reporter --save-dev
Created a .env file and added MS Hook in the root of directory
Created environment.properties under allure-results folder.

But still not able to integrate properly. Can anyone please help me out on this ?
I even couldn’t find any example or documentation, Can you please guide me?
Cypress Version: 6.5

Having the same issue as above, were you able to find a solution?

the same problem
MS Teams message was sent successfully.
(node:4404) UnhandledPromiseRejectionWarning: Error: Incoming webhook URL is required
but no massage posted

You probably forgot to provide Incoming webhook URL in .env file. Please do this setup for this. This should work then.
But in my case its not calling MsTeams package, saying unexpected token. Are you facing same issue ?

You probably forgot to provide Incoming webhook URL in .env file. Please do this setup for this. This should work then.
But in my case its not calling MsTeams package, saying unexpected token. Are you facing same issue ?

I have created .env but doesnt work. After that I insert webhook in node_modules\cypress-msteams-reporter\src\ms-teamsWebhook.js. After that message will appear in chat but witout button allure

Hi,
I am not able to integrate this package with Cypress. Getting an error 'Unexpected token '.'' while running 'npx cypress-msteams-reporter'
Steps what i followed:

I have my prerequisite installed and working fine i.e Allure/commandline
npm install cypress-msteams-reporter --save-dev
Created a .env file and added MS Hook in the root of directory
Created environment.properties under allure-results folder.

But still not able to integrate properly. Can anyone please help me out on this ?
I even couldn’t find any example or documentation, Can you please guide me?
Cypress Version: 6.5

Hello @anubajaj23! I could reproduce this case only when using an incorrect incoming webhook url. Can you please double check your url and let me know if the problem still persists.

Hello @maritome ! Thank you for help! I write .env correctly and it works perfectly.
Let me ask one more qusetion about 'Open Test Report'
I type:
npx cypress-msteams-reporter --report-url "http://<IP_ADDRESS>:5500/allure-report/" --verbose
reportPath: ./allure-report/widgets/status-chart.json
 testEnvironmentPropertiesFile: ./allure-report/widgets/environment.json
 reportUrl: http://<IP_ADDRESS>:5500/allure-report/
MS Teams message was sent successfully.

whats ok I receved msg and see button. But when I click I see another URL like "https://teams.microsoft.com/null"
another one test I have changed  --report-url "https://google.com" it works correctly. Google page opens
Whats wrong with allure url?

Hi @maritome,
I have configured Incoming webhook URL correctly because i have verified it multiple times, but after debugging i found the issue is with some packages. Please see the screenshots

I am using TS with this project, is there any dependencies that i m missing?
Also i have some doubt with my plugins/index.js file, i am using dotenv with allure plugin, what will be the correct way to initialise both together?
Can you please help me on this ?

Hello @anubajaj23,
Sorry for the late response.
It seems like the reported issue is related to the Node.js version. Can you please check your node version and if it is v12 upgrade it to v14?
I tried with node v14.17.0 and it works fine for me.


Fix lagging 3d view for big data in auto color mode

References and relevant issues
closes #6397
Description
This array fixes fps performance issues in OpenGL introduced by #3308. In that PR, the texture type was changed to float32 in order to directly pass the labels values to the texture. It turns out that OpenGL performance for float32 textures is much worse than for uint8 textures.
Here we change the code to use uint8 whenever the final number of colors is less than 255 in automatic coloring mode, or uint16 if the number is less than 65535.
This is achieved by transforming original data using a modulo-like operation that avoids the background label landing on 0.
This PR introduces numba dependency, which might not be a long-term solution. We may try to move this utility to some package that already contains compiled code. We can revisit the decision if it causes issues (such as a delay in supporting newer Python versions), and perhaps push such a function to a compiled dependency such as scikit-image.
This PR disables caching used for speedup painting until someone starts painting. It is a significant speedup and reduces memory usage.

This PR disables caching used for speedup painting until someone starts painting. It is a significant speedup and reduces memory usage.

Nice catch!

restarting what looks like random failure.

restarting what looks like random failure.

I have opened PR to fix this random failures #6423

I'm also unsure about the state of the direct map — different lines suggest different things with regards to the texture format. Are direct colours always 32-bit or not? It seems we are very close to fixing, so it would be good to do in this PR also...

For direct colormap, we need to implement separate functions for transforming labels to compressed format based on color dict, not num of colors. I could start working on this. But it will be a separate track.

@Czaki thanks for the clarifications! Just two more comments and then I think it's ready to go:

this comment about updating the slice view: would be good to add references in the code since we're not really sure why it's needed and also probably needs to be fixed with better architecture in the near future.
modulo_plus_one can of course be private for now (_modulo_plus_one), but I think it should still be renamed and include a proper docstring to understand what it's doing and why.

Then I think we can merge this. Will look at #6439 now. 🙏

I spot one problem. There is a lag when someone starts drawing (because of creating a cache array). Should we make it on the selection of paint mode?

@Czaki I was about to push some changes to the _modulo_plus_one docstring (which needs updating now of course). And I was a bit unhappy with low label values now being changed in the node data, but understood the need.
However, now that I am looking at it, it doesn't look like we actually even support a non-zero background label through our public API? (There is no relevant kwarg to the Labels layer.) (I just found that you could set layer.colormap.background_value, but a GitHub code search finds no instances of anyone touching that value.) So, I think rather than support it through this whole stack and codify it in our tests (_data_view is an implementation detail that will have to disappear once we move slicing information off the layers, which is absolutely necessary for multicanvas), I think we should just revert your last few commits and not worry about nonzero background labels until someone complains. What do you think?
Anyway, I'll push my changes, they can be reverted just as well; but I really think we should strongly consider reverting them because even temporary test values add significant code debt — in the future someone will have to think about whether those tests need to be ported to some new system, or just discarded, or something else...

However, now that I am looking at it, it doesn't look like we actually even support a non-zero background label through our public API? (There is no relevant kwarg to the Labels layer.) (I just found that you could set layer.colormap.background_value,

My impression from the previous talk (during the last fixing of labels rendering) is that we want to support setting different backgrounds from 0.

My impression from the previous talk (during the last fixing of labels rendering) is that we want to support setting different backgrounds from 0. Maybe we should just drop it. I just do not want to break this.

I remember this being added specifically cause someone asked for it and they had data with -1 as background... I think @kevinyamauchi was implementing this at the time maybe?

Good thing @Czaki convinced me to keep the functionality then. 😅 Thanks for chiming in @brisvag! 🙏

Gaaah, @Czaki while I was rewording the description, I thought of another issue with this PR: we should not use num_colors to do the mod operation, or labels that have the same color will always have the same color. The mod operation (a) should only occur when the label data dtype doesn't fit in uint8 in the first place, and (b) should be by a prime number that is greater than num_colors but still fits in the desired dtype, and that prime number should get changed when Shuffle is hit. 😕 And we should figure out a test that catches this issue in the future...
At any rate, though, in order to avoid complicating this PR further, I think that we should merge this, and fix it in a subsequent PR. We can raise an issue with the 0.4.19 milestone to make sure it gets handled...
Have I got the analysis right?

Ok after a quick chat with @Czaki we have determined that this issue also exists on main. Therefore, I'm going to merge this and make an issue, which we can then fix. (It may even go back further, but I'm not certain about this, will need to test properly.)

The issue is explained in detail in #6448.


Steps for time isolation on PX4

There might be more to come here.

Looks like that's all for now.


[kmac, clkmgr] KMAC clock idle state (via hint), can't auto restart?

For the top level test case "chip_sw_kmac_idle" the test description states:
Verify the KMAC idle signaling to clkmgr.

Write the KMAC clk hint to 1 within clkmgr to indicate KMAC clk is ready to be gated.
Verify that the KMAC clk hint status within clkmgr reads 0 (KMAC is idle).
Initiate an KMAC operation with a known key, plain text and digest.
Verify that the KMAC clk hint status within clkmgr now reads 1 (KMAC is not idle),
before the KMAC operation is complete.

While writing some code for this, the first part looks to be working, setting the clkmgr KMAC hint
and then checking the status confirms the clk status is 0 (KMAC is idle).
However when then attempting to initiate a KMAC operation (i.e SHA3) the system locks up
(I assume the KMAC clock is not restarting.) The idle signal which is monitored by clkmgr looks to be driven high when KMAC FSM is idle and msgfifo is empty.
Is it the case that these signals cannot change once the clock is stopped and we are therefore stuck with idle high?
The test description implies the clock should auto restart and not rely on unsetting the clock hint.

Yeah the scheme here is not as smart as auto-clock gating (imply both auto stop and auto start).
Instead the scheme here is meant purely to "keep clocks going until kmac is finished" to ensure that while kmac is operational, we cannot manipulate the clocks to create an undesired result.
So once you set the hint, we only shut the clocks off when the unit is idle.  If you want it to run again, you'd actually need to turn it on via software, so the "auto-ness" is one direction only.
as a side note, when you file these top level issues in the future, if it's not clear who to assign them to, could you assign it to @sriyerg, @timothytrippel and @tjaychen first? We can then re-distribute as needed.
Otherwise if there's no assignee, the issue might just fall through the cracks.

Question answered, so closing


Rookie topic - docker image creation and hosting

Hi guys,
I’ve been desperately trying to host this model on a Google Cloud container - I’m extremely new to all this, and need your help…
I’ve been trying to add a Flask server structure that would let me execute the commands precised in the README.md file, correctly adjusting the pdm.lock before so with the Flask package, making sure since I’m working on a Mac initially that I build the image with —platform Linux/amd)4 to avoid exec format error, but it never seems to work.
Could I ask for help in setting this…? Please tell me what details I can provide to help solve this, and apologies in advance if this issue is too vague, but, well… I’m just starting here 😅
Thanks a lot for your awesome work anyhow !

Good question. You can actually use the awesome deployment on Replicate by @chenxwh here: https://replicate.com/vaibhavs10/incredibly-fast-whisper
The cog is here: https://github.com/Vaibhavs10/insanely-fast-whisper/pull/42

I actually found the demo, but wasn't able to use it, which is why I was looking for a way to host it myself in the end...
The error I had in the demo was the following :
Traceback (most recent call last):
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/cog/server/worker.py", line 217, in _predict
result = predict(**payload)
^^^^^^^^^^^^^^^^^^
File "/src/predict.py", line 85, in predict
outputs = self.pipe(
^^^^^^^^^^
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/transformers/pipelines/automatic_speech_recognition.py", line 357, in call
return super().call(inputs, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/transformers/pipelines/base.py", line 1132, in call
return next(
^^^^^
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/transformers/pipelines/pt_utils.py", line 124, in next
item = next(self.iterator)
^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/transformers/pipelines/pt_utils.py", line 266, in next
processed = self.infer(next(self.iterator), **self.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/transformers/pipelines/base.py", line 1046, in forward
model_outputs = self._forward(model_inputs, **forward_params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/transformers/pipelines/automatic_speech_recognition.py", line 552, in _forward
generate_kwargs["num_frames"] = stride[0] // self.feature_extractor.hop_length
TypeError: unsupported operand type(s) for //: 'tuple' and 'int'

I tried with several .mp3 files, without any success... I filled the form with task : transcribe, language empty, batch_size empty, timestamp : word, and my hf token...

So I tried the same demo with timestamp : chunk, and the same for all the rest, but again, impossible to get anything working...
Here's the error I always encounter :
Segmenting the audio clips.
Traceback (most recent call last):
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/cog/server/worker.py", line 217, in _predict
result = predict(**payload)
^^^^^^^^^^^^^^^^^^
File "/src/predict.py", line 111, in predict
segmented_transcript = post_process_segments_and_transcripts(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/predict.py", line 231, in post_process_segments_and_transcripts
upto_idx = np.argmin(np.abs(end_timestamps - end_time))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/numpy/core/fromnumeric.py", line 1325, in argmin
return _wrapfunc(a, 'argmin', axis=axis, out=out, **kwds)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.6/lib/python3.11/site-packages/numpy/core/fromnumeric.py", line 59, in _wrapfunc
return bound(*args, **kwds)
^^^^^^^^^^^^^^^^^^^^
ValueError: attempt to get argmin of an empty sequence

Which let me with the idea of trying to host the model myself to try and see if that may be working better...

I mean, @Vaibhavs10 , you are doing an amazing job and providing it to us for free, please do not apologize haha, I hope I can give it back to you if the system I build with your model works, that's what I want ! :D
Keep me posted, and thanks a lot for your amazing work !

Hey @Vaibhavs10 , just wanted to ask if you had some news on this one, if I may...! Eager to use the Replica deployment of the model asap ! :D Take care !

Hi @MaximeDde - This should be fixed on Replicate! :)

@Vaibhavs10 I am having a similar issue for some audio urls, here is an example from a podcast that I found an issue with:
https://www.buzzsprout.com/555001/10682170-3-tools-you-need-to-up-level-your-productivity-success-with-julie-solomon.mp3
I get the same error as above:
Traceback (most recent call last):
File "/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/cog/server/worker.py", line 217, in _predict
result = predict(**payload)
^^^^^^^^^^^^^^^^^^
File "/src/predict.py", line 162, in predict
raise e
File "/src/predict.py", line 122, in predict
outputs = self.pipe(
^^^^^^^^^^
File "/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/transformers/pipelines/automatic_speech_recognition.py", line 357, in __call__
return super().__call__(inputs, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/transformers/pipelines/base.py", line 1132, in __call__
return next(
^^^^^
File "/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/transformers/pipelines/pt_utils.py", line 124, in __next__
item = next(self.iterator)
^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/transformers/pipelines/pt_utils.py", line 266, in __next__
processed = self.infer(next(self.iterator), **self.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/transformers/pipelines/base.py"
"unsupported operand type(s) for //: 'tuple' and 'int'"

Here is the input used:
input = {
            url:"https://www.buzzsprout.com/555001/10682170-3-tools-you-need-to-up-level-your-productivity-success-with-julie-solomon.mp3",
            task: "transcribe",
            language: "english",
            timestamp: "word",
            batch_size: 64,
            diarise_audio: false
        }

Any ideas? Thanks.


Specified trigger type of Azure Function

When you create a new Azure Function, you have to specify what trigger it should be based on. There exists an IoT Hub trigger as well, however this sample code relies specifically on Event Grid trigger. That's why would be very helpful to specify trigger type earlier to avoid later confusion with the wrong trigger execution / use.

#sign-off


[scorecard] inject scorecard config to bundle image

Description of the change:
Adds scorecard config to bundle image, by modying bundle.Dockerfile.

@estroz Modified writing of Dockerfile, please have a look.

Added tests for RewriteFileContents


edit to install dir die message - prompt for mkdir

Why not also update the maali_die function to add color echo "\033[0;31m $1 \033[0m" so the message is in red and stands out?

done! good to go? :)


Azureedge staging endpoint

There are talks about production and staging which is fine, however, there are no examples on how the staging slot for an azure endpoint could look like. Trying to apply the same strategy as the linked documentation, nothing seems to work.
Can I go to my staging slot of the given cdn endpoint? If so, or if not, can you update given documentation so that it is clear

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

ID: c61c7bcf-ccd8-2ca2-7ee2-b75e66e87939
Version Independent ID: 3fe10193-d724-e221-2191-c10b00075bc6
Content: Azure CDN rules engine reference
Content Source: articles/cdn/cdn-verizon-premium-rules-engine-reference.md
Service: azure-cdn
GitHub Login: @duongau
Microsoft Alias: duau

Thanks for the feedback! I have assigned the issue to the content author to investigate this and update the document as appropriate.

Thank you for you dedication to our documentation.
Unfortunately, we have been unable to review this issue in a timely manner. We sincerely apologize for the delayed response. We are closing this issue. If you feel that the problem persists, please respond to this issue with additional information.
Please continue to provide feedback about the documentation. We appreciate your contributions to our community.
#please-close


Bucket Sort in Go

Fixes: #2110

@atarax665 @HarshCasper Please review this

Code has been plagiarized from here


Throws a lot of errors in the console

Plugin Version
2.0.6
Select The Core
Purpur
Description
I called a person to check, wrote a command to disable the timer and it gave a lot of errors
Errors can be viewed here:https://pastebin.com/93t1tE6j

What is the 'cheatcheck' command?
Only /check

I added an alias (in the plugin.yml file), since the /check command is occupied by the advancedban plugin, this does not affect the functionality of the plugin in any way

Use main command - /lightcheck..

не помогло: https://pastebin.com/mYDQdkiH

Пасиб конечно что ранее на английском писал)

plugin.yml верни как было или перекачай плагин


Result Accuracy of KNN

How Can I get the accuracy result of the classifier?

from sklearn.metrics import accuracy_score acc_knn = accuracy_score(y, knn_model.predict(X)) print('KNN training accuracy = ' + str(100*acc_knn) + '%')

Its not working, It just shows labeled pictures

and how to define X , y ?

use this code instead for accuracy:
import math
from sklearn import neighbors
import os
from sklearn.metrics import accuracy_score
import os.path
import pickle
from PIL import Image, ImageDraw
import face_recognition
from face_recognition.face_recognition_cli import image_files_in_folder
ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg'}
def train(train_dir, model_save_path=None, n_neighbors=None, knn_algo='ball_tree', verbose=False):
"""
Trains a k-nearest neighbors classifier for face recognition.
:param train_dir: directory that contains a sub-directory for each known person, with its name.

 (View in source code to see train_dir example tree structure)

 Structure:
    <train_dir>/
    ├── <person1>/
    │   ├── <somename1>.jpeg
    │   ├── <somename2>.jpeg
    │   ├── ...
    ├── <person2>/
    │   ├── <somename1>.jpeg
    │   └── <somename2>.jpeg
    └── ...

:param model_save_path: (optional) path to save model on disk
:param n_neighbors: (optional) number of neighbors to weigh in classification. Chosen automatically if not specified
:param knn_algo: (optional) underlying data structure to support knn.default is ball_tree
:param verbose: verbosity of training
:return: returns knn classifier that was trained on the given data.
"""
X = []
y = []

# Loop through each person in the training set
for class_dir in os.listdir(train_dir):
    if not os.path.isdir(os.path.join(train_dir, class_dir)):
        continue

    # Loop through each training image for the current person
    for img_path in image_files_in_folder(os.path.join(train_dir, class_dir)):
        image = face_recognition.load_image_file(img_path)
        face_bounding_boxes = face_recognition.face_locations(image)

        if len(face_bounding_boxes) != 1:
            # If there are no people (or too many people) in a training image, skip the image.
            if verbose:
                print("Image {} not suitable for training: {}".format(img_path, "Didn't find a face" if len(face_bounding_boxes) < 1 else "Found more than one face"))
        else:
            # Add face encoding for current image to the training set
            X.append(face_recognition.face_encodings(image, known_face_locations=face_bounding_boxes)[0])
            y.append(class_dir)

# Determine how many neighbors to use for weighting in the KNN classifier
if n_neighbors is None:
    n_neighbors = int(round(math.sqrt(len(X))))
    if verbose:
        print("Chose n_neighbors automatically:", n_neighbors)

# Create and train the KNN classifier
knn_clf = neighbors.KNeighborsClassifier(n_neighbors=n_neighbors, algorithm=knn_algo, weights='distance')
knn_clf.fit(X, y)

# Save the trained KNN classifier
if model_save_path is not None:
    with open(model_save_path, 'wb') as f:
        pickle.dump(knn_clf, f)

return knn_clf

def predict(X_img_path, knn_clf=None, model_path=None, distance_threshold=0.6):
"""
Recognizes faces in given image using a trained KNN classifier
:param X_img_path: path to image to be recognized
:param knn_clf: (optional) a knn classifier object. if not specified, model_save_path must be specified.
:param model_path: (optional) path to a pickled knn classifier. if not specified, model_save_path must be knn_clf.
:param distance_threshold: (optional) distance threshold for face classification. the larger it is, the more chance
       of mis-classifying an unknown person as a known one.
:return: a list of names and face locations for the recognized faces in the image: [(name, bounding box), ...].
    For faces of unrecognized persons, the name 'unknown' will be returned.
"""
if not os.path.isfile(X_img_path) or os.path.splitext(X_img_path)[1][1:] not in ALLOWED_EXTENSIONS:
    raise Exception("Invalid image path: {}".format(X_img_path))

if knn_clf is None and model_path is None:
    raise Exception("Must supply knn classifier either thourgh knn_clf or model_path")

# Load a trained KNN model (if one was passed in)
if knn_clf is None:
    with open(model_path, 'rb') as f:
        knn_clf = pickle.load(f)

# Load image file and find face locations
X_img = face_recognition.load_image_file(X_img_path)
X_face_locations = face_recognition.face_locations(X_img)

# If no faces are found in the image, return an empty result.
if len(X_face_locations) == 0:
    return []

# Find encodings for faces in the test iamge
faces_encodings = face_recognition.face_encodings(X_img, known_face_locations=X_face_locations)

# Use the KNN model to find the best matches for the test face
closest_distances = knn_clf.kneighbors(faces_encodings, n_neighbors=1)
are_matches = [closest_distances[0][i][0] <= distance_threshold for i in range(len(X_face_locations))]

# Predict classes and remove classifications that aren't within the threshold
return [(pred)  for pred in zip(knn_clf.predict(faces_encodings))]

"""
Shows the face recognition results visually.

:param img_path: path to image to be recognized
:param predictions: results of the predict function
:return:
"""
pil_image = Image.open(img_path).convert("RGB")
draw = ImageDraw.Draw(pil_image)

for name, (top, right, bottom, left) in predictions:
    # Draw a box around the face using the Pillow module
    draw.rectangle(((left, top), (right, bottom)), outline=(0, 0, 255))

    # There's a bug in Pillow where it blows up with non-UTF-8 text
    # when using the default bitmap font
    name = name.encode("UTF-8")

    # Draw a label with a name below the face
    text_width, text_height = draw.textsize(name)
    draw.rectangle(((left, bottom - text_height - 10), (right, bottom)), fill=(0, 0, 255), outline=(0, 0, 255))
    draw.text((left + 6, bottom - text_height - 5), name, fill=(255, 255, 255, 255))

# Remove the drawing library from memory as per the Pillow docs
del draw

# Display the resulting image
pil_image.show()

if name == "main":
classifier = train("knn_examples/train", model_save_path="trained_knn_model.clf", n_neighbors=2)
X1 = []
y1 = []
pathgen = "knn_examples/test/"
f = os.listdir(pathgen)
path = ["%s/" % item  for item in f]
pathxx = ["('%s',)" % item  for item in f]
for i in range(0,len(f)):
pathdd = pathgen+path[i]
f2 = os.listdir(pathdd)
pictures = ["%s" % item  for item in f2]
for k in range(0,len(f2)):
predictions = predict(pathdd+pictures[k], model_path="trained_knn_model.clf")
for name in predictions:
X1.append(1)
if str(name)==str(pathxx[i]):
y1.append(1)
else:
print(name,pathxx[i])
y1.append(0)
print(X1,y1)
acc_knn = accuracy_score(y1, X1)
print('KNN training accuracy = ' + str(100*acc_knn) + '%')

It looks like X and y are defined in the code. X holds the face encodings, y holds the names of the people you are trying to predict which are the same as the 'class_dir'.

@jonathan-soll  Thank you so much, I meant accuracy of results , you mentioned the accuracy of training,
if name == "main":
classifier = train("knn_examples/train", model_save_path="trained_knn_model.clf", n_neighbors=2)
X1 = []
y1 = []
pathgen = "knn_examples/test/"
f = os.listdir(pathgen)
path = ["%s/" % item for item in f]
pathxx = ["('%s',)" % item for item in f]
for i in range(0,len(f)):
pathdd = pathgen+path[i]
f2 = os.listdir(pathdd)
pictures = ["%s" % item for item in f2]
for k in range(0,len(f2)):
predictions = predict(pathdd+pictures[k], model_path="trained_knn_model.clf")
for name in predictions:
X1.append(1)
if str(name)==str(pathxx[i]):
y1.append(1)
else:
print(name,pathxx[i])
y1.append(0)
print(X1,y1)
acc_knn = accuracy_score(y1, X1)
print('KNN training accuracy = ' + str(100*acc_knn) + '%')


eCharts doesn't install, runs out of RAM

Describe the bug
iob add echarts crashes the LXC. Adding echarts instance via GUI stops on upload[7] without adding an instance.
To Reproduce
Either use CLI or WebGUI to install/add instance of eCharts
Expected behavior
Successfull adapter installation plus adding instnce has to be fullfilled with exit code 0.
Screenshots & Logfiles
N/A
Versions:

Adapter version: eCharts v1.5.1
JS-Controller version: JS v5.0.12
Node version: Node v18.18.2
Operating system: Same behaviour on Ubuntu v22 and Debian v11

Additional context
Allocated RAM of the LXC has to be increased to 8GB to have the installation run through successfully. After installation RAM can be reduced to desired value.

Same here, was annoying until I found this solution...

Same here, was annoying until I found this solution...

That's not a solution. When a Update comes, same Problem, what i read.
Wondering, some people has no problem on raspis with less RAM.

reference to https://github.com/ioBroker/ioBroker.js-controller/issues/2538


macos Sonoma 14.4.1 (M3 chip) 安装不了

Describe the bug

A clear and concise description of what the bug is.
Taken the following installation steps:

created clean conda environment (python=3.8)
pip install -r requirements.txt
This reported error during build of scikit-learn "ImportError: numpy is not installed.
scikit-learn requires numpy >= 1.13.3."
Then I run pip install numpy==1.21.0
trying to continue with pip install -r requirements.txt leads to same ImportError again, despite numpy is surely installed.

Environment (please complete the following information):

OS: [e.g. mac / window] macos Sonoma 14.4.1  M3 chip
Python Version [e.g. 3.6]
conda 3.8

Screenshots

If applicable, add screenshots to help explain your problem.

Additional context

Add any other context about the problem here.

推荐使用Linux

您好，mac下可能python库的兼容性较差，建议您使用linux，一般情况只要成功安装python对应版本的库是可以正常运行的。您还有其他问题吗？


updated DL preprocessor docs for bytea

Since we changed to bytea for packed dep and indep vars, needed to update the users docs to correspond.
For weird and unknown doxygen issues, @kaknikhil & I learned that
DROP AGGREGATE IF EXISTS MADLIB_SCHEMA.agg_array_concat(anyarray);
CREATE AGGREGATE MADLIB_SCHEMA.agg_array_concat(anyarray) (
   SFUNC = array_cat,
   PREFUNC = array_cat,
   STYPE = anyarray
   );

works but
DROP AGGREGATE IF EXISTS MADLIB_SCHEMA.agg_array_concat(anyarray);
CREATE AGGREGATE MADLIB_SCHEMA.agg_array_concat(anyarray) (
   SFUNC = array_cat,
   STYPE = anyarray,
   PREFUNC = array_cat
   );

results in a blank page being published.  This is not root cause, but the docs do compile by doing this.

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/1087/

Refer to this link for build results (access rights to CI server needed):
https://builds.apache.org/job/madlib-pr-build/1092/


(Bug) #1741 TypeError: Cannot read property 'play' of null

Description
I think the issue happens because of the wrong context for some play fn executions. Fixed context for some of the play method calls.
About #1741
How Has This Been Tested?
This error shouldn't appear on sentry
Checklist:

[x] PR title matches follow: (Feature|Bug|Chore) Task Name
[x] My code follows the style guidelines of this project
[x] I have followed all the instructions described in the initial task (check Definitions of Done)
[x] I have performed a self-review of my own code
[x] My changes generate no new warnings
[ ] I have added tests that prove my fix is effective or that my feature works
[x] New and existing unit tests pass locally with my changes
[x] I have added reference to a related issue in the repository
[x] I have added a detailed description of the changes proposed in the pull request. I am as descriptive as possible, assisting reviewers as much as possible.
[ ] I have added screenshots related to my pull request ( for frontend tasks)
[ ] I have pasted a gif showing the feature.
[x] @mentions of the person or team responsible for reviewing proposed changes

@yaroslav-fedyshyn-nordwhale do you have a method for QA to try and reproduce the error? does it happen when moving quickly between screens?

@sirpy no I don't know how to recreate this. I tried in different ways - it always works fine for me.

@sirpy as we had a lot of animation issue last days, what you think about implementing https://app.zenhub.com/workspaces/gooddollar-5d50833888a83c6880d3e345/issues/gooddollar/gooddapp/1633 just after fixing all critical bugs ?


nothing to do with OkamiStation everthing to do with Creating Space

Hey,
Did you think I was dead ?

Honestly, I just messed around with the code and stuff, I don't really have any plans to continue with it.


Problem accessing config values

I've just installed djangocms-blog, following the installation steps, but I've exceptions of the same nature all around. I'm not sure which module to blame, but hope here you have some ideas:)

File "/home/pooh/work/venv/lib64/python3.5/site-packages/aldryn_apphooks_config/models.py", line 54, in getattr
return getattr(self.app_data.config, item)
File "/home/pooh/work/venv/lib64/python3.5/site-packages/app_data/containers.py", line 159, in getattr
return self.getitem(name)
File "/home/pooh/work/venv/lib64/python3.5/site-packages/app_data/containers.py", line 146, in getitem
self._attr_cache[name] = field.clean(self._data.get(name, field.initial))
File "/home/pooh/work/venv/lib64/python3.5/site-packages/django/forms/fields.py", line 161, in clean
self.validate(value)
File "/home/pooh/work/venv/lib64/python3.5/site-packages/django/forms/fields.py", line 823, in validate
params={'value': value},
django.core.exceptions.ValidationError: ["Select a valid choice. ['Blog'] is not one of the available choices."]

I've poked around, indeed, the values from the config are read as lists, not strings. I've tried modifying the respective places to use the string value from the list, and it works.
In the DB it's like this:

|  1 | djangocms_blog.cms_appconfig.BlogConfig | Blog      | {"config": {"use_abstract": null, "og_type": ["Article"], "send_knock_update": null, "paginate_by": "10", "default_published": null, "og_author_url": "get_author_url", "object_type": ["Article"], "gplus_author": "get_author_gplus", "url_patterns": ["short_date"], "sitemap_changefreq": ["monthly"], "og_author": "get_author_name", "gplus_type": ["Blog"], "use_placeholder": null, "og_app_id": null, "set_author": null, "sitemap_priority": "0.5", "template_prefix": null, "twitter_author": "get_author_twitter", "send_knock_create": null, "og_profile_id": null, "og_publisher": null, "twitter_type": ["summary"], "twitter_site": null, "menu_structure": ["complete"]}} |

Here I'm not sure what is the reason to store arrays instead of values, and therefore what's the best approach to fix it, can you please help?
django-1.11.6
django-cms (3.4.5)
djangocms-blog (0.9b10) — from git

Have you tried with django 1.10.8?

Yes, the same:(
On 15 Nov 2017 5:50 p.m., "kynsi"<EMAIL_ADDRESS>wrote:

Have you tried with django 1.10.8?
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/nephila/djangocms-blog/issues/395#issuecomment-344615400,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AZG4jV4rsF0NOKUyWWEgc4SYs62QlscSks5s2vo5gaJpZM4Qef7D
.

@aikipooh which version of django-appdata is installed?
Could you post your INSTALLED_APPS setting?
Have you added django CMS blog application to a CMS page and published it?

@yakky, I've all this dismantled already, so cannot say anything. Using zinnia now.

@aikipooh thanks for the feedback!


Update typescript-eslint monorepo to v6 (major) (@typescript-eslint/eslint-plugin, @typescript-eslint/parser)

Created this issue as the lint step in https://github.com/open-telemetry/opentelemetry-js/pull/4017 failed.
The goal of this issue is to:

update @typescript-eslint/eslint-plugin, @typescript-eslint/parser in the repo (see https://github.com/open-telemetry/opentelemetry-js/pull/4017)
address all errors that occur without introducing breaking changes.

I am would like to work on this as part of the contribfest


Fix various flaws

This MR fixes various bugs in the simulation leading to poor computational efficiency because of very small internal step size, and wrong acceleration estimation during the projection on the state space.

No alterating of the stepper state during the update of the telemetry
Full precision (double) while parsing the data log file (note that the time accuracy is 1us by design)
Catch the exception raised by the viewer if Gepetto-viewer is closed during a replay, so that it stops the animation without error.

ping @matthieuvigne


Save_dataset_pickles.ipynb

In the readme, you refer to the script Save_dataset_pickles.ipynb
Is this the same one as in the DeepSum repo? What does this script do exactly?
Thank you for your help!

It was a leftover from DeepSUM, it is not needed and we removed it from the instructions.

Thanks!


Question about wishlist structure

I was wondering why the "preferred" field is only returned in the wishlist detail call and not in the overview?
This results in the need to get all the wishlist for a customers profile just to know which one is the preferred one.
Overview response:
{
"elements": [{
"type": "Link",
"uri": "inSPIRED-inTRONICS-Site/-;loc=en_US;cur=USD/customers/-/wishlists/fw8KCgoEzAMAAAF0gH4GFSTt",
"title": "Test",
"itemId": "fw8KCgoEzAMAAAF0gH4GFSTt"
}, {
"type": "Link",
"uri": "inSPIRED-inTRONICS-Site/-;loc=en_US;cur=USD/customers/-/wishlists/HYMKCgoEt_QAAAF04pIGFSTt",
"title": "Test 2",
"itemId": "HYMKCgoEt_QAAAF04pIGFSTt"
}],
"type": "ResourceCollection",
"name": "wishlists"
}
Detail response:
creationDate:<PHONE_NUMBER>304
itemsCount: 0
preferred: true
public: false
title: "Test"
type: "WishList"
We would like to have the preferred field in the overview response.

Unfortunately this is a known limitation of the ICM wishlist REST API. We cannot change that in the context of this PWA REST client.
But I opened an internal Jira ticket (for reference IS-30762) for the ICM development that addresses this shortcoming and I hope that it might be changed in a future ICM version.
In any way, since we show more than the wishlist name (e.g. the items) in our PWA wishlists overview we need to fetch all wishlists details anyways. So there would be even more to wish for from the listing call.


chapi: Add ping test before iscsi login to avoid timeout errors

Problem:

If the target is not reachable from some interfaces, then iscsi login will
take long time 120s before timeout. This causes long delay during device
discovery

Implementation:

Add simple ping test before iSCSI login. Currently this is added only if iscsi interfaces
are defined(cloud).

Testing: Tested mount with multiple volumes on ec2 instance
Review: gcostea, rkumar, sbyadarahalli
Bug: https://nimblejira.nimblestorage.com/browse/NLT-
Signed-off-by: Shiva Krishna, Merla<EMAIL_ADDRESS>

I think this works but it does mean that ICMP must be enabled. We've hit issues in some of our java code using isReachable. isReachable does the following: "Best effort is made by the implementation to try to reach the host, but firewalls and server configuration may block requests resulting in a unreachable status while some specific ports may be accessible. A typical implementation will use ICMP ECHO REQUESTs if the privilege can be obtained, otherwise it will try to establish a TCP connection on port 7 (Echo) of the destination host."
Because that's not always reliable, we switched to an attempt to connect on a socket to a given IP:Port combination. Our port of choice has been 80 since it's the most widely used TCP port. I think this approach would be equivalent to doing net.Dial("tcp", "IP:Port") in go. You might end up with more consistent results going that route.

Thanks George. I agree, if ICMP is blocked then we might skip all iSCSI logins. Shall i use the logic to attempt TCP connection to port 3260? This port is  used by iscsid for all iSCSI discovery and login, so that should be accessible.

And port 3260 must be available for iSCSI anyway.  Great!

And port 3260 must be available for iSCSI anyway. Great!

Thanks. Done..


MM-T1669 team highlight icon

Summary

When a team which is not in active state is clicked, the clicked team will be highlighted.
Ticket Link

Usecase

This issue has been automatically labelled "stale" because it hasn't had recent activity.
A core team member will check in on the status of the PR to help with questions.
Thank you for your contribution!
/cc @jasonblais @hanzei

Hi @openmohan,
Thanks for your PR! Do you have any questions about the feedback? I'm happy to clarify.

Hi @openmohan,
Thanks for your PR! Do you have any questions about the feedback? I'm happy to clarify.

Sorry for the late reply, I overlooked.
I am finding "click and hold mouse event" mimic to be tricky in cypress. I tried cypress.trigger and it did not work. I will spend some more time later today and will get back.

/update-branch

@openmohan Let us know your plan about this PR?

@saturninoabril I will try one more time to see if I can mock the "click and hold" action, If that does not work, I will close the PR :-)

Thanks @openmohan!

@openmohan have you tried this https://docs.cypress.io/api/commands/type.html#Key-Combinations

@openmohan have you tried this https://docs.cypress.io/api/commands/type.html#Key-Combinations for pressed release

Trying this

@openmohan have you tried this https://docs.cypress.io/api/commands/type.html#Key-Combinations for pressed release

Thanks for the suggestion @M-ZubairAhmed.
Along with the suggestion, I tried trigger and click too. Unfortunately, none of them worked.

@openmohan oh ok. @saturninoabril please advise on how to procees

Thanks @openmohan for checking. I tried this a bit as well and none worked for me either. Looks like a valid limitation. Let's close this PR. I'll mark the test case as "Cypress limitation" but will try to revisit in the future too.

Thanks @openmohan for checking. I tried this a bit as well and none worked for me either. Looks like a valid limitation. Let's close this PR. I'll mark the test case as "Cypress limitation" but will try to revisit in the future too.

Thanks @saturninoabril . Let's hope we get something in future cypress version or let's build one. :-)

Thanks @openmohan and hoping for the best in the future 😄


[KYUUBI #2473] [Improvement] Add FilteredShowDatabasesCommand to AuthZ module

Why are the changes needed?

How was this patch tested?

[x] Add some test cases that check the changes thoroughly including negative and positive cases if possible

[ ] Add screenshots for manual tests if appropriate

[x] Run test locally before make a pull request

Codecov Report

Merging #2613 (854cd00) into master (802890a) will increase coverage by 0.02%.
The diff coverage is 88.00%.

@@             Coverage Diff              @@
##             master    #2613      +/-   ##
============================================
+ Coverage     63.57%   63.60%   +0.02%
  Complexity       79       79
============================================
  Files           380      382       +2
  Lines         18480    18505      +25
  Branches       2499     2502       +3
============================================
+ Hits          11749    11770      +21
- Misses         5621     5623       +2
- Partials       1110     1112       +2

Impacted Files
Coverage Δ

...park/authz/ranger/FilterDataSourceV2Strategy.scala
85.00% <85.00%> (ø)

...ugin/spark/authz/ranger/RangerSparkExtension.scala
100.00% <100.00%> (ø)

...xecution/datasources/v2/SparkCatalogV2Bridge.scala
100.00% <100.00%> (ø)

...rg/apache/kyuubi/engine/trino/TrinoSqlEngine.scala
52.63% <0.00%> (-7.02%)
:arrow_down:

.../org/apache/kyuubi/operation/KyuubiOperation.scala
68.00% <0.00%> (-1.34%)
:arrow_down:

...rg/apache/kyuubi/engine/trino/TrinoStatement.scala
71.26% <0.00%> (+4.59%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 802890a...854cd00. Read the comment docs.

can we run build/mvn clean package -pl :kyuubi-spark-authz_2.12 -Dspark.version=2.4.7? manually?

can we run build/mvn clean package -pl :kyuubi-spark-authz_2.12 -Dspark.version=2.4.7? manually?

It can'e compiled using 2.4.7, the ShowNamespaces was added in Spark3

try to make it work? I guess it's easy

can we run build/mvn clean package -pl :kyuubi-spark-authz_2.12 -Dspark.version=2.4.7? manually?

It can'e compiled using 2.4.7, the ShowNamespaces was added in Spark3

Try using the String of node names in pattern matching and add ShowDatabasesCommand case to adapt spark 2.x.

Thanks, using reflecting make it work.

can we handle ShowNamespace in PlannerStrategy?

thanks, merged to master

Thanks for your suggestions.


Add Kubevirt Cloud Controller Manager

What this PR does / why we need it:
Add new External cloud provider for Kubevirt platform
This new controller is running in the management cluster, in the
controlplane namespace
The infrastructure used for this controller is the management cluster,
therefore as part of the deployment, creating special ServiceAccount
including very limited permissions inside the namespace (Services, VMs
and VMIs)
For more info about the Kubevirt-cloud-controller-manager see:
https://github.com/openshift/cloud-provider-kubevirt
Checklist

[ ] Subject and description added to both, commit and PR.
[ ] Relevant issues have been referenced.
[ ] This change includes docs.
[ ] This change includes unit tests.

/lgtm

/retest

/retest

/retest

/retest

/retest

/retest

/retest

/test e2e-kubevirt-azure-ovn

/test e2e-kubevirt-azure-ovn
/test e2e-kubevirt-gcp-ovn

does this need to set external in the kubelet https://github.com/openshift/library-go/blob/master/pkg/cloudprovider/external.go#L17-L20?

does this need to set external in the kubelet https://github.com/openshift/library-go/blob/master/pkg/cloudprovider/external.go#L17-L20?

As far as I understand, because Kubevirt platform doesn't have InTree implementation, indicating the platform type should be enough, please correct me if I wrong.
What is this used for in openshift, beside of indicating the InTree/OutOfTree implementation?

/retest
we have new kubevirt test lanes that we want to execute

/lgtm
@enxebre library-go change has been merged. The KubeVirt platform is now known to have an external cloud provider https://github.com/openshift/library-go/pull/1396

@enxebre can you please take a look on this?
If its ok by you, I think it ready to be merged

/approve

:1st_place_medal:


AZ IoT C2D get lots of errors from C library when send messages via Django server

OS and version used:   . Ubuntu 16.04

Python runtime used:   Python2.7.12

SDK version used:

Description of the issue:

I tried to develop my own backend using Django 1.11.16 with REST endpoint receiving POST method. This is to receive http POST request and then trigger a function with AZ C2D messaging to corresponding device ID. I can successfully send message to device with few requests. After that you will see my console log get exploding with lines and lines of errors from iot hub c library. Looking at my code i send http 204 response back to the request right after iot_messaging.send_sync is called. Is there anything i mistakenly did here?
Code sample exhibiting the issue:

Console log of the issue:

Also when i tried to remove this
try:
# Try Python 2.xx first
raw_input("Press Enter to continue...\n")
except:
pass
# Use Python 3.xx in the case of exception
input("Press Enter to continue...\n")
before
-------
iothub_messaging.close()
   --------

@kwarodom, thank you for your contribution to our open-sourced project! Please help us improve by filling out this 2-minute customer satisfaction survey

it looks like you're closing the client before waiting for the asynchronous operation to complete. I don't know if that could cause these issues (I'll add the C SDK folks to this thread) but I'm pretty sure this is not what you should be doing. You should wait for the callback to be called for all send operations before you call close.

@kwarodom - could you please make sure your call to iothub_messaging.close is called and let us know if that addresses the issue?  Looking at the code in question, it looks like in your for loop you're doing a 'return' after 1 pass (is that what you want by the way, since presumably you want to keep iterating?) so you may never execute the close call at end of function.
@pierreca  - From code review of the C service SDK & Python boost, there's at least one problem.  If an app calls IoTHubMessaging_Destroy but not IoTHubMessaging_Close first, what's going to happen is that the _Destroy will take out the Lock_Deinit(messagingClientInstance->LockHandle).  However, the ScheduleWork_Thread is still partying and when its lock is destroyed from underneath it - well, it's not happy.
This points to a few issues, namely the Python boost layer should probably be calling ``IoTHubMessaging_Closefirst in a destructor - if Close wasn't called yet - just as good programming practice.  But at same time the C SDK should have theIoTHubMessaging_Destroy` itself wait for the thread to drain off if it's still active.  Opening a C github bug on that specifically in a moment...
So @kwarodom your code shouldn't be hitting this problem- underlying layers should handle cleanup better - but I think for a workaround for now just make sure you call the close and you should be OK.

Created https://github.com/Azure/azure-iot-sdk-c/issues/693 to track.  And thanks @kwarodom for looking through your logs and calling this to our attention.

Here is what i found after trying to call iothub_messaging.close() still getting an error also, my device cannot receive not message as well.

@kwarodom - the send of the message happens asyncronously.  If you iothub_message.close() immediately after posting the message to send, then it's not going to have enough time to get the message out.
The code that you're thinking you're looking for is more along the lines of
for i in range(...):
[tab]the logic you have up and including the iothub_messaging.send_async(...)
[tab]do not iothub_messaging.close()
[tab]do not "return response" -> you want the for loop to keep executing
After you've sent the messages you want, wait for the self.send_complete_callbacks to indicate that they've finished executing.  You should have a maximum amount of time you'll wait as a timeout just in case.
Only after the sends have been posted and received response from server (or you get a timeout in the failure case) should you be doing the iothub_messaging.close().  You will (for now) want the explicit calls to close - at some point we'll make SDK's more forgiving where just destroying the iothub_messaging object will do the right thing whether on note close was invoked.

Hi, even after using iothub_messaging.close(), I am facing the same issue.
`Sending message: 0
Error: Time:Fri Aug 30 11:54:20 2019 File:/usr/sdk/src/c/uamqp/src/saslclientio.c Func:on_sasl_frame_received_callback Line:909 SASL handshake failed with code 02
Error: Time:Fri Aug 30 11:54:20 2019 File:/usr/sdk/src/c/c-utility/adapters/tlsio_openssl.c Func:decode_ssl_received_bytes Line:797 SSL channel closed in decode_ssl_received_bytes.
Error: Time:Fri Aug 30 11:54:20 2019 File:/usr/sdk/src/c/uamqp/src/saslclientio.c Func:on_underlying_io_error Line:243 Error callback received in unexpected state
Error: Time:Fri Aug 30 11:54:20 2019 File:/usr/sdk/src/c/c-utility/adapters/tlsio_openssl.c Func:on_underlying_io_bytes_received Line:846 Error in decode_ssl_received_bytes.
Press Enter to continue...
send_complete_callback called with context : 0
messagingResult : OK
Error: Time:Fri Aug 30 11:54:41 2019 File:/usr/sdk/src/c/uamqp/src/saslclientio.c Func:saslclientio_send_async Line:1181 send called while not open
Error: Time:Fri Aug 30 11:54:41 2019 File:/usr/sdk/src/c/uamqp/src/connection.c Func:on_bytes_encoded Line:268 Cannot send encoded bytes
Error: Time:Fri Aug 30 11:54:41 2019 File:/usr/sdk/src/c/uamqp/src/saslclientio.c Func:saslclientio_close_async Line:1130 saslclientio_close called while not open
Error: Time:Fri Aug 30 11:54:41 2019 File:/usr/sdk/src/c/uamqp/src/connection.c Func:on_bytes_encoded Line:272 xio_close failed
Error: Time:Fri Aug 30 11:54:41 2019 File:/usr/sdk/src/c/uamqp/src/saslclientio.c Func:saslclientio_close_async Line:1130 saslclientio_close called while not open
Error: Time:Fri Aug 30 11:54:41 2019 File:/usr/sdk/src/c/uamqp/src/connection.c Func:connection_close Line:1437 xio_close failed
`

@neha-s-deshpande - could you please open a new issue for this?  There are some SASL log errors from the underlying C implementation in the original issue, but they seem to be coming from a different section from the code from your log attached.
Please include the smallest possible repro of Python code along with which SDK version you're on, OS you're using, etc.
@pierreca - for this issue in particular, since original poster hasn't weighed in in quite a while I recommend we close this one out.

ok. I have opened issue @https://github.com/Azure/azure-iot-sdk-python/issues/291 .

With the Python v2 reaching General Availability we are recommending users move away from the v1 SDK.
We will be closing the v1 SDK issues whose features are covered by the v2 release.
Feel free to open an new issue if you find an issue with the v2 SDK.

Thank you for your patronage

@jspaith, @kwarodom, @neha-s-deshpande, thank you for your contribution to our open-sourced project! Please help us improve by filling out this 2-minute customer satisfaction survey


adds client command

I wanted to add the specific client command that people should run with the uaac gem.

@gmmeyer Looks good! Thanks


Refactor Data Handling for Flexible Coordinate Layouts

Description:
Despite the ability to possess any arbitrary coordinate layout, our backend consistently converts the data to a zxy order. Given that we've eliminated the need to download the entire subvolume in the view_style=view mode with the prior PR, there's an opportunity to make our data handling more flexible and avoid these hardcoded transformations.
Expected Functionality:

The system should adapt to and handle any arbitrary coordinate layout provided by the precompute dataset without enforcing a conversion to the zxy order.
The 2D representation of the dataset should seamlessly align with the Neuroglancer (NG) representation.

Proposed Solution:

Remove Hardcoded Transformations: Refactor sections of the backend that force the data into a zxy order.
Generic Formulation: Implement a dynamic data handling approach that can cater to any given coordinate layout of the precompute dataset.
2D-NG Alignment: Ensure that the resulting 2D visual representation matches the NG display, thereby providing a consistent user experience across platforms.

Addressed with PR #76.


Failed to compile: feature edition 2021 is required

I have cargo version: cargo 1.54.0-nightly (e931e4796 2021-05-24).
When trying to install the tools with cargo install, I get:
error: failed to compile `wasm-tools v1.0.1`, intermediate artifacts can be found at `/tmp/cargo-installbbf1ym`

Caused by:
  failed to parse manifest at `/home/vedantroy/.cargo/registry/src/github.com-1ecc6299db9ec823/wasm-encoder-0.9.0/Cargo.toml`

Caused by:
  feature `edition2021` is required

  consider adding `cargo-features = ["edition2021"]` to the manifest

Any ideas what's going on?

FWIW I've been seeing the same thing just now; running rustup update resolved this. My cargo version now is:
cargo 1.58.0 (f01b232bc 2022-01-19)

I bumped the edition for wasm-encoder to 2021, although there's no specific reason that it needed to be.
Although a policy wasn't explicitly stated for this repo, our minimum toolchain version has been "stable" in other BCA repos (e.g. Wasmtime) as it's really not fun to support older toolchains in significantly complex repos as it hampers the adoption of stabilized toolchain features by the contributors.
Like @srenatus, I'm unable to reproduce a problem with cargo install wasm-tools using the latest stable tools (cargo at 1.58.0, rustc at 1.58.1).
We can back out the edition change to that crate, if needed, but I do think we should not have a minimum toolchain version other than stable.

I'm going to close this since this is intended in the sense that upgrading to 2021 should be fine, but if a toolchain upgrade is too difficult for you @vedantroy we can look into going back to 2018.

Upgrading is fine. I guess I was confused since my cargo/rustc version looks like it was compiled/released/something?? in 2021:
(My cargo version)
cargo 1.54.0-nightly (e931e4796 2021-05-24)

The 2021 edition was released with 1.56.0; while the nightly build you were using was indeed released in 2021, it looks like it didn't support the "2021 edition of Rust" at that time.


Editorconfig universal

👨💻 Changes proposed

Add JetBrains IDEs configuration folder to gitignore
Add a universal editorconfig file matching the current VSCode config file

📄 Note to reviewers
This ensures we don't enforce usage of VSCode in the project.
Editorconfig is accepted by many code editors and IDEs out of the box.

It seems you have not installed the required devDependencies to auto fix formatting and check for commit messages. Follow the following steps to pass the checks:

npm i
npm run format:fix
git add .
git commit -m "<conventional commit message here>"

It seems you have not installed the required devDependencies to auto fix formatting and check for commit messages.  Husky is running a pre-commit hook that triggers lint-staged to execute eslint fix and format by prettier, that all works just fine for me.
I ran it manually to ensure it's correctly formatted, here's the result:
❯ npm run format:check

> format:check
> prettier . --check

Checking formatting...
All matched files use Prettier code style!

I've checked the failed workflow, and it's failing for files that I haven't touched by this PR, which is weird.
2022-08-15T01:31:08.2186559Z > format:check
2022-08-15T01:31:08.2187861Z > prettier . --check
2022-08-15T01:31:08.2192886Z
2022-08-15T01:31:08.9244300Z Checking formatting...
2022-08-15T01:31:09.0216788Z [warn] .commitlintrc.json
2022-08-15T01:31:09.0293953Z [warn] .eslintrc.json
2022-08-15T01:31:09.1965791Z [warn] .lintstagedrc.json
2022-08-15T01:31:09.2417227Z [warn] .vscode/extensions.json
2022-08-15T01:31:09.2517337Z [warn] .vscode/settings.json
2022-08-15T01:31:09.4899193Z [warn] next.config.js
2022-08-15T01:31:09.7950454Z [warn] package-lock.json
2022-08-15T01:31:09.8445208Z [warn] package.json
2022-08-15T01:31:10.0813055Z [warn] pages/_app.tsx
2022-08-15T01:31:10.1117941Z [warn] pages/_document.tsx
2022-08-15T01:31:10.1339527Z [warn] pages/api/hello.ts
2022-08-15T01:31:10.1630566Z [warn] pages/index.tsx
2022-08-15T01:31:10.2148618Z [warn] pages/signin.tsx
2022-08-15T01:31:10.2476786Z [warn] pages/signup.tsx
2022-08-15T01:31:10.2655736Z [warn] postcss.config.js
2022-08-15T01:31:10.3462208Z [warn] tailwind.config.js
2022-08-15T01:31:10.3540947Z [warn] tsconfig.json
2022-08-15T01:31:10.3663652Z [warn] Code style issues found in 17 files. Forgot to run Prettier?

As per your suggestion, I've also tried to auto-fix it with format:fix, no files were formatted.
Could you please restart the workflow for this failed step?

We had a big change of tabs -> spaces recently and that might be a reason for it. Wait for the following PR to get merged unitl then I'll see what else could be the reason:

#80

We had a big change of tabs -> spaces recently and that might be a reason for it. Wait for the following PR to get merged unitl then I'll see what else could be the reason:

style: use tabs in place of spaces #80

I see, if currently spaces are used that could be a reason for breaking since I've configured to use tabs, the same way as the current vscode configuration file is configured (which I used to match the project configuration with). I don't think tabs are particularly better or worse than spaces, but I can't care less - whatever the project is using.
Since I can't restart the job myself, I'll ping you once the blocking PR is merged, if you merge that PR yourself would be nice if you could restart the job as well. Thanks!

@ykdojo please do not merge just yet, once we deal with the failing CI step, probably once the #80 is merged  - we can proceed. Thanks!

I reran the job after merging #80 but the prettier job is still failing. I'm going out right now, will look into it once I'm back home.

@mark-omarov Rebasing the PR with main fixed the issue. Do you have anything else to add here or should we merge?

@mark-omarov Rebasing the PR with main fixed the issue. Do you have anything else to add here or should we merge?

Nothing else, good to merge 👍


[media/CircleGraph] Implement visq settings method

This will implement visq settings method to

prepare style elements
fill legend table
store error nodes

ONE-vscode-DCO-1.0-Signed-off-by: SaeHie Park<EMAIL_ADDRESS>

for #1350, from #1351


Regen projects

Cherry-picked from #24

Regenerated APIs
Fixed code changes from regenerated models

This seems like a lot of work. I was wondering if these could be published as npm packages from the respective provider repos. That way the update step for this repo would be

An implementation of the updated package version
rather than
An update of the interface to the api (separate from the actual api)
An implementation of the updated package version

In the way which they exsist as npm packages inside the other provider repos the change to the api and interface would go together. I feel like a single PR would minimize the risk for mistakes. When the changes for the interface and the api get displayed together it should be easier to cross check the logic.

Grand idea. Currently to regen the models we have to first boot up the entirety of Wharf in docker-compose just so the codegen can pull them down via HTTP, instead of just using the swagger.json that's generated from swag init anyway.
I want to put this idea on ice though for the providers as I want to close off access to the providers. This collides a little with the idea of only having the one API (wharf-api) available, and hiding the providers behind proxied request via the main API
Perhaps this could be done for the main API though. I've created a issue for it: https://github.com/iver-wharf/wharf-api/issues/27 though there are some concerns still from my perspective.


chore: release 1.8.6

:robot: I have created a release *beep* *boop*
1.8.6 (2022-05-26)
Bug Fixes

cannot send multiple files (ec70e66)

This PR was generated with Release Please. See documentation.

:robot: Release is at https://github.com/keq-request/keq/releases/tag/v1.8.6 :sunflower:


Astro SDK + Task Mapping

Check the possibility of using task mapping with Astro SDK, something like
@sql
def get_campaigns():
    return """select campaign_id from active_campaigns"""

summarize_campaign.expand(capaign_id=get_campaigns())

Add an example DAG or add a task in existing Example DAG to show this usage

Any progress on this @pankajastro ?

No @kaxil last week I came to know about this but will conclude by this week.

Sounds good, let's try to get it done on Monday so we can cut 1.0.0b1 on Mon/Tue

@pankajastro is facing the below issue while spinning up airflow through docker container. Debugging through it
ERROR: You need to upgrade the database. Please run airflow db upgrade. Make sure the command is run using Airflow version 2.3.3+astro.1.

@sql decorator directly does not and throw the below error. I'm using from astro import sql import.
Broken DAG: [/usr/local/airflow/dags/task_map_test.py] Traceback (most recent call last):
  File "<frozen importlib._bootstrap>", line 228, in _call_with_frames_removed
  File "/usr/local/airflow/dags/task_map_test.py", line 31, in <module>
    def get_campaigns(table: Table):
TypeError: 'module' object is not callable

The potential decorator that I can use for this is either sql.transform or sql.run_raw_sql.
Getting below error when GOOGLE_APPLICATION_CREDENTIALS env is not set and using airflow connection only
[2022-07-26, 07:52:55 UTC] {base.py:68} INFO - Using connection ID 'google_cloud_default' for task execution.
[2022-07-26, 07:52:55 UTC] {base.py:68} INFO - Using connection ID 'google_cloud_default' for task execution.
[2022-07-26, 07:52:57 UTC] {bigquery.py:1053} INFO - Dataset Resource: Dataset(DatasetReference('astronomer-airflow-providers', 'tmp_astro'))
[2022-07-26, 07:52:57 UTC] {base.py:68} INFO - Using connection ID 'google_cloud_default' for task execution.
[2022-07-26, 07:53:01 UTC] {_metadata.py:99} WARNING - Compute Engine Metadata server unavailable on attempt 1 of 3. Reason: timed out
[2022-07-26, 07:53:04 UTC] {_metadata.py:99} WARNING - Compute Engine Metadata server unavailable on attempt 2 of 3. Reason: timed out
[2022-07-26, 07:53:04 UTC] {_metadata.py:99} WARNING - Compute Engine Metadata server unavailable on attempt 3 of 3. Reason: [Errno 111] Connection refused
[2022-07-26, 07:53:04 UTC] {_default.py:290} WARNING - Authentication failed using Compute Engine authentication due to unavailable metadata server.
[2022-07-26, 07:53:04 UTC] {taskinstance.py:1909} ERROR - Task failed with exception
Traceback (most recent call last):
  File "/usr/local/lib/python3.9/site-packages/astro/sql/operators/transform.py", line 16, in execute
    self.database_impl.drop_table(self.output_table)
  File "/usr/local/lib/python3.9/site-packages/astro/databases/base.py", line 204, in drop_table
    self.run_sql(statement)
  File "/usr/local/lib/python3.9/site-packages/astro/databases/base.py", line 93, in run_sql
    result = self.connection.execute(sqlalchemy.text(sql_statement), parameters)
  File "/usr/local/lib/python3.9/site-packages/astro/databases/base.py", line 68, in connection
    return self.sqlalchemy_engine.connect()
  File "/usr/local/lib/python3.9/site-packages/astro/databases/google/bigquery.py", line 43, in sqlalchemy_engine
    return create_engine(uri)
  File "<string>", line 2, in create_engine
  File "/usr/local/lib/python3.9/site-packages/sqlalchemy/util/deprecations.py", line 309, in warned
    return fn(*args, **kwargs)
  File "/usr/local/lib/python3.9/site-packages/sqlalchemy/engine/create.py", line 576, in create_engine
    (cargs, cparams) = dialect.create_connect_args(u)
  File "/usr/local/lib/python3.9/site-packages/sqlalchemy_bigquery/base.py", line 815, in create_connect_args
    client = _helpers.create_bigquery_client(
  File "/usr/local/lib/python3.9/site-packages/sqlalchemy_bigquery/_helpers.py", line 58, in create_bigquery_client
    credentials, default_project = google.auth.default(scopes=SCOPES)
  File "/usr/local/lib/python3.9/site-packages/google/auth/_default.py", line 616, in default
    raise exceptions.DefaultCredentialsError(_HELP_MESSAGE)
google.auth.exceptions.DefaultCredentialsError: Could not automatically determine credentials. Please set GOOGLE_APPLICATION_CREDENTIALS or explicitly create credentials and re-run the application. For more information, please see https://cloud.google.com/docs/authentication/getting-started
[2022-07-26, 07:53:04 UTC] {taskinstance.py:1415} INFO - Marking task as FAILED. dag_id=example_dynamic_map_task, task_id=get_campaigns, execution_date=20220726T075249, start_date=20220726T075253, end_date=20220726T075304
[2022-07-26, 07:53:04 UTC] {manager.py:53} WARNING - Unable to find an extractor. task_type=TransformOperator ***_dag_id=example_dynamic_map_task task_id=get_campaigns ***_run_id=manual__2022-07-26T07:52:49.528508+00:00
[2022-07-26, 07:53:04 UTC] {console.py:21} INFO - {"eventTime": "2022-07-26T07:53:04.243050Z", "eventType": "FAIL", "inputs": [], "job": {"facets": {}, "name": "example_dynamic_map_task.get_campaigns", "namespace": "default"}, "outputs": [], "producer": "https://github.com/OpenLineage/OpenLineage/tree/0.10.0/integration/***", "run": {"facets": {"unknownSourceAttribute": {"_producer": "https://github.com/OpenLineage/OpenLineage/tree/0.10.0/integration/***", "_schemaURL": "https://raw.githubusercontent.com/OpenLineage/OpenLineage/main/spec/OpenLineage.json#/definitions/BaseFacet", "unknownItems": [{"name": "TransformOperator", "properties": {"_BaseOperator__from_mapped": false, "_BaseOperator__init_kwargs": {"conn_id": "", "multiple_outputs": false, "op_args": [], "op_kwargs": {}, "python_callable": "<<non-serializable: function>>", "task_id": "get_campaigns"}, "_BaseOperator__instantiated": true, "_dag": "<<non-serializable: DAG>>", "_inlets": [], "_log": "<<non-serializable: Logger>>", "_outlets": [], "conn_id": "", "depends_on_past": false, "do_xcom_push": true, "downstream_task_ids": [], "email_on_failure": true, "email_on_retry": true, "executor_config": {}, "ignore_first_depends_on_past": true, "inlets": [], "kwargs": {"default_args": {}, "multiple_outputs": false, "op_args": [], "op_kwargs": {}, "python_callable": "<<non-serializable: function>>", "task_id": "get_campaigns"}, "multiple_outputs": false, "op_args": [], "op_kwargs": {}, "outlets": [], "output_table": "<<non-serializable: Table>>", "owner": "***", "parameters": {}, "params": "<<non-serializable: ParamsDict>>", "pool": "default_pool", "pool_slots": 1, "priority_weight": 1, "python_callable": "<<non-serializable: function>>", "queue": "default", "retries": 0, "retry_delay": "<<non-serializable: timedelta>>", "retry_exponential_backoff": false, "sql": "", "start_date": "<<non-serializable: DateTime>>", "task_group": "<<non-serializable: weakproxy>>", "task_id": "get_campaigns", "trigger_rule": "all_success", "upstream_task_ids": [], "wait_for_downstream": false, "weight_rule": "downstream"}, "type": "operator"}]}}, "runId": "f2a20953-7b2c-4c8a-9dbd-f28f64e3751f"}}
[2022-07-26, 07:53:04 UTC] {standard_task_runner.py:92} ERROR - Failed to execute job 50 for task get_campaigns (Could not automatically determine credentials. Please set GOOGLE_APPLICATION_CREDENTIALS or explicitly create credentials and re-run the application. For more information, please see https://cloud.google.com/docs/authentication/getting-started; 218)
[2022-07-26, 07:53:04 UTC] {local_task_job.py:156} INFO - Task exited with return code 1
[2022-07-26, 07:53:04 UTC] {local_task_job.py:273} INFO - 0 downstream tasks scheduled from follow-on schedule check

using sql. transform and export GOOGLE_APPLICATION_CREDENTIALS in containers
Getting below error
[2022-07-26, 08:21:20 UTC] {taskinstance.py:1909} ERROR - Task failed with exception
Traceback (most recent call last):
  File "/usr/local/lib/python3.9/site-packages/airflow/models/taskinstance.py", line 2370, in _record_task_map_for_downstreams
    raise UnmappableXComTypePushed(value)
airflow.exceptions.UnmappableXComTypePushed: unmappable return type 'Table'
[2022-07-26, 08:21:20 UTC] {taskinstance.py:1415} INFO - Marking task as FAILED. dag_id=example_dynamic_map_task, task_id=get_campaigns, execution_date=20220726T082057, start_date=20220726T082100, end_date=20220726T082120
[2022-07-26, 08:21:20 UTC] {manager.py:53} WARNING - Unable to find an extractor. task_type=TransformOperator ***_dag_id=example_dynamic_map_task task_id=get_campaigns ***_run_id=manual__2022-07-26T08:20:57.134603+00:00
[2022-07-26, 08:21:20 UTC] {console.py:21} INFO - {"eventTime": "2022-07-26T08:21:20.564416Z", "eventType": "FAIL", "inputs": [], "job": {"facets": {}, "name": "example_dynamic_map_task.get_campaigns", "namespace": "default"}, "outputs": [], "producer": "https://github.com/OpenLineage/OpenLineage/tree/0.10.0/integration/***", "run": {"facets": {"unknownSourceAttribute": {"_producer": "https://github.com/OpenLineage/OpenLineage/tree/0.10.0/integration/***", "_schemaURL": "https://raw.githubusercontent.com/OpenLineage/OpenLineage/main/spec/OpenLineage.json#/definitions/BaseFacet", "unknownItems": [{"name": "TransformOperator", "properties": {"_BaseOperator__from_mapped": false, "_BaseOperator__init_kwargs": {"conn_id": "", "multiple_outputs": false, "op_args": [], "op_kwargs": {"table": "<<non-serializable: Table>>"}, "python_callable": "<<non-serializable: function>>", "task_id": "get_campaigns"}, "_BaseOperator__instantiated": true, "_dag": "<<non-serializable: DAG>>", "_inlets": [], "_log": "<<non-serializable: Logger>>", "_outlets": [], "conn_id": "", "depends_on_past": false, "do_xcom_push": true, "downstream_task_ids": [], "email_on_failure": true, "email_on_retry": true, "executor_config": {}, "ignore_first_depends_on_past": true, "inlets": [], "kwargs": {"default_args": {}, "multiple_outputs": false, "op_args": [], "op_kwargs": {"table": "<<non-serializable: Table>>"}, "python_callable": "<<non-serializable: function>>", "task_id": "get_campaigns"}, "multiple_outputs": false, "op_args": [], "op_kwargs": {"table": "<<non-serializable: Table>>"}, "outlets": [], "output_table": "<<non-serializable: Table>>", "owner": "***", "parameters": {}, "params": "<<non-serializable: ParamsDict>>", "pool": "default_pool", "pool_slots": 1, "priority_weight": 1, "python_callable": "<<non-serializable: function>>", "queue": "default", "retries": 0, "retry_delay": "<<non-serializable: timedelta>>", "retry_exponential_backoff": false, "sql": "", "start_date": "<<non-serializable: DateTime>>", "task_group": "<<non-serializable: weakproxy>>", "task_id": "get_campaigns", "trigger_rule": "all_success", "upstream_task_ids": [], "wait_for_downstream": false, "weight_rule": "downstream"}, "type": "operator"}]}}, "runId": "0d157b9f-764f-4571-865b-976e31edd751"}}
[2022-07-26, 08:21:20 UTC] {standard_task_runner.py:92} ERROR - Failed to execute job 54 for task get_campaigns (unmappable return type 'Table'; 494)

with some transformation, I'm able to run https://github.com/astronomer/astro-sdk/tree/example_dynamic_map but the changes are significant so not sure we should add this example or not

it looks better with run_raw_sql https://github.com/astronomer/astro-sdk/pull/575. Thank you @tatiana for the help.


Add let expression in do notation.

Codecov Report

Merging #30 (cf14c92) into main (96254e5) will increase coverage by 0.00%.
The diff coverage is 81.81%.

@@           Coverage Diff           @@
##             main      #30   +/-   ##
=======================================
  Coverage   73.43%   73.43%
=======================================
  Files           1        1
  Lines         877      896   +19
  Branches      241      247    +6
=======================================
+ Hits          644      658   +14
- Misses         17       18    +1
- Partials      216      220    +4

Impacted Files
Coverage Δ

include/hspp.h
73.43% <81.81%> (+<0.01%)
:arrow_up:

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qemu error when running indexer-gateway on Apple Silicon

Running subsquid/hydra-indexer-gateway:5 on M1 MacBook Pro
Expected behavior
Ran docker-compose up. Expected localhost:4010 to start up
Actual behavior
Got the following log / error:
found metadata database
{"timestamp":"2022-03-06T00:50:54.000+0000","level":"info","type":"startup","detail":{"kind":"migrations-startup","info":"migrations server port env var is not set, defaulting to 9691"}}
{"timestamp":"2022-03-06T00:50:54.000+0000","level":"info","type":"startup","detail":{"kind":"migrations-startup","info":"server timeout is not set, defaulting to 30 seconds"}}
{"timestamp":"2022-03-06T00:50:54.000+0000","level":"info","type":"startup","detail":{"kind":"migrations-startup","info":"starting graphql engine temporarily on port 9691"}}
{"timestamp":"2022-03-06T00:50:54.000+0000","level":"info","type":"startup","detail":{"kind":"migrations-startup","info":"waiting 30 for 9691 to be ready"}}
{"timestamp":"2022-03-06T00:51:26.000+0000","level":"info","type":"startup","detail":{"kind":"migrations-startup","info":"failed waiting for 9691, try increasing HASURA_GRAPHQL_MIGRATIONS_SERVER_TIMEOUT (default: 30)"}}
metadata hash: 87816a67260b2ab0b18da3fae9a8ec0a
metadata db: gateway_metadata_87816a67260b2ab0b18da3fae9a8ec0a
waiting until indexer db is ready
qemu: uncaught target signal 11 (Segmentation fault) - core dumped
qemu: uncaught target signal 11 (Segmentation fault) - core dumped
qemu: uncaught target signal 11 (Segmentation fault) - core dumped

Information
According to https://github.com/docker/for-mac/issues/5123#issuecomment-784992589, an image which supports mac m1 chips can probably fix this.

We need to switch to Docker Multi-Arch builds for docker-indexer-gateway

Looks like same support will be needed for images hydra-indexer-status-service and hydra-indexer

Duplicates https://github.com/subsquid/squid/issues/21