Make xbox related changes

There's a lot that can be pruned.
I don't see much point.
Leaving it here makes for easier rebasing.
The fuzzer ini needs to be updated to point to our xqemu.
Somewhat tested but issues will be handled once everything is under the same branch.

My bad. Was trying to fork and submodule under a different repo.
Ignore.

My bad. Was trying to fork and submodule under a different repo.
Ignore.


feat(ui): add Checkbox, Orderbox, InputCheckbox, InputOrder and InputSelect

…Select
Issue:
What I did
How to test

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Deploy preview for mcs-lite-ui ready!
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Honor intermediate paths in principal names for Ensured Groups

Fixes #1438

Coverage decreased (-0.005%) to 40.757% when pulling 87f6b2826c196ba3d0f05bc71addffaf230c59a8 on tml:master into 07c081dc9184616cc24694a96c8dddbfac5218d4 on Adobe-Consulting-Services:master.


[FR] Select folder destination in case of choose another source different to current_folder

Describe the bug
The database becomes unresponsive when a new row is inserted via the row template and must be reloaded by clicking on another note before the change is recognized and changes can be made to the entry. This can also be reproduced when no row template is present as well.
To Reproduce
Steps to reproduce the behavior:

Type in name of new row then click plus sign OR click plus sign for new row.
Click on any column of new row and it will not respond.
Click on another note.
Click back on database to reload and you should now be able to edit columns for that row.

Expected behavior
Row columns should be able to be edited after creation without a manual reload.
Screenshots
See video screen capture. (Apologies for the resolution.)
Desktop (please complete the following information):

OS: masOS Monterey - Version 12.5.1
Version: Obsidian Version 0.15.9 (Installer 0.15.8); DB Folder Version 2.3.3

Additional context
New notes are being moved to appropriate folder via the Auto Note Mover plugin upon creation.
https://user-images.githubusercontent.com/106125987/188204202-9054c16c-2f07-4138-9329-d02220850f4b.mov

Could you share the console errors?
MacOS cmd+shift+I
Windows Ctrl+shift+I
I can not reproduce it, maybe the cause is the own template?

Attached
obsidian.md-1662142880047.log

plugin:auto-note-mover:1850 [Auto Note Mover] Moved the note "Test File.md" to the "TV SERIES DATABASE/TV EPISODE RELEASES".
app.js:1 Uncaught TypeError: Cannot read properties of null (reading 'frontmatter')
looks lime you have another plugin(auto-note-mover) that moves the new note so it cant be edited

Ah, I see what you mean.
I was trying to keep the database outside of its source folder because I did not want the database to get lost inside of the source folder.
I set up the source to be a certain tag (tv_episode) as I found this would allow the database to be outside of the source folder and I would not have to have "current_folder" selected. I would have had the source set up to a query, querying the source folder ("Life/TV SERIES DATABASE/TV EPISODE RELEASES", however I could not get that to work. Hence, this is also why I chose to go with the Auto Note Mover plugin, so once it was created, it could move it to the desired folder. I could set Auto Note Mover to do this manually after I have created and edited the entry note.
I am open to any other suggestions. However, it might be valuable if someone wants the database to be out of the source folder in another place, and have the new entry go into the desired source folder without another plugin involved.

My proposal: In case a source other than the current folder is selected, show an optional configuration with the destination of new files. I can include it in the roadmap as a new feature

In fact I want to include it with https://github.com/RafaelGB/obsidian-db-folder/issues/126
So this issue could be a subtask =)

https://user-images.githubusercontent.com/11924043/188269999-45191491-272e-4c8d-9b2e-c538587a0b36.mov

Wow! I think that could be a great option!

avaliable with 2.3.4


Azure Samples

This is one of the samples for my blog post. There will be more in subsequent pull requests.

Hi @arturl, I'm your friendly neighborhood Microsoft Pull Request Bot (You can call me MSBOT). Thanks for your contribution!

In order for us to evaluate and accept your PR, we ask that you sign a contribution license agreement. It's all electronic and will take just minutes. I promise there's no faxing. https://cla.microsoft.com.

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@arturl, Thanks for signing the contribution license agreement so quickly! Actual humans will now validate the agreement and then evaluate the PR.
Thanks, MSBOT;

Updated!


Separate blogs and work experience boxes

Duplicate: https://github.com/xcollantes/portfolio/issues/63


Fix for git localized messages issue, and also fixes "gc is already running" message.

Sorry, I got lost in IDEA-vs-git battle and made changes from a new fork.
Now it's in one commit, maybe I'll get into squashing commits some day, but not today. :)

https://github.com/nirvdrum/svn2git/issues/180

Fixed conflict.

Sorry to be such a bother, but can you rebase onto master to get rid of that merge commit?

Let me try to do that. :)

Ooops, I did it again...


⚠ Spryr has degraded performance

In d353813, Spryr (https://spryr.com) experienced degraded performance:

HTTP code: 200
Response time: 8792 ms

Resolved: Spryr performance has improved in a09b696 after 25 minutes.


Pixabay

Source Site
https://pixabay.com/
Value Provided
High quality curation, solid community, good inventory
Licenses Provided
https://pixabay.com/service/license/
Implementation

[ ] 🙋 I would be interested in implementing this feature.

Pixabay has some CC0 content upto 2019-01-09. Content uploaded after this date is licensed under their own custom license which is incompatible with CC. Read the ToS.
Their API (search images and search videos) does not provide filtering by license in the request and does not provide the license information in the response.


Asserting that all objects in an NSArray are of a specific class

Is there an existing way to check that all objects in an NSArray are of a specific type?
If not, would you be open to a pull request with an interface as follows?
Syntax:
NSArray *x; // x can be NSArray, NSSet (NSDictionary? Checking only values?)
expect(x).to.containOnlyInstancesOf([XXClass class]);
expect(x).to.containOnlyKindsOf([XXClass class]);
expect(x).to.containOnlySubclassesOf([XXClass class]);

Regards,
Jon

I built a custom matcher to do this: https://github.com/orta/Expecta-ContainerClasses perhaps some of the extra ideas could be migrated into that?

Think this can be dealt with via a custom matcher. :+1:


namedExport not working

Hello!
I'm trying to use named exports and it's not working.
export { ReactComponent as Example } from './example.svg';
results in:
src/components/example.svg import {   createElement } from "react";
It only works if i use:
export { default as Example } from './example.svg';
I have tried with the following config but it's not worked too.
svgrPlugin({namedExport: 'ReactComponent'}),
Any suggestion?
Thank you!

Hi! It looks like that parameter isn't supported in SVGR's Node API. After looking through the SVGR documentation, these are the supported parameters: https://react-svgr.com/docs/options/
I think you can use the template parameter to setup a function to change the component name. I updated the package with the correct type declarations.

I found an issue here:
https://github.com/gregberge/svgr/issues/557
It seems a svgr/core issue.
Thank you so much!

@fschwalm can you share how you end up fixing that?


Typerror: withCustomKey is not working

Example code:
const MMKVwithEncryptionKey = new MMKVStorage.Loader().withEncryption().withCustomKey('encryptionKey').initialize();

.initialize() should not be async btw since there might be immediate .get* call after that line on app boot and await can only be used inside the function.

Thanks for reporting this!
There is actually nothing such as withCustomKey, that is a bug in documentation. I will fix it soon.
Use this:
const MMKVwithEncryptionKey = new MMKVStorage.Loader().withEncryption().encryptWithCustomKey('encryptionKey').initialize();

Without async the database will not be initialized when you make the get call. That is the other problem.

Thanks, understood. I'm using it this way now.
// src/store/mmkv.js
import MMKVStorage from 'react-native-mmkv-storage';

class MMKV {
  constructor() {
    this.instance = new MMKVStorage.Loader().withEncryption();
    this.MMKV = null;
  }

  initialize = async () => {
    this.MMKV = await this.instance.initialize();
  };

  setMapAsync = async (name, value) => {
    return this.MMKV.setMapAsync(name, value);
  };

  getMapAsync = async (name) => {
    return this.MMKV.getMapAsync(name);
  };
}

export default new MMKV();

// App.js
import 'react-native-gesture-handler';
import React, {useEffect} from 'react';
import {View, StyleSheet} from 'react-native';
import RNBootSplash from 'react-native-bootsplash';
import AppNavigator from './src/navigation/AppNavigator';
import {MMKV, dispatch} from './src/store';

export default function App() {
  useEffect(() => {
    MMKV.initialize().then(async () => {
      try {
        const settings = await MMKV.getMapAsync('settings');
        dispatch({type: 'settings', settings});
      } catch (err) {
        console.log(err.message);
      } finally {
        RNBootSplash.hide({duration: 250}); // fade
      }
    });
  }, []);

  return (
    <View style={styles.container}>
      <AppNavigator />
    </View>
  );
}

// other components
import {MMKV} from './src/store';

Btw thanks for the library, just what I wanted :)

I will look into it and see if we can make the API directly exposed without async, because async is creating some problems especially with redux-persist etc.

It seems like data is stored inside the document directory, Is it possible to change it to somewhere else? My app is a file storing app, mmkv folder and sks stuff is being exposed to end users :(

In iOS there are no other directories for storing flat files, in fact after exposing iTunes file sharing this path is shared on both iTunes and files. On android it's possible to expose another directory but not for iOS. A while ago I have used realm and they don't seem to host on that, not sure where realm data is stored tho.

can a folder be hidden? @sayem314

@sayem314  I will look into it and see what we can do about it.


First version, still things to adjust

# This defines in which IP and port Plone is running.
# The default is <IP_ADDRESS>:8080
upstream backend {
    server host.docker.internal:8080;
}
upstream frontend {
    server host.docker.internal:3000;
}

# server {
#   listen 80;
#   server_name localhost;
#   return 301 https://$server_name$request_uri;
# }

server {
  listen 80;
  server_name local.kitconcept.io;

  client_max_body_size 1G;

  access_log /dev/stdout;
  error_log /dev/stdout;

  location ~(.*)$ {
    location ~* \.(js|jsx|css|less|swf|eot|ttf|otf|woff|woff2)$ {
        add_header Cache-Control "public";
        expires +1y;
        proxy_pass http://frontend;
    }
    location ~* static.*\.(ico|jpg|jpeg|png|gif|svg)$ {
        add_header Cache-Control "public";
        expires +1y;
        proxy_pass http://frontend;
    }

    if ($http_accept = 'application/json') {
        rewrite ^(.*) /VirtualHostBase/http/local.kitconcept.io/Plone/VirtualHostRoot$1 break;
        proxy_pass http://backend;
        break;
    }

    location ~ /(.*)\/@@images\/(.*)$ {
        rewrite ^(.*) /VirtualHostBase/http/local.kitconcept.io/Plone/VirtualHostRoot$1 break;
        proxy_pass http://backend;
        break;
    }

    proxy_set_header        Host $host;
    proxy_set_header        X-Real-IP $remote_addr;
    proxy_set_header        X-Forwarded-For $proxy_add_x_forwarded_for;
    proxy_set_header        X-Forwarded-Proto $scheme;
    proxy_pass              http://frontend;
  }
}

Maybe @@download should be managed like @@images too

@plone/volto-team I would schedule this for Volto 13, technically not a breaking change, but the change I think it's worth to make it noticeable. What do you think?

I wonder how easy would be to configure haproxy instead of nginx :thinking:


showStarRateDialog doesn't open Google Play Store page

Describe the bug
showStarRateDialog doesn't open Google Play Store page. On the other hand showRateDialog opens Google Play Store page as expected on the same configuration.
UPD: Looks like the problem is in actionsBuilder. When I add custom actionsBuilder to showRateDialog, it stops open Google Play Store page too.
actionsBuilder: (context) {
return [
FlatButton(
child: Text(Localization.of(context).later),
onPressed: () async {
rateMyApp.callEvent(RateMyAppEventType.laterButtonPressed);
Navigator.pop(
context, RateMyAppDialogButton.rate);
},
),
FlatButton(
child: Text(Localization.of(context).rate),
onPressed: () async {
await rateMyApp.callEvent(RateMyAppEventType.rateButtonPressed);
Navigator.pop(
context, RateMyAppDialogButton.rate);
},
),
];
},
To Reproduce
Follow instructions to add rate_my_app library to flutter project.
Call showStarRateDialog.
Dialog is closed without showing Google Play Store page.
Expected behavior
Google Play Store page should be displayed.
Smartphone (please complete the following information):

Device: Google Pixel 3a, Xioami Mi5
OS: Android 11, Android 9

@stepanov-standy You have to manually call rateMyApp.launchStore() if you want to open the store page in a custom action widget.

Thanks! Should we add this line of code to this section on pub.dev?

I don't think so, as it is only an example, and it only that is only there to suggest you what to do, nothing more.


Feature request: more infos about language stanza

Justification
while i try to install libreoffice-language-cask i come over the problem that is not so much info about the language is available. just now i don't can find out before installation if the language is determinated from my current OS system or how i choose it. i read through readme's and casks a bit and also don't find the right information just with the brew cask command. this info should be given before i install a cask. i would suggest some (one or more) enhancements for this use case.
Description of feature/enhancement
add more info about language option in this places:
Missing documentation

[ ] A: missing info in stanzas/language.md which language is used while installation
[ ] B: missing option --language= in man brew-cask
[ ] C: missing option --language= in USAGE.md

brew cask help with languages

[ ] D: show the used language depending on OS in brew cask info <token>
[ ] E: list of possible languages of a stanza with brew cask info <token>
[ ] F: show the option --language= in brew cask info <token> at section caveeats
[ ] G: suggest to install an language pack if an additional language pack is available brew cask install <token> or brew cask info <token>

Example use case
A: stanzas/language.md
at section Installation in stanzas/language.md add this as first paragraph:
when you install a cask with language stanzas It will install in this order:
1. just get either the language of your system
2. if there is no match, then the language marked with default in cask (mostly `en`)
3. or the language you specifically asked for with option `—language=<iso-language>[,<iso-language>]`

B: man brew-cask
add info at manpages/brew-cask.1
FREQUENTLY USED COMMANDS
       install [--force] [--skip-cask-deps] [--require-sha][--language=<iso-language>[,<iso-language>]] token [ token ... ]
              Install Cask identified by token.

and
COMMANDS
       audit [--language=<iso-language>[,<iso-language>]] [ token ... ]
              Check the given Casks for installability.
              If no tokens are given on the command line, all Casks are audited.

and
OPTIONS

       --language=<iso-language>[,<iso-language>]
              Set language of the cask to install.
              The first matching language is used otherwise the default language on the cask.
              The default value is the language of your system.

C: USAGE.md
in USAGE.md add this line in section Options
You can also modify the installed language when issuing `brew cask install`:

    - `--language=<iso-language>[,<iso-language>]` changes the language of the cask to install.
      The first matching language is used otherwise the default language on the cask.
      The default value is the language of your system.

D&E: add info to brew cask info <token>
muescha$ brew cask info seamonkey
seamonkey: 2.46
http://www.seamonkey-project.org/
Not installed
From: https://github.com/caskroom/homebrew-cask/blob/master/Casks/seamonkey.rb
==> Name
SeaMonkey
==> Artifacts
SeaMonkey.app (app)
==>available Languages
*de*
en-GB
en (default)
fr
it
ru
==>System Language
de
==>Installing Language
de
Note: this installing language is because of your system language
Note: you can use the option `--language=<iso-language>[,<iso-language>]` to install a specific language.
      The first matching language is used otherwise the default language on the cask.
muescha$

or if it not match the system language:
==>System Language
zh
==>Installing Language
en
Note: this installing language is because of the default language setting in cask
      and there is no match to your system language
Note: you can use the option `--language=<iso-language>[,<iso-language>]` to install a specific language.
      The first matching language is used otherwise the default language on the cask.
muescha$

F: show in caveats
if D&E is not possible
muescha$ brew cask info seamonkey
seamonkey: 2.46
http://www.seamonkey-project.org/
Not installed
From: https://github.com/caskroom/homebrew-cask/blob/master/Casks/seamonkey.rb
==> Name
SeaMonkey
==> Artifacts
SeaMonkey.app (app)
==>Caveats
this cask include language stanzas. you can use the option `--language=<iso-language>[,<iso-language>]`
to install a specific language or use the default language determinated by your system.

G: info about additional language packs
muescha$ brew cask info libreoffice
[...]
==>Caveats
there exists a language pack in cask `libreoffice-language-pack`

updated first post from <iso-language> to <iso-language>[,<iso-language>]
(see: Mac.languages in mac.rb )

updated first post with The first matching language is used otherwise the default language on the cask.
(see language_eval in dsl.rb and Mac.languages in mac.rb )

updated fist post with at section B for brew audit
(see auditor#audit in auditor.rb )

No on F and G.

Closed in favour of https://github.com/caskroom/homebrew-cask/issues/31128 and https://github.com/caskroom/homebrew-cask/issues/31129.


⚠ Fortnite has degraded performance

In b7babbb, Fortnite (https://fortnite.com) experienced degraded performance:

HTTP code: 200
Response time: 1650 ms

Resolved: Fortnite performance has improved in 67356dc.


how about to use 12.5ms for one frame instead of 10ms?

Can I modify the codes to train the lpcnet vocoder using frame size 12.5ms? Will it be as good as 10ms?

@yxlijinzhu have you tried change different frame size? how do you modify the feature extract scripts? I tried using 5ms frame size but got 'nan' in the first frame.

Can I modify the codes to train the lpcnet vocoder using frame size 12.5ms? Will it be as good as 10ms?

Hello, I am currently changing the frame length to 12.5. May I ask you:
#define FRAME_SIZE_5MS (2)
#define OVERLAP_SIZE_5MS (2)
#define TRAINING_OFFSET_5MS (1)
#define WINDOW_SIZE_5MS (FRAME_SIZE_5MS + OVERLAP_SIZE_5MS)
How did you change these parameters?
（I doubled each of these parameters to train properly）

@yxlijinzhu have you tried change different frame size? how do you modify the feature extract scripts? I tried using 5ms frame size but got 'nan' in the first frame.

Hello, I also encountered this situation, have you solved it?

I haven't done this change.-------- 原始邮件 --------发件人： wangshiyao-1119 @.>日期： 2021年6月29日周二 傍晚5:02收件人： mozilla/LPCNet @.>抄送： yxlijinzhu @.>, Mention @.>主    题： Re: [mozilla/LPCNet] how about to use 12.5ms for one frame instead of 10ms? (#20)
@yxlijinzhu have you tried change different frame size? how do you modify the feature extract scripts? I tried using 5ms frame size but got 'nan' in the first frame.
Hello, I also encountered this situation, have you solved it?
—You are receiving this because you were mentioned.Reply to this email directly, view it on GitHub, or unsubscribe.


Choose a single location for examples

We had some discussion here: https://github.com/apache/camel-k/pull/2731
I think it's important to have a single location for examples, because it would be much easier to maintain and also we could be able to tag them without having the camel-k release enriched with examples.
My vote is to move all the examples in the https://github.com/apache/camel-k-examples repository
But I'd like to get more feedback and votes.

Yes, it was something I planned to do in the past, but went out of my radar (#2462). As mentioned in that discussion, I am good with moving everything in the dedicated repository. In that case, I suggest we apply the same branching strategy of the main project.

Ok, I'm going to work on this.

It sounds good to me. Having the examples promoted into their own repository will certainly make them more visible. Possibly, it'll even make things easier to setup automated testing and foster test coverage in this new repository.

Do we still want to move everything in a different repository?

+1 for me. We can link the example folder in the new location.

Great, thanks @oscerd ! I wonder if we should also remove the CamelSource examples.

Where are them?

Where are them?

This one for instance: https://github.com/apache/camel-k-examples/tree/main/04-aws-kinesis-source-basic

Yeah, I think we need to focus on kamelets and generic-examples.


Migrate Code Jam Management

We'll be migrating the Code Jam Management System from Python to this bot. Needs #4 to be completed first.
Important Notes

I dunno, ask Toxic.

As #18 got merged, I think this can be closed now.


Refactor DependencyGraph

Note that this is still work in progress.

[x] DependencyGraph stores nodes in a list, where position of nodes is it's address (or index). In a situation when a node depends on an unseen node this is problematic (so variable temp was created to deal with this problem).
[x] input_ for _parse can be either a string (the old behavior) or an iterable of lines (so it's possible to use DependencyGraph to parse a large corpus, for example ukwac).
[x] Tests don't cover all the functionality, I'll try to cover it as much as possible.
[ ] DependencyGraph.nodes should be ordered by address.
[ ] DependencyGraph.nodes[...]['deps'] should be an ordered dict as well, where keys are relations. This will make it easy to retrieve all the dependents of a node. Btw, are relations unique?

Some other points

I'm not sure whether remove_by_address, get_by_address and contains_address are needed. They duplicate dictionary API.
right_children() should return the list of children, computing the length of it is trivial.
Maybe, it makes sense make triples() to return node, not just a word, its head and a ctag.

In general, the PR is not ready yet, I might change it a bit: restructure the code, write more tests and documentation.

I've updated modules that use DependencyGraph and added tests (based on demos). The PR is ready to be reviewed and merged.

I've added two more points about dependent node storage. Seems that order is important and just storing it in a dict may break many things.

Thanks for all this work @dimazest. I've inspected the changes and they look fine. I'm going to merge and see how the testing goes at https://nltk.ci.cloudbees.com/job/nltk/

Hi @dimazest,
Could you please check the following code
    if not self.nodes[0]['deps']['ROOT']:
        raise DependencyGraphError(
            "The graph does'n contain a node "
            "that depends on the root element."
        )

It will fail for the following test case:
gold_sent = DependencyGraph("""
Economic  JJ     2      ATT
news  NN     3       SBJ
has       VBD       0       PRED
little      JJ      5       ATT
effect   NN     3       OBJ
on     IN      5       ATT
financial       JJ       8       ATT
markets    NNS      6       PC
.    .      3       PU
""")
Probably you don't want to fix the root relationship as 'ROOT' since it might be predicate relationship i.e 'PRED'

Some issues for the dependency parsers are showing up on the CI server. Would you please take a look @dimazest

Thanks for feedback and merge. I'll have a look to the tests and think how to get the relationship from a root node in a reliable way.
Do you think it's a problem that dg.nodes.values() are not ordered?

and a follow up question. @longdt219, how many nodes will depend on the ROOT node? I suspect there might be several of them (possibly with different relations). Does it make sense to have .root attribute, it seems it's not really a root.

Hi @dimazest,
There might be many nodes have different relationship with root node. Here is what I think
(1) The nodes[0] is always the ROOT node so you don't need the .root attribute.
(2) Only keep the basic contrains about the dependency graph i.e. no-cycle. Remove all other contrains. This will make the dependency graph flexible
(3) Keeping dependency graph simple. For example, we don't need the 'deps' attribute for each nodes. The 'head' is enough.

@longdt219  originally, .root is the node that the ROOT node points to. I think some code relies on this fact. However you are right that the dependency graph needs to be as flexible as possible, so it's capable of dealing with trees produced by parsers.
Regarding removing deps is a good idea to keep the code simple, but quite often one needs to know what are the children of some node. For example, to get the subject and the object of a verb. Without .deps that will require additional iteration over the graph.
Thank you all for the comments. I'll come back to this once I clear some university work, but I should be able to come back soon.


Add ignore option to NpzDeserializer

This PR adds an option to NpzDeserializer that ignores a subset of weights stored in the given npy file.
This is useful in the case when subset of parameters do not have the same shapes as those of the corresponding parameters in the file.
strict can ignore copying values in the case when corresponding parameters do not exist at all.
However, there is no easy way to deal with the situation when the corresponding parameters exist, but the shapes differ. Currently, shape mismatch error is raised.
This option is originally intended to solve the above problem. However, I made it a bit more general.
This way, a user can also ignore to copy some values even if their shapes match with the ones stored in the file.

How about taking a callable in addition to a list of names? The callable takes a layer name and returns whether it is skipped or not. I want to use regular expressions to filter params.

Nice suggestion. I updated the code.

jenkins test this please

When a user misunderstand its specification and uses it with a list of callables, it shows no errors. How about supporting a list of callables? How do you think?

Sure Good idea.

jenkins test this please

LGTM


PasswordInput: Show button in size large is off center

Describe the bug
The show button in the large PasswordInput is in the wrong place
To Reproduce
Steps to reproduce the behavior:

Go to https://next--upbeat-sinoussi-f675aa.netlify.app/api/password-input/

Screenshots

Notes
In addition to fixing the above for large inputs, lets also polish up the show/hide button in the regular size

Looks good here!


The article doesn't touch the subject of querying two datasets

This article doesn't talk about connecting to two datasets at the same time. My understanding is that it doesn't work, but it's not listed as a limitation or as a preview limitation. If this is a limitation, it would be good if it's mentioned in the article
This is probably a duplicate of isssue #2981, but I might be slightly different

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

ID: b9b13312-84ac-72b4-483f-5d8169ecf1e0
Version Independent ID: f648e18b-55f9-9167-a6f1-98be8180bac1
Content: Using DirectQuery for datasets and Azure Analysis Services (preview) - Power BI
Content Source: powerbi-docs/connect-data/desktop-directquery-datasets-azure-analysis-services.md
Service: powerbi
Sub-service: pbi-data-sources
GitHub Login: @davidiseminger
Microsoft Alias: davidi

Thanks for your comment, @erapade . This issue has been assigned to the doc author for review.

@PRMerger8 Jan Michael Omondang Data complex will certify if those codes are within the listed log prefixed-update.
J

It states that this is possible in the first paragraph.

@davidiseminger:  I can’t see that it’s described in the first section. The documentation describes how to connect to one Cube and one Excel file, but not two Cubes. IE what about if also Budget would have been a Cube (not an Excel file). This is not addressed at all and not listed as a limitation


Docker image with Python 2.7

It'd be handy if we can use Python 2.7 out of the box. Currently, the image on Docker Hub (https://hub.docker.com/r/microsoft/mmlspark/) has only Python 3.5.

@elibarzilay has this been adressed?

Closing this issue as we are only supporting python 3.5 to minimize complexity


Update index.html

fix typo

Hey. All documentation is generated from source comments. Could you create
a PR targeting the correct src/*.js file?
On Tue, 15 Sep 2015 at 1:50 pm Doug Shamoo<EMAIL_ADDRESS>wrote:

fix typo
You can view, comment on, or merge this pull request online at:
https://github.com/tgriesser/bookshelf/pull/908
Commit Summary

Update index.html

File Changes

M index.html
https://github.com/tgriesser/bookshelf/pull/908/files#diff-0 (4)

Patch Links:

https://github.com/tgriesser/bookshelf/pull/908.patch
https://github.com/tgriesser/bookshelf/pull/908.diff

—
Reply to this email directly or view it on GitHub
https://github.com/tgriesser/bookshelf/pull/908.

Sure, sorry about that.


[Bug] Annoying warning "No linker preference for target native" when running "flutter run"

Describe the bug
To make a windows app, according to tutorial, after running the final step flutter run on win10 with rust 1.60.0. It gives an annoying warning.  Whole project is here.
$ flutter run
Multiple devices found:
Windows (desktop) • windows • windows-x64    • Microsoft Windows [Version 10.0.17763.2803]
Edge (web)        • edge    • web-javascript • Microsoft Edge 100.0.1185.50
[1]: Windows (windows)
[2]: Edge (edge)
Please choose one (To quit, press "q/Q"): 1
Launching lib\main.dart on Windows in debug mode...
CMake Warning at C:/Program Files (x86)/Corrosion/share/cmake/Corrosion.cmake:314 (message):
  No linker preference for target native
Call Stack (most recent call first):
  C:/Program Files (x86)/Corrosion/share/cmake/CorrosionGenerator.cmake:329 (_add_cargo_build)
  C:/Program Files (x86)/Corrosion/share/cmake/CorrosionGenerator.cmake:479 (_generator_add_target)
  C:/Program Files (x86)/Corrosion/share/cmake/Corrosion.cmake:408 (_generator_add_cargo_targets)
  rust.cmake:15 (corrosion_import_crate)
  CMakeLists.txt:53 (include)
···

Codegen logs with RUST_LOG=debug env variable
RUST_LOG=debug flutter_rust_bridge_codegen  --rust-input native/src/api.rs --dart-output lib/bridge_generated.dart --c-output ios/Runner/bridge_generated.h
[2022-04-28T09:26:20Z DEBUG flutter_rust_bridge_codegen::commands] execute command: bin=powershell args=["-noprofile", "-c", "dart pub global list"] current_dir=None cmd="powershell" "-noprofile" "-c" "dart pub global list"
[2022-04-28T09:26:21Z DEBUG flutter_rust_bridge_codegen::commands] command="powershell" "-noprofile" "-c" "dart pub global list" stdout=ffigen 4.1.3
     stderr=
[2022-04-28T09:26:21Z DEBUG flutter_rust_bridge_codegen::commands] execute command: bin=where args=["cbindgen"] current_dir=None cmd="where" "cbindgen"
[2022-04-28T09:26:21Z DEBUG flutter_rust_bridge_codegen::commands] command="where" "cbindgen" stdout=C:\Users\dbsx\.cargo\bin\cbindgen.exe
     stderr=
[2022-04-28T09:26:21Z DEBUG flutter_rust_bridge_codegen::commands] C:\Users\dbsx\.cargo\bin\cbindgen.exe

[2022-04-28T09:26:21Z INFO  flutter_rust_bridge_codegen] Picked config: Opts { rust_input_path: "D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native/src/api.rs", dart_output_path: "D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\lib/bridge_generated.dart", dart_decl_output_path: None, c_output_path: ["D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\ios/Runner/bridge_generated.h"], rust_crate_dir: "D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native", rust_output_path: "D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native/src\\bridge_generated.rs", class_name: "Native", dart_format_line_length: 80, skip_add_mod_to_lib: false, llvm_path: ["/opt/homebrew/opt/llvm", "/usr/local/opt/llvm", "/usr/lib/llvm-9/lib", "/usr/lib/llvm-10/lib", "/usr/lib/llvm-11/lib", "/usr/lib/llvm-12/lib", "/usr/lib/llvm-13/lib", "/usr/lib/", "/usr/lib64/", "C:/Program Files/llvm", "C:/Program Files/LLVM", "C:/msys64/mingw64"], llvm_compiler_opts: "", manifest_path: "D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native\\Cargo.toml", dart_root: Some("D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb"), build_runner: true }
[2022-04-28T09:26:21Z INFO  flutter_rust_bridge_codegen] Phase: Parse source code to AST
[2022-04-28T09:26:21Z INFO  flutter_rust_bridge_codegen] Phase: Parse AST to IR
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::source_graph] Trying to parse "\\\\?\\D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native\\src\\api.rs"
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::source_graph] Trying to parse "\\\\?\\D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native\\src\\bridge_generated.rs"
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::parser] parse_function function name: Ident(platform)
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::parser] parse_function function name: Ident(rust_release_mode)
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::parser] parse_function function name: Ident(add_2_unsigned_value)
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen] parsed functions: IrFile { funcs: [IrFunc { name: "platform", inputs: [], output: EnumRef(IrTypeEnumRef { name: "Platform", is_struct: true }), fallible: false, mode: Normal, comments: [] }, IrFunc { name: "rust_release_mode", inputs: [], output: Primitive(Bool), fallible: false, mode: Normal, comments: [] }, IrFunc { name: "add_2_unsigned_value", inputs: [IrField { ty: Primitive(U32), name: IrIdent { raw: "v1" }, comments: [] }, IrField { ty: Primitive(U32), name: IrIdent { raw: "v2" }, comments: [] }], output: Primitive(U32), fallible: false, mode: Normal, comments: [] }], struct_pool: {}, enum_pool: {"Platform": IrEnum { name: "Platform", wrapper_name: None, path: ["crate", "api", "Platform"], comments: [],
_variants: [IrVariant { name: IrIdent { raw: "Unknown" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "Android" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "Ios" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "Windows" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "Unix" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "MacOs" }, comments: [], kind:
Struct(IrStruct { name: "MacOs", wrapper_name: None, path: None, fields: [IrField { ty: Delegate(String), name: IrIdent { raw: "field0" }, comments: [] }], is_fields_named: false, comments: [] }) }, IrVariant { name: IrIdent { raw: "Wasm" }, comments: [], kind: Value }], _is_struct: true }}, has_executor: false }
[2022-04-28T09:26:22Z INFO  flutter_rust_bridge_codegen] Phase: Transform IR
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen] transformed functions: IrFile { funcs: [IrFunc { name: "platform", inputs: [], output: EnumRef(IrTypeEnumRef { name: "Platform", is_struct: true }), fallible: false, mode: Normal, comments: [] }, IrFunc { name: "rust_release_mode", inputs: [], output: Primitive(Bool), fallible: false, mode: Normal, comments: [] }, IrFunc { name: "add_2_unsigned_value", inputs: [IrField { ty: Primitive(U32), name: IrIdent { raw: "v1" }, comments: [] }, IrField { ty: Primitive(U32), name: IrIdent { raw: "v2" },
comments: [] }], output: Primitive(U32), fallible: false, mode: Normal, comments: [] }], struct_pool: {}, enum_pool: {"Platform": IrEnum { name: "Platform", wrapper_name: None, path: ["crate", "api", "Platform"], comments: [], _variants: [IrVariant { name: IrIdent { raw: "Unknown" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "Android" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "Ios" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "Windows" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "Unix" }, comments: [], kind: Value }, IrVariant { name: IrIdent { raw: "MacOs" }, comments: [], kind: Struct(IrStruct { name: "MacOs", wrapper_name: None, path: None, fields: [IrField { ty: Delegate(String),
name: IrIdent { raw: "field0" }, comments: [] }], is_fields_named: false, comments: [] }) }, IrVariant { name:
IrIdent { raw: "Wasm" }, comments: [], kind: Value }], _is_struct: true }}, has_executor: false }
[2022-04-28T09:26:22Z INFO  flutter_rust_bridge_codegen] Phase: Generate Rust code
[2022-04-28T09:26:22Z INFO  flutter_rust_bridge_codegen] Phase: Generate Dart code
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::generator::dart] distinct_input_types=[Primitive(U32)][2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::generator::dart] distinct_output_types=[Delegate(String), Primitive(Bool), EnumRef(IrTypeEnumRef { name: "Platform", is_struct: true }), Primitive(U32), Primitive(U8), PrimitiveList(IrTypePrimitiveList { primitive: U8 })]
[2022-04-28T09:26:22Z INFO  flutter_rust_bridge_codegen] Phase: Other things
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::commands] execute format_rust path=D:\DATA\BaiduNetdiskWorkspace\project\personal\testFrb\native/src\bridge_generated.rs
[2022-04-28T09:26:22Z DEBUG flutter_rust_bridge_codegen::commands] execute command: bin=rustfmt args=["D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native/src\\bridge_generated.rs"] current_dir=None cmd="rustfmt" "D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native/src\\bridge_generated.rs"
[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] command="rustfmt" "D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native/src\\bridge_generated.rs" stdout= stderr=
[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] execute cbindgen rust_crate_dir=D:\DATA\BaiduNetdiskWorkspace\project\personal\testFrb\native c_output_path=C:\Users\dbsx\AppData\Local\Temp\.tmpVUutDf.h
[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] cbindgen config:
    language = "C"

    # do NOT include "stdarg.h", see #108 and #53
    sys_includes = ["stdbool.h", "stdint.h", "stdlib.h"]
    no_includes = true

    [export]
    include = []

[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] cbindgen config_file: NamedTempFile("C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpTaDFw2")
[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] execute command: bin=cbindgen args=["-v", "--config", "C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpTaDFw2", "--output", "C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpVUutDf.h"] current_dir=Some("D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\native") cmd="cbindgen" "-v" "--config" "C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpTaDFw2" "--output" "C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpVUutDf.h"
[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] command="cbindgen" "-v" "--config" "C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpTaDFw2" "--output" "C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpVUutDf.h" stdout= stderr=INFO: Take native::Platform - opaque (Enum is not marked with a valid #[repr(prim)] or #[repr(C)].).
    INFO: Take native::wire_platform.
    INFO: Take native::wire_rust_release_mode.
    INFO: Take native::wire_add_2_unsigned_value.
    INFO: Take native::free_WireSyncReturnStruct.
    INFO: Take native::DartPort.
    INFO: Take native::DartPostCObjectFnType.
    INFO: Take native::store_dart_post_cobject.
    INFO: Take native::WireSyncReturnStruct.

[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] execute ffigen c_path=C:\Users\dbsx\AppData\Local\Temp\.tmpVUutDf.h dart_path=C:\Users\dbsx\AppData\Local\Temp\.tmp4onann llvm_path=["/opt/homebrew/opt/llvm", "/usr/local/opt/llvm", "/usr/lib/llvm-9/lib", "/usr/lib/llvm-10/lib", "/usr/lib/llvm-11/lib", "/usr/lib/llvm-12/lib", "/usr/lib/llvm-13/lib", "/usr/lib/", "/usr/lib64/", "C:/Program Files/llvm", "C:/Program Files/LLVM", "C:/msys64/mingw64"]
[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] ffigen config:
            output: 'C:\Users\dbsx\AppData\Local\Temp\.tmp4onann'
            name: 'NativeWire'
            description: 'generated by flutter_rust_bridge'
            headers:
              entry-points:
                - 'C:\Users\dbsx\AppData\Local\Temp\.tmpVUutDf.h'
              include-directives:
                - 'C:\Users\dbsx\AppData\Local\Temp\.tmpVUutDf.h'
            comments: false
            preamble: |
              // ignore_for_file: camel_case_types, non_constant_identifier_names, avoid_positional_boolean_parameters, annotate_overrides, constant_identifier_names

            llvm-path:
               - '/opt/homebrew/opt/llvm'
               - '/usr/local/opt/llvm'
               - '/usr/lib/llvm-9/lib'
               - '/usr/lib/llvm-10/lib'
               - '/usr/lib/llvm-11/lib'
               - '/usr/lib/llvm-12/lib'
               - '/usr/lib/llvm-13/lib'
               - '/usr/lib/'
               - '/usr/lib64/'
               - 'C:/Program Files/llvm'
               - 'C:/Program Files/LLVM'
               - 'C:/msys64/mingw64'

[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] ffigen config_file: NamedTempFile("C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpOxhJF0")
[2022-04-28T09:26:23Z DEBUG flutter_rust_bridge_codegen::commands] execute command: bin=powershell args=["-noprofile", "-c", "dart pub global run ffigen --config \"C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpOxhJF0\""] current_dir=None cmd="powershell" "-noprofile" "-c" "dart pub global run ffigen --config \"C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpOxhJF0\""
[2022-04-28T09:26:25Z DEBUG flutter_rust_bridge_codegen::commands] command="powershell" "-noprofile" "-c" "dart pub global run ffigen --config \"C:\\Users\\dbsx\\AppData\\Local\\Temp\\.tmpOxhJF0\"" stdout=Running in Directory: 'D:\DATA\BaiduNetdiskWorkspace\project\personal\testFrb'
    Input Headers: [C:\Users\dbsx\AppData\Local\Temp\.tmpVUutDf.h]
    Finished, Bindings generated in C:\Users\dbsx\AppData\Local\Temp\.tmp4onann
     stderr=
[2022-04-28T09:26:25Z INFO  flutter_rust_bridge_codegen::commands] Running build_runner at D:\DATA\BaiduNetdiskWorkspace\project\personal\testFrb
[2022-04-28T09:26:25Z DEBUG flutter_rust_bridge_codegen::commands] execute command: bin=powershell args=["-noprofile", "-c", "cd \"D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\"; dart run build_runner build
--delete-conflicting-outputs"] current_dir=None cmd="powershell" "-noprofile" "-c" "cd \"D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\"; dart run build_runner build --delete-conflicting-outputs"
[2022-04-28T09:26:32Z DEBUG flutter_rust_bridge_codegen::commands] command="powershell" "-noprofile" "-c" "cd \"D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\"; dart run build_runner build --delete-conflicting-outputs" stdout=[INFO] Generating build script...
    [INFO] Generating build script completed, took 549ms

    [INFO] Initializing inputs
    [INFO] Reading cached asset graph...
    [INFO] Reading cached asset graph completed, took 72ms

    [INFO] Checking for updates since last build...
    [INFO] Checking for updates since last build completed, took 644ms

    [INFO] Running build...
    [INFO] 1.2s elapsed, 1/2 actions completed.
    [INFO] 2.5s elapsed, 1/2 actions completed.
    [INFO] Running build completed, took 2.8s

    [INFO] Caching finalized dependency graph...
    [INFO] Caching finalized dependency graph completed, took 41ms

    [INFO] Succeeded after 2.8s with 1 outputs (2 actions)

     stderr=
[2022-04-28T09:26:32Z DEBUG flutter_rust_bridge_codegen::commands] execute format_dart path=D:\DATA\BaiduNetdiskWorkspace\project\personal\testFrb\lib/bridge_generated.freezed.dart line_length=80
[2022-04-28T09:26:32Z DEBUG flutter_rust_bridge_codegen::commands] execute command: bin=powershell args=["-noprofile", "-c", "dart format D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\lib/bridge_generated.freezed.dart --line-length 80"] current_dir=None cmd="powershell" "-noprofile" "-c" "dart format D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\lib/bridge_generated.freezed.dart --line-length 80"
[2022-04-28T09:26:34Z DEBUG flutter_rust_bridge_codegen::commands] command="powershell" "-noprofile" "-c" "dart format D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\lib/bridge_generated.freezed.dart --line-length 80" stdout=Formatted 1 file (0 changed) in 0.48 seconds.
     stderr=
[2022-04-28T09:26:34Z DEBUG flutter_rust_bridge_codegen::commands] execute format_dart path=D:\DATA\BaiduNetdiskWorkspace\project\personal\testFrb\lib/bridge_generated.dart line_length=80
[2022-04-28T09:26:34Z DEBUG flutter_rust_bridge_codegen::commands] execute command: bin=powershell args=["-noprofile", "-c", "dart format D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\lib/bridge_generated.dart --line-length 80"] current_dir=None cmd="powershell" "-noprofile" "-c" "dart format D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\lib/bridge_generated.dart --line-length 80"
[2022-04-28T09:26:35Z DEBUG flutter_rust_bridge_codegen::commands] command="powershell" "-noprofile" "-c" "dart format D:\\DATA\\BaiduNetdiskWorkspace\\project\\personal\\testFrb\\lib/bridge_generated.dart --line-length 80" stdout=Formatted D:\DATA\BaiduNetdiskWorkspace\project\personal\testFrb\lib/bridge_generated.dart
    Formatted 1 file (1 changed) in 0.37 seconds.
     stderr=
[2022-04-28T09:26:35Z INFO  flutter_rust_bridge_codegen] Success! Now go and use it :)
cp ios/Runner/bridge_generated.h macos/Runner/bridge_generated.h
flutter pub run build_runner build
[INFO] Generating build script...
[INFO] Generating build script completed, took 630ms

[INFO] Initializing inputs
[INFO] Reading cached asset graph...
[INFO] Reading cached asset graph completed, took 84ms

[INFO] Checking for updates since last build...
[INFO] Checking for updates since last build completed, took 654ms

[INFO] Running build...
[INFO] 1.2s elapsed, 0/1 actions completed.
[INFO] 2.2s elapsed, 0/1 actions completed.
[INFO] Running build completed, took 2.9s

[INFO] Caching finalized dependency graph...
[INFO] Caching finalized dependency graph completed, took 44ms

[INFO] Succeeded after 3.0s with 1 outputs (1 actions)

cd native && cargo fmt
dart format .
Formatted 5 files (0 changed) in 0.62 seconds.

To Reproduce
Like I stated here.
What I did totally according to official template:

uncomment  flutter pub run build_runner build in justfile
add 3 freeze related package according to section 4.3.3
install all dependencies according to section 4.3.1
install corrison through cmake and comment some lines in windows\rust.cmake
CHANGE CODE in lib\main.dart accordingly
run just;
run flutter build

From setp 5, I used the code bleow instead of that stated in section 4.3.4:
// replace with this:
                final text = platform.when(
                  //error here,'when' cannot be recognized
                  // final text = snap.data!.when(//error here,'when' cannot be recognized
                  ios: () => 'iOS',
                  windows: () => 'Windows',
                  android: () => 'Android',
                  unix: () => 'Unix',
                  macOs: (arch) => 'MacOS on $arch',
                  wasm: () => 'the Web',
                  unknown: () => 'Unknown OS',
                );
                return Text('$text ($release)', style: style);

Expected behavior
There should not have the annoying warning.
Generated binding code
No response
OS
win10
Version of flutter_rust_bridge_codegen
1.27.2
Flutter info
Flutter (Channel stable, 2.10.5, on Microsoft Windows [Version 10.0.17763.2803], locale zh-CN)
    • Flutter version 2.10.5 at D:\flutter
    • Upstream repository https://github.com/flutter/flutter.git
    • Framework revision 5464c5bac7 (10 days ago), 2022-04-18 09:55:37 -0700
    • Engine revision 57d3bac3dd
    • Dart version 2.16.2
    • DevTools version 2.9.2

Version of clang++
<IP_ADDRESS>
Version of cbindgen
No response
Version of ffigen
No response
Additional context
No response

I guess it is a problem of corrosion? Have you tried asking there? Or maybe debugging C:/Program Files (x86)/Corrosion/share/cmake/Corrosion.cmake:314 by having a look at it?


Abi python bindings

This pull request adds mpibind for Python and files to support mpibind for Python. These changes fall into three categories.
Adding functionality to the mpibind C library

Add the mpibind_apply function which applies a handle's mapping to a provided taskid
Add the mpibind_get_cpus_ptask function that allows users to access the cpu mapping for a given task as a string

mpibind for Python

Adding mpibind for Python and incorporating it into the build process
Adding docs and an toy mpi4py example using mpibind for Python

Testing mpibind for Python

Updating the expected files to include parameters that the python tests parse
Writing the python testing framework

Please let me know if you have any questions or if there are change I could work on to make the review process easier.

I almost forgot to mention, there might be a licensing complication with some of these files and we may have to find some workarounds.
config/am_check_pymod.m4 and config/tap-driver.py are taken from flux-core.
config/am_check_pymod.m4 is a macro that we can use to check for the presence of python libraries like cffi.
config/tap-driver.py is a wrapper for the shell tap driver that is used with the python tests
I am not sure who the original authors of config/am_check_pymod.m4 are though as there are mentions of the macro outside of flux-core.

I changed the history such that the following changes have been integrated into this PR:

Finished adding doc strings to python code
Fixed make vs make install behavior of python bindings using install-data-hook to modify the mpibind.py file in the install tree
Added license headers to the 2 files that came from flux
Updated test suite to only rely on expected files
Fixed nesting of environment checks in test-suite such that python tests can run without LIBTAP

Please let me know if you would like me to make any changes.


AutoGluon Runs more than the given time limit.

I am running a tabular classifier on a big dataset of about 300MB with a 6GB container and a 1-hour time limit, but it runs for 18 hours.
As per documentation, it should run for 1 hour only, if it has a resource issue or the dataset size is big then it should fail within the given time limit. but I got the model after 18 hours.
Version:  0.4.0
Code:
model = TabularPredictor(label=target, problem_type='binary', path='\tmp\)
model.fit(training_df, time_limit=3600,
                           presets=['high_quality_fast_inference_only_refit', 'optimize_for_deployment'],
                           hyperparameter_tune_kwargs='auto',
                           num_stack_levels=None,
                           auto_stack=False,
                           num_bag_folds=None)

I tried it multiple times on multiple datasets and I faced the same issue but the issue is only on huge datasets.

I tried to ignore some algorithms like FASTAI, NN_TORCH, NN but still the same issue.

Can you provide full logs? This will help identify the issue.

Also, try ignoring KNN, that might do the trick (and please tell me if it does)

@Innixma I exclude the KNN also but still took more time than the given time limit.
I am attaching the logs
Shape of data (160000, 203)
{'message': 'Data PreProcessing Done', 'debug_message': 'Data PreProcessing Done', 'status': 'TRAINING_RUNNING'}
Preset alias specified: 'high_quality_fast_inference_only_refit' maps to 'high_quality'.
Presets specified: ['high_quality_fast_inference_only_refit', 'optimize_for_deployment']
Warning: hyperparameter tuning is currently experimental and may cause the process to hang.
Beginning AutoGluon training ... Time limit = 1740s
AutoGluon will save models to "/tmp/autogluon//autogluon_model/"
AutoGluon Version:  0.4.0
Python Version:     3.8.13
Operating System:   Linux
Train Data Rows:    160000
Train Data Columns: 202
Label Column: Class
Preprocessing data ...
Selected class <--> label mapping:  class 1 = 1, class 0 = 0
Using Feature Generators to preprocess the data ...
Fitting AutoMLPipelineFeatureGenerator...
	Available Memory:                    26991.84 MB
	Train Data (Original)  Memory Usage: 267.84 MB (1.0% of available memory)
	Inferring data type of each feature based on column values. Set feature_metadata_in to manually specify special dtypes of the features.
	Stage 1 Generators:
		Fitting AsTypeFeatureGenerator...
	Stage 2 Generators:
		Fitting FillNaFeatureGenerator...
	Stage 3 Generators:
		Fitting IdentityFeatureGenerator...
		Fitting CategoryFeatureGenerator...
			Fitting CategoryMemoryMinimizeFeatureGenerator...
	Stage 4 Generators:
		Fitting DropUniqueFeatureGenerator...
	Types of features in original data (raw dtype, special dtypes):
		('float', [])  : 200 | ['var_99', 'var_100', 'var_101', 'var_102', 'var_103', ...]
		('int', [])    :   1 | ['_PartInd_']
		('object', []) :   1 | ['_dmIndex_']
	Types of features in processed data (raw dtype, special dtypes):
		('category', []) :   1 | ['_dmIndex_']
		('float', [])    : 200 | ['var_99', 'var_100', 'var_101', 'var_102', 'var_103', ...]
		('int', [])      :   1 | ['_PartInd_']
	5.4s = Fit runtime
	202 features in original data used to generate 202 features in processed data.
	Train Data (Processed) Memory Usage: 257.6 MB (1.0% of available memory)
Data preprocessing and feature engineering runtime = 5.86s ...
AutoGluon will gauge predictive performance using evaluation metric: 'accuracy'
	To change this, specify the eval_metric parameter of Predictor()
Automatically generating train/validation split with holdout_frac=0.03125, Train Rows: 155000, Val Rows: 5000
Fitting 7 L1 models ...
Hyperparameter tuning model: LightGBMXT ... Tuning model for up to 222.96s of the 1734.13s of remaining time.
	Stopping HPO to satisfy time limit...
Fitted model: LightGBMXT/T1 ...
	0.8994	 = Validation score   (accuracy)
	10.49s	 = Training   runtime
	0.02s	 = Validation runtime
Fitted model: LightGBMXT/T2 ...
	0.8994	 = Validation score   (accuracy)
	10.35s	 = Training   runtime
	0.01s	 = Validation runtime
Fitted model: LightGBMXT/T3 ...
	0.8994	 = Validation score   (accuracy)
	11.5s	 = Training   runtime
	0.02s	 = Validation runtime
Fitted model: LightGBMXT/T4 ...
	0.8994	 = Validation score   (accuracy)
	10.22s	 = Training   runtime
	0.02s	 = Validation runtime
Fitted model: LightGBMXT/T5 ...
	0.8994	 = Validation score   (accuracy)
	10.14s	 = Training   runtime
	0.02s	 = Validation runtime
Fitted model: LightGBMXT/T6 ...
	0.8994	 = Validation score   (accuracy)
	12.53s	 = Training   runtime
	0.02s	 = Validation runtime
Fitted model: LightGBMXT/T7 ...
	0.8994	 = Validation score   (accuracy)
	11.22s	 = Training   runtime
	0.01s	 = Validation runtime
Fitted model: LightGBMXT/T8 ...
	0.9202	 = Validation score   (accuracy)
	77.89s	 = Training   runtime
	0.26s	 = Validation runtime
Fitted model: LightGBMXT/T9 ...
	0.8994	 = Validation score   (accuracy)
	11.26s	 = Training   runtime
	0.06s	 = Validation runtime
Fitted model: LightGBMXT/T10 ...
	0.9172	 = Validation score   (accuracy)
	39.98s	 = Training   runtime
	0.15s	 = Validation runtime
Hyperparameter tuning model: LightGBM ... Tuning model for up to 222.96s of the 1524.15s of remaining time.
	Ran out of time, early stopping on iteration 114. Best iteration is:
	[100]	valid_set's binary_error: 0.0904
	Stopping HPO to satisfy time limit...
Fitted model: LightGBM/T1 ...
	0.8994	 = Validation score   (accuracy)
	10.07s	 = Training   runtime
	0.01s	 = Validation runtime
Fitted model: LightGBM/T2 ...
	0.9122	 = Validation score   (accuracy)
	106.2s	 = Training   runtime
	0.31s	 = Validation runtime
Fitted model: LightGBM/T3 ...
	0.8994	 = Validation score   (accuracy)
	11.92s	 = Training   runtime
	0.02s	 = Validation runtime
Fitted model: LightGBM/T4 ...
	0.8994	 = Validation score   (accuracy)
	12.12s	 = Training   runtime
	0.06s	 = Validation runtime
Fitted model: LightGBM/T5 ...
	0.8994	 = Validation score   (accuracy)
	10.25s	 = Training   runtime
	0.01s	 = Validation runtime
Fitted model: LightGBM/T6 ...
	0.8994	 = Validation score   (accuracy)
	12.97s	 = Training   runtime
	0.02s	 = Validation runtime
Fitted model: LightGBM/T7 ...
	0.8994	 = Validation score   (accuracy)
	11.07s	 = Training   runtime
	0.02s	 = Validation runtime
Fitted model: LightGBM/T8 ...
	0.8994	 = Validation score   (accuracy)
	10.42s	 = Training   runtime
	0.01s	 = Validation runtime
Fitted model: LightGBM/T9 ...
	0.8994	 = Validation score   (accuracy)
	11.28s	 = Training   runtime
	0.01s	 = Validation runtime
Fitted model: LightGBM/T10 ...
	0.9096	 = Validation score   (accuracy)
	25.12s	 = Training   runtime
	0.08s	 = Validation runtime
Hyperparameter tuning model: RandomForestGini ... Tuning model for up to 222.96s of the 1298.14s of remaining time.
	No hyperparameter search space specified for RandomForestGini. Skipping HPO. Will train one model based on the provided hyperparameters.
Fitted model: RandomForestGini ...
	0.8994	 = Validation score   (accuracy)
	1236.33s	 = Training   runtime
	23.34s	 = Validation runtime
Hyperparameter tuning model: RandomForestEntr ... Tuning model for up to 222.96s of the 35.84s of remaining time.
	No hyperparameter search space specified for RandomForestEntr. Skipping HPO. Will train one model based on the provided hyperparameters.
Fitted model: RandomForestEntr ...
	0.8994	 = Validation score   (accuracy)
	845.23s	 = Training   runtime
	18.52s	 = Validation runtime
Hyperparameter tuning model: NeuralNetFastAI ... Tuning model for up to 222.96s of the -830.32s of remaining time.
generated new fontManager
	Ran out of time, stopping training early. (Stopping on epoch 16)
	Stopping HPO to satisfy time limit...
Fitted model: NeuralNetFastAI/T1 ...
	0.9138	 = Validation score   (accuracy)
	216.09s	 = Training   runtime
	0.27s	 = Validation runtime
Hyperparameter tuning model: XGBoost ... Tuning model for up to 222.96s of the -1048.94s of remaining time.
	Stopping HPO to satisfy time limit...
Fitted model: XGBoost/T1 ...
	0.9202	 = Validation score   (accuracy)
	224.25s	 = Training   runtime
	0.18s	 = Validation runtime
Fitting model: LightGBMLarge ... Training model for up to 222.96s of the -1275.39s of remaining time.
	0.8994	 = Validation score   (accuracy)
	11.67s	 = Training   runtime
	0.03s	 = Validation runtime
Fitting model: WeightedEnsemble_L2 ... Training model for up to 360.0s of the -1290.98s of remaining time.
	0.9216	 = Validation score   (accuracy)
	1.76s	 = Training   runtime
	0.01s	 = Validation runtime
AutoGluon training complete, total runtime = 3033.41s ... Best model: "WeightedEnsemble_L2"
Fitting 1 L1 models ...
Fitting model: LightGBMXT/T8_FULL ...

No logs after that

@Innixma I run the job on a different public dataset for 30 minutes and it is still running from last 3 hours and logs also freezer
logs:
data_set_name BNG_vehicle_1660214959000_train, training file /tmp/autogluon/BNG_vehicle_1660214959000_train/BNG_vehicle_1660214959000_train-4.csv
dataset id dataset-6b7406bb-fcef-48a8-b25b-5e368fb9c0fa,  /tmp/autogluon/
going to fetch data of dataset 'dataset-6b7406bb-fcef-48a8-b25b-5e368fb9c0fa'
found 1 dataset items
going to get list of groups unders a dataset 'dataset-6b7406bb-fcef-48a8-b25b-5e368fb9c0fa'
found 0 dataset items groups
data_set_name BNG_vehicle_1660214959000_test, training file /tmp/autogluon/BNG_vehicle_1660214959000_test/BNG_vehicle_1660214959000_test-4.csv
Shape of data (800000, 19)
Preset alias specified: 'high_quality_fast_inference_only_refit' maps to 'high_quality'.
Presets specified: ['high_quality_fast_inference_only_refit', 'optimize_for_deployment']
Warning: hyperparameter tuning is currently experimental and may cause the process to hang.
Beginning AutoGluon training ... Time limit = 1740s
AutoGluon will save models to "/tmp/autogluon//autogluon_model/"
AutoGluon Version:  0.4.0
Python Version:     3.8.13
Operating System:   Linux
Train Data Rows:    800000
Train Data Columns: 18
Label Column: Class
Preprocessing data ...
Train Data Class Count: 4
Using Feature Generators to preprocess the data ...
Fitting AutoMLPipelineFeatureGenerator...
	Available Memory:                    28288.72 MB
	Train Data (Original)  Memory Usage: 115.2 MB (0.4% of available memory)
	Inferring data type of each feature based on column values. Set feature_metadata_in to manually specify special dtypes of the features.
	Stage 1 Generators:
		Fitting AsTypeFeatureGenerator...
	Stage 2 Generators:
		Fitting FillNaFeatureGenerator...
	Stage 3 Generators:
		Fitting IdentityFeatureGenerator...
	Stage 4 Generators:
		Fitting DropUniqueFeatureGenerator...
	Types of features in original data (raw dtype, special dtypes):
		('float', []) : 18 | ['COMPACTNESS', 'SCALED_VARIANCE_MAJOR', 'SCALED_VARIANCE_MINOR', 'SCALED_RADIUS_OF_GYRATION', 'SKEWNESS_ABOUT_MAJOR', ...]
	Types of features in processed data (raw dtype, special dtypes):
		('float', []) : 18 | ['COMPACTNESS', 'SCALED_VARIANCE_MAJOR', 'SCALED_VARIANCE_MINOR', 'SCALED_RADIUS_OF_GYRATION', 'SKEWNESS_ABOUT_MAJOR', ...]
	4.9s = Fit runtime
	18 features in original data used to generate 18 features in processed data.
	Train Data (Processed) Memory Usage: 115.2 MB (0.4% of available memory)
Data preprocessing and feature engineering runtime = 5.45s ...
AutoGluon will gauge predictive performance using evaluation metric: 'accuracy'
	To change this, specify the eval_metric parameter of Predictor()
Automatically generating train/validation split with holdout_frac=0.02, Train Rows: 784000, Val Rows: 16000
Fitting 7 L1 models ...
Hyperparameter tuning model: NeuralNetFastAI ... Tuning model for up to 223.01s of the 1734.55s of the remaining time.
generated new fontManager
	Ran out of time, stopping training early. (Stopping on epoch 3)
	Stopping HPO to satisfy time limit...
Fitted model: NeuralNetFastAI/T1 ...
	0.751	 = Validation score   (accuracy)
	188.64s	 = Training   runtime
	0.32s	 = Validation runtime
Hyperparameter tuning model: LightGBMXT ... Tuning model for up to 223.01s of the 1543.81s of remaining time.

No logs after this

Unfortunately I was never able to reproduce this issue. It may have been fixed in v0.5 or the upcoming v0.6 release. If you can provide a reproducible example using latest mainline, please re-open the issue.


Implementation status

Working on spherical_render branch
Todo

[x] Load Opensfm data for spherical camera
[x] Render forward - Need to check pixels are in the right position
[x] Render forward - Need to check if jacobian is okay
[x] Render backward - Need to check mathematical correctness for backward

Current status
Forward pass is not good

Sample dataset
https://dtbn.jp/6eEZeo8e
(The url will expire in a week)
image

reconstruction

Forward pass is look okay

Worked! I dont know why it's upside down.

Real data is not as good as simulated data, but looks working well.
https://github.com/user-attachments/assets/192cc732-d8e6-4c3e-a9eb-45e89b315388

Excellent contribution, I tested the code on the OmniBlender dataset and found that the default strategy has a sharp rise in loos after the 3000th step and seems to reset the opacity every 100 steps after that, resulting in a poor encounter, whereas with the mcmc strategy my psnr was 5db higher than the results on the omnigs paper!


Project level alerts are not working

Rancher versions: 2.0 master 2/28
Steps to Reproduce:

Create a notifier
Create a project level against a workload that has a bad image associated

Results:  Alert never fires

The format of id of the resource is deployment:cattle-alerting:alertmanager", which is different from  Backend's assumption. Backend will change to follow the actual format.

Version - 2.0 master 3/2
Verified fixed


chore: update estree resolution

:tada: This PR is included in version 1.15.5 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

:tada: This PR is included in version 1.15.5 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


qCurveTo support for skeletonPoints

… but does so when using a static font. Same for points() as it’s utilizing skeletonPoints().
That is, when using .points() or .pen().points() on a StSt.
https://github.com/goodhertz/coldtype/blob/9f389f2fda789cc8b7fad29540be31f57ce3ef37/coldtype/pens/datpen.py#L309
Possible fix:
Either add a elif t == "qCurveTo": ... or change elif t == "curveTo": to elif t == "curveTo" or t == "qCurveTo":
For me that works well then.

Ah! Right, yeah it only supports .otf-style at the moment since it has no qCurveTo support, that's definitely the issue.
I can work on this soon, but I think the best solution here would actually be to pull these functions (skeleton, skeletonPoints) out into an "fx" module, (i.e. in the coldtype/fx directory) so that they don't have to live directly in the DATPen/DraftingPen source (which is a little cluttered at the moment), then these functions could be more robust / full-featured.

I see, however I could rewrote the method locally to actually provide the qCurveTo support by just adding that bit as mentioned. And then it works already.
Where to implement it is rather a question of the architecture, I don’t want to intervene there at all 🤐 ☺

Ah! Think I kind of misunderstood / mis-remembered the scope of skeletonPoints — that change totally makes sense, I've just pushed it to main.
Can I ask how you're using the skeletonPoints method? I have to admit that was an earlier addition to the library that I don't find myself using much anymore, so would love to know more about your use-case.

Oh, sorry for making it confusing.
Actually first I was trying to see if/how I can get the bezierPath in order to distribute text on a letter bezierPath (instead of a "normal" path. I didn’t find out how, yet, but then I was playing around with displayng the points of the letters, kind of like with my Presenter Plugin (for GlyphsApp), just animated :)
There are likely more opportunities to play with, and I thought it’s already there anyway, so why not :)


reactjs.org - Main Page Snippet Error

Hello, by opening reactjs.org there are some snippets showing basic things in React. All this snippets are working except the last "A Component Using External Plugins". You should make a more clear way of how to integrate Remarkable because I get: Uncaught ReferenceError: Remarkable is not defined. I hope you fix it fastly cause it's not something hard.

@alexanderfilippov670 You need to import Remarkable, and it is clearly mentioned that it uses remarkable an external markdown.

@alexanderfilippov670 You need to import Remarkable, and it is clearly mentioned that it uses remarkable an external markdown.

How to do that? I don't find any helpful resource.

@alexanderfilippov670 You need to import Remarkable, and it is clearly mentioned that it uses remarkable an external markdown.

How to do that using a CDN? I don't find any helpful resource.

Run this "npm install remarkable --save", and go through this link for reference.


Problem with Swift 3

every thing is simple and sweet on normal state , i.e. on unselected state,
on selected state it is all messed . the selected color is all over the icon not only on radio indicator !

Can you send a screenshot please? Also, this shouldn't have anything to do with Swift 3


[WIP] Issue warnings when accessing deprecated layer state

References and relevant issues
See #5477 for some of the motivation here. This is split from that larger PR, to make reviewing the core idea here easier.
Description
This introduces a mechanism to notify developers about deprecated state that is returned in Layer.as_layer_data_tuple. Similarly, this affects any plugins that rely on the data, attrs, layer_type tuple for layer interchange.
Without this mechanism, any equivalent parameters/properties that are deprecated will either be

present in the layer state dict returned, without a notification of their deprecation;
or removed from the layer state dict return.

We could live with (2), but it is a breaking change without the soft landing of a deprecation.
(1) is not much better because it just delays the removal and breaking change (unless we continue to accumulate all state ever in a layer, which seems unsustainable).
This PR also uses this new mechanism to ensure that the deprecated Points.edge_* state issues a warning when it is accessed.

I'm not convinced this is worth it, but wanted to open the PR separately from #5477 to isolate this potential contribution.

I'm not convinced this is worth it, but wanted to open the PR separately from #5477 to isolate this potential contribution.

One thing that suggests this PR might be worth it is that it uncovers a minor napari-svg bug that is currently silently failing: https://github.com/napari/napari/actions/runs/9456571418/job/26048729441?pr=6976#step:12:2660
That failure is not particularly critical, but there could be bigger ones out there.

What's holding this in draft mode @andy-sweet? I'm not sure I entirely understand the discussion re. as_layer_data_tuple, but were there any other concerns?

Like @Czaki mentioned, the current solution outright breaks tests and will break similar usage in the wild.
But the proposed changes make the dictionary more specialized, potentially confusing, and may break other (maybe less common) usage in the wild. As a compromise, it's probably worth it, but I haven't convinced myself yet. So I'm planning to spend a little time thinking about alternative solutions.
Will make a decision/recommendation before the end of the week.

I've implemented a solution to the deserialization issue, which is to store the deprecated items separately from the dictionary itself.
The main positive effect of this approach is that
from napari.layers import Points
points = Points()
data, attrs, _ = points.as_layer_data_tuple()
new_points = Points(data, **meta)

will not raise, which is important since this is part of the public API and is at least used in a few places in napari internally and in its tests. Because of this usage, making this change also means that this PR becomes simpler too because I don't have to make special affordances for the tests.
The main negative effect is that we're returning a dictionary that behaves a little strangely because it will allow direct access to the deprecated items through __getitem__, __setitem__, __delitem__, and __contains__ but not through other ways like iteration.
This might result in some strange inconsistencies (e.g. x in attrs is true, but for y in attrs won't include x), but those will only occur when a deprecated key is being accessed. I think that falls in line with a fair deprecation policy, which is to notify the user and make a best effort to provided deprecated values or behaviors.
I think I'm happy with this approach, but let me stew on it just a little more! Or feel free to criticize or propose other ideas!

Anyone have any idea why the workflow that uses pip to install from this branch's commit does not trigger the DeprecationWarning in  test_as_layer_data_tuple_read_deprecated_key?
For consistency with #6980, I'm planning to update this so it uses FutureWarning instead of DeprecationWarning, but I'm unsure if that will help.

For consistency with https://github.com/napari/napari/pull/6980, I'm planning to update this so it uses FutureWarning instead of DeprecationWarning, but I'm unsure if that will help.

Huh, I mean that was going to be my only suggestion...

For consistency with #6980, I'm planning to update this so it uses FutureWarning instead of DeprecationWarning, but I'm unsure if that will help.

Huh, I mean that was going to be my only suggestion...

That did not work, and effectively has the same error as before
___________ test_as_layer_data_tuple_read_deprecated_key[edge_width] ___________

key = 'edge_width'

    @pytest.mark.parametrize(
        'key',
        [
            'edge_width',
            'edge_width_is_relative',
            'edge_color',
            'edge_color_cycle',
            'edge_colormap',
            'edge_contrast_limits',
        ],
    )
    def test_as_layer_data_tuple_read_deprecated_key(key: str):
        layer = Points()
        _, attrs, _ = layer.as_layer_data_tuple()
        with pytest.raises(FutureWarning):
>           attrs[key]
E           Failed: DID NOT RAISE <class 'FutureWarning'>

followed by the seemingly contradictory
=============================== warnings summary ===============================
...
layers/points/_tests/test_points.py::test_as_layer_data_tuple_read_deprecated_key[edge_width]
  /opt/hostedtoolcache/Python/3.9.19/x64/lib/python3.9/site-packages/napari/utils/migrations.py:243: FutureWarning: edge_width is deprecated since 0.5.0 and will be removed in 0.6.0. Please use border_width
    warnings.warn(message, FutureWarning)

Maybe PBKAC: why am I using pytest.raises instead of pytest...? Not sure why this would only affect the pip install` tests though.

I have found that the same problem as for Points layer, there is for Image.interpolation. So I propose a generalization based on rename_argument in andy-sweet#70

@Czaki : thanks for the PR - I merged it and also cleaned this up a bit more.
As part of that cleaning, I renamed DeprecatedProperty to DeprecatedParameter, though I'm starting to reconsider how useful this thing is, especially because it's publicly exposed right now - we could give it a private name (i.e. _DeprecatedParameter) though because no instances of it are publicly exposed.

I think there's still some discussion about the desired behavior of DeprecatingDict, so I removed the ready to merge label. I think it's OK to bring this in later for a v0.5.0 release candidate, or even for v0.5.1 (especially since this is partially motivated by and blocks https://github.com/napari/napari/pull/5477 which probably won't make it for v0.5.0).

Another option here is not introduce this data structure at all, and just let plugins that use deprecated/removed state break. That sounds bad, but we do want plugin devs to update things at some point (i.e. for v0.6.0). The warning + extra time of a deprecation is ideal, but I am worried about introducing too much complexity here.

@Czaki : In a branch off this, I made DeprecatingDict fancier so that setting and deleting deprecated keys can update the corresponding non-deprecated items consistent: https://github.com/andy-sweet/napari/compare/main...andy-sweet:napari:feat-fancy-layer-state-deprecation?expand=1
I do not love it and am not convinced it or something like it is something we should try to support.
One compromise I like more is to raise when trying to set or delete a deprecated key. That way the fix for the developer is clear. My guess is that mutating the layer state dict is not too common, so this won't happen much. If I'm wrong, we can do the fancy thing later.
What do you think?

Why did you decide to stop using NamedTuple? For me, it reduces readability and makes it harder to discover from where the arguments come.

Why did you decide to stop using NamedTuple? For me, it reduces readability and makes it harder to discover from where the arguments come.

It introduced another publicly exposed type which was difficult to name and didn't seem to improve the readability enough. I don't feel too strongly about it, so don't mind bringing it back, especially if you can propose a good name for it.
I think the bigger issue is around the behavior of the class around keeping deprecated/non-deprecated values consistent.

It introduced another publicly exposed type which was difficult to name and didn't seem to improve the readability enough. I don't feel too strongly about it, so don't mind bringing it back, especially if you can propose a good name for it.

We may make it private, we may convert migrations from script to module. For me using plain tuple, is a simple way to get some bug during refactor/improve.

I think the bigger issue is around the behavior of the class around keeping deprecated/non-deprecated values consistent.

yes

We may make it private, we may convert migrations from script to module. For me using plain tuple, is a simple way to get some bug during refactor/improve.

I brought it back as a private class used to store renamed attributes/arguments internally, but not used to store deprecations in DeprecatingDict (since that needs to stores things other than renames) or in DeprecatingDict.set_deprecated_from_rename (since that is public), but we still get the benefit of using keyword arguments to initialize and unpack it to prevent related bugs.

This is working as expected for me and has been approved and rtm for a day so I'm going to merge. @andy-sweet where, if anywhere, would you document this behaviour for users? Maybe where we define the LayerDataTuple class we can leave a little note?

@andy-sweet where, if anywhere, would you document this behaviour for users? Maybe where we define the LayerDataTuple class we can leave a little note?

I don't think documentation is too critical for this. Assuming it all works correctly, the only change in behavior a user/developer sees is the warning, which is consistent with other ways of interacting with the corresponding deprecated parameters and properties.
I think better typing and documentation of LayerDataTuple is worthwhile, but more as a general contribution that's not specific to this effort.


Update about-plugins.md

Fix regex equivalent example.

After thinking about it for a while, I came to the conclusion that maybe my understanding of the example might not be correct. I'm closing this and opening a new issue just to report the invalid RegExp, so @nchanged can implement a correct fix instead of this (probably incorrect) PR.


Make zig.zls.path scoped as machine-overridable.

This prevents it from being synced between machines by default, which is undesirable for people who switch between e.g. Windows and Linux.
This change aligns with how vscode-clangd handles its clangd.path setting, as an example: https://github.com/clangd/vscode-clangd/blob/eca1e05a39c4e987dca6247d825dfbe92fd5996f/package.json#L97-L102

Could you apply this to zig.path as well?

Sure, done.


[TypeChecker] Mark perf test-case for rdar://problem/22282851 as fast

Recent changes to contraction of the closure argument/parameter type
variables resulted in speed up in type-checker performance which resolved
one of existing "slow" test-cases.

@swift-ci please smoke test and merge

/cc @rudkx do you think I need to cherry-pick this to 5.0 and 4.1 as well or our "no asserts" builds set up only for master branch?

Not sure which builds we're running for those branches, but if it's not failing there we're probably fine without it (unless of course someone in the future adds those builds...).

Alright, I'll cherry-pick into 5.0 only for now, and if we ever need it will cherry-pick to 4.1 as well.


Hyperparameter selection

Hi! Has anyone experimented with hyperparameters, such as n_flows and n_mel_channels, in addition to n_channels in WN? As I understood correctly, the number of flow blocks increase a training time linearly, and n_mels is just conditioning detalization. So, what should I expect if I decrease the number of flows and increase n_mels?

I no longer have access to the samples so I can't share, but from what I've tried, decreasing n_flows quickly degrades audio quality. I was trying to reduce model size and I couldn't find any meaningful tradeoff where reduction would be worth the loss in quality, even for small values of n_flow decrease.
If you increase n_mels I think that's going to make it even harder for the model to learn, because you're increasing dimensionality, and now you'd probably need more flows, not less.

So, I've experimented with n_mels, and I conclude that n_mels slightly increase training speed (i've got good results at 350k steps with 12 batch size). Next i'll try to dance with WN parameters. Here I found, that receptive field of 3^8 points is much more than one group after "squeeze" operation in waveglow. That seems to be a bug in its architecture. So, I continue experimenting

Closing due to inactivity.


global: refactor to Vue3

Setup

[x] 1. Install clean Vue3, pug, typescript 4.1
[x] 1.1 Install additional dependences
[x] 2.1 Define project folders structure
[x] 2.2 Define project - tour logic
[x] 3. Define which Feature widgets is needed
[x] 4. Vuex - logic and structure
[x] 5. Add Languages support

Features:

[ ] 7.1 Sheet drag & drop
[ ] 7.2 Advanced sheet numeration and grouping
[ ] 7.3 Sheet color change
[ ] 7.4 Sheet text change
[ ] 7.5 Add sheet
[ ] 7.6 Remove sheet
[ ] 7.7 Sheet filtering by name
[ ] 7.8 Elements Tour
[ ] 7.9 Theme changes
[ ] 7.10 Language changes
[ ] 8 Feedback widget
[ ] 9 About widget with links to GitHub and main site
[ ] 10 Playground mode (integrated with vue-tour).
Option 1: Work inside excel: add sample sheets (for example with prefix "pl_") and give control for them only.
Option 2: Work outside excel: show fake sheets.
Option 3: Both option: tour - show how to use it

What can be used:
Sources: https://tarektouati.github.io/vue-use-web/
Dnd: https://github.com/kutlugsahin/vue-smooth-dnd

deprecated due #144


Please address suitability for untrusted inputs in docs

A question that I have run into in multiple times on different projects is: How suitable is bincode for network communication?
Example scenario
A typical scenario is a networking application that sends messages between two participants (peer-to-peer or client server). By default, one can reach for JSON at this point, as the libraries are built against a spec and are safe dealing with hostile inputs (provided they are size-limited).
bincode strikes me as something that (at least initially) was intended for trusted communication, possibly in-memory communication, potentially sacrificing support for input from untrusted sources for extra speed.
This question seems to have been asked directly or in a roundabout way in multiple other issues: https://github.com/servo/bincode/issues/216, https://github.com/servo/bincode/issues/136, https://github.com/servo/bincode/issues/221, https://github.com/servo/bincode/issues/240, https://github.com/servo/bincode/issues/255, https://github.com/servo/bincode/issues/266.
Alternatives
There is a real hole in the Rust ecosystem that yearns to be filled with a compact binary format that can be used to send unversioned, untrusted data with serde support. Certainly protobuf, captain proto, flatbuffers exist, but they all tackle a grander scope and come with extra hoops to jump through - at least I just want to slap a #[derive(Serialize)] onto my struct and send it more efficiently than JSON across the aether.
Of the available, mature alternatives, msgpack and bson are mentioned, but these are self-describing and thus "waste" space by serializing struct field names as well.
There are other non-established contenders listed in the serde docs, but many fail to address this issue in a precise manner in their docs as well.
The list
To judge suitability for using bincode for a specific project, at least the following questions need to be answered:

Is the format stable/well-defined, i.e. does not change across minor versions. This is typically important when storing data using bincode long-term.

Is the format invariant over differences in byte-order, that is will a big-endian machine produce the same output as a little-endian machine?

Is it space-efficient for binary data, i.e. will it be space efficient for large binary data?

Is it written with "hostile" data in mind? Rust's memory safety goes a long way of course, but some things like handling invalid inputs or not pre-allocating large amounts of memory when receiving a message are required, and typically a performance-security trade-off.

I may have missed some points, but these came to mind immediately.
It would be great if these could be answered in the docs - I will happily volunteer to write a note and add it to the README.md or core module docs, but each of these need an answer from someone who knows the actual source code well.
Each question will actually need two answers, one addressing the status quo and another whether or not this is an accidental or intended property. Any project that relies on bincode certainly needs to know the guarantees it can expect from future versions.
Note that answering "don't know and won't ever guarantee it" on each of these is perfectly fine - I would just like to see it written down, as I find myself in discussions about this with my colleagues fairly often and having sent them to various GitHub issues, it seems that there is a real need for this information =).
If someone could just let me know informally about the state and goals, I will do my best to turn this into a PR updating the docs.
In the meantime, thanks for six years of work that already went into this crate :)

These are the answers to the questions outlined above:

a. The library is stable across minor revisions in that the same configuration will produce the same output. New options have been added to configure the way data is encoded
b. The intention is to eventually codify the format into a specification. There will always be configuration options but these will be documented as part of the spec.

The default configuration will be invariant over byte-order. A user can set up bincode to use native-endian, in which case it will not be invariant.

bincode should be space-efficient for binary data by design. As an example, a slice of u8 will be encoded as a length and then the raw u8s

bincode attempts to protect against hostile data. There is a maximum size configuration (although not on by default), and pre-allocation size is limited based on that configuration. The structures produced by bincode should all be valid structures and deserializing will not cause UB (assuming of course that the deserialization code for the struct is safe).

https://github.com/bincode-org/bincode/issues/240 sounds relevant for protecting against inputs claiming large field sizes, maliciously or due to corruption / version mismatch / cat on keyboard using netcat.


Minor corrections

Removed language from MDN url so the reader lands on the appropriate localized page.
A couple of other minor typos.

Awesome! Thanks :)


mesh manifest diff should have text diff option

Sometimes, the text diff format (used in mesh profile diff) is easier to read than the compact diff style used in mesh manifest diff.
The request is to use the --verbose flag to cause mesh manifest diff to output a text based diff instead.

start working on this...


added the /articles endpoint. allowing both the /article and the /art…

Guys, do you agree with these changes?
The goal is to be able load the /articles?sessionID=1234... in an iframe on the zeeguu page without having to go through the login page.
Even if, in the future we have to discuss ways of not having to hardcode the sessionID in the page... A rogue extension could easily get access to the source code of a page, and then with the session ID start uploading spam on behalf of the learner.

Regarding the session security problem, I made it an issue on #39 .

As we have added issues for all idea's this pull request spawned, shall I merge this? Then I'll be able to adapt branches from this and pull request them back ;)

Yes. Please go ahead and merge.
On Mar 30, 2017 7:22 PM, "Luc van den Brand"<EMAIL_ADDRESS>wrote:

As we have added issues for all idea's this pull request spawned, shall I
merge this? Then I'll be able to adapt branches from this and pull request
them back ;)
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feat: transform-origin

Checklist

[x] iOS new arch
[x] Android new arch
[x] iOS/Android old arch
[ ] Add examples

Summary

This PR adds transform-origin support, similar to web. Spec

Why?
By default, rotate/scale/skew transforms occur around the center of the View. If we want to perform them around the top-left of the view, we need to first translate to the top/left point, perform the transform, and then translate back to the center. This can be achieved with the following steps:
 transform: [
   { translateX: -viewWidth / 2 },
   { translateY: -viewHeight / 2 },
   { scale: animatedV.value },
   { translateX: viewWidth / 2 },
   { translateY: viewHeight / 2 }
]

The above approach requires View dimensions, that need to be calculated using onLayout, measure, or using constants. Transform origin can simplify it and also bring it closer to the web feature parity.

Changelog:
[GENERAL] [ADDED] - transform-origin.
Test Plan:

Run pod install/rebuild android RN tester app and test transform origin example in Transform examples.
Test on fabric/paper architecture.

High-level thought on the approach here: Could we applytransformOrigin as we calculate the transform matrix on the ShadowNode/ShadowView instead, and avoid having to mutate the transform in the mounting layer?
An example of what's going to be incorrect here now is any of the measure callbacks which respect transforms: https://github.com/facebook/react-native/blob/0e83c53122f871f54c562b945e3cb9e2c27c406f/packages/react-native/ReactCommon/react/renderer/core/LayoutableShadowNode.cpp#L35

High-level thought on the approach here: Could we applytransformOrigin as we calculate the transform matrix on the ShadowNode/ShadowView instead, and avoid having to mutate the transform in the mounting layer?

i am currently doing it from the mounting layer because we need the View dimensions for transform origin. From high level i can think of two approaches, either get the transform in shadow node calculation from the native view or create a state for transforms in shadow node and reset it from the mounting layer. Does this make any sense?

i am currently mutating it from the mounting layer because we need the View dimensions for transform origin.

ShadowNode / ShadowView have the full layout information available, so ideally getTransform correctly represents the transform, accounting for the transformOrigin. I'd recommend making the change at that layer.
Please also add a test that shows this works correctly when animations of the transform property are used.

@javache can you check this approach? https://github.com/facebook/react-native/compare/main...intergalacticspacehighway:react-native:f/transform-origin-resolve?expand=1
It adds a resolveTransform function that returns a new transform based on the transform-origin and layoutMetrics. This makes sure we get the updated transform in shadow node's getTransform. This won't require us to mutate the transform prop. (only tested on fabric iOS. If this looks good, I can try to add it for Android/old Arch)

@intergalacticspacehighway That looks very promising! Can you add it here, and I'll add some comments?

@javache sorry for the delay, been out for a trip. I just merged the new approach here so you can review. I'll add the support for old arch and android.

@javache I've updated the code so it works on old/new arch + android/ios. However, I think there is a fundamental issue with the approach I have taken to make it work on Android and iOS old arch. Ideally, I want to implement a solution where it triggers transform updates from cpp/shadow node realm, so I don't have to repeat things for respective platforms.
i.e. once we have the layout info in shadow nodes we can trigger an imperative update call to native side to update the view transforms and not use the existing setter prop approach. wdyt? I'll have to dig more for this. Let me know what you think! The current approach works with native driver as well but has some redundancy/not very clean.

@javache picking it this week, making separate PRs. I pulled latest main and when running rn-tester, it doesn't start in fabric mode. The pod install happens with fabric enabled but the app starts in old arch. Is something changed how fabric is enabled on rn-tester. I couldn't find anything different in readme.

@javache Thank you for reviewing. I have made separate PRs and incorporated the changes you suggested. We can discuss it there.
iOS old arch - https://github.com/facebook/react-native/pull/38514
Android - https://github.com/facebook/react-native/pull/38558
iOS fabric arch - https://github.com/facebook/react-native/pull/38559

Sorry for the delayed reviews, I was on parental leave. I'll get to this this week!

Closing this PR as reviews are happening on the split PR's.


Draft principles documents, adapted lightly from NSLS-II guide.

Adapted from Guiding Design Principles
Incorporating a great demonstration of better OO design from SE for SC
Split into two pages, as discussed

The changes look good to me. This is ready from my point of view.


Added support for the 0C45:7402 TEMPerHumM12V1.2, which uses a Si7021 sensor.

Verified to match another hygrometer to within 1% RH and 3 °C.
Here are some pictures if you're interested: http://u.forre.st/TEMPerHumM12V1.2/

Yes, this works for me.  Actually I had to make a further minor enhancement to support TEMPerHumM12V1.3 which is what my device is.  I don't seem to be able to submit this mod though.  Sorry I don't know how to use git.  In SVN speak I am trying to commit a change to the TEMPerHum12V1.2 branch.  Maybe I can't because it's not been merged yet.  I have some files and they work.
I have tried to attach the patch.  Sorry I don't know what I'm doing.
TEMPerHUM12V1.3.patch.txt

@davet2001 I created a pull request for your branch: #40


Update README.md

Overview
Update requirement passage in README
Closes #17
Checklist before merge

[x] Update the CHANGELOG.md

@travissouthard
Kindly have a look

Hi @travissouthard are there any changes required in the PR to be merged to the project.


Allow using a custom Biome binary for development

We should provide a way of loading a custom biome binary for development purpose.

Not sure it's needed, the development workflow of zed is very simple: you just load this very repository as an extension and it will work.

Good idea, may be possible with the LSP settings interface.

Would that be configurable in the end user's configuration?


:no_entry: (EARLY) :sparkles: Allow delimiter to be configured for path and paths parameters

With the above changes:
from typing import Sequence

from neoclient import Path, get
from neoclient.dependencies import status_code

@get("https://httpbin.org/status/{codes}", response=status_code)
def status(codes: Sequence[int] = Path(delimiter=",")) -> int:
    ...

>>> status((200, 201, 202))
202
>>> status((200, 201, 202))
201

Path(...), Paths(...), @path(...), @path_params(...) all tested and appear to be working well


not working

kaspersky internet security detects a Trojan and deletes the file and does not work pls help

Well, disable the security as long as you need to use it, and then enable it again.

Should be fixed, updates will take place in a few minutes. If for some reason your antivirus still falsely detects this extension, do as @moonstarcat524 said and disable it while using UltraType.

OK
On Tue, Dec 12, 2017 at 8:37 PM, ultratype<EMAIL_ADDRESS>wrote:

Should be fixed, updates will take place in a few minutes. If for some
reason your antivirus still falsely detects this extension, do as
@moonstarcat524 https://github.com/moonstarcat524 said and disable it
while using UltraType.
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Add Frontend Notebook

About
Hello Sir,
I want to add a new Frontend Notebook
This is a Simple Virtual Notebook Where we can write our daily work or it's like a to-do list
Screenshot

Additional Context
Please assign me this issue under OSEN.

@Shu12388y Please assign me this issue under OSEN.


[backport] Enable strict xfail in pytest

Backport of #5407 by @kmaehashi

[automatic post] Jenkins, test this please.

Jenkins CI test (for commit 5778b7055a0d9a96c77bb31684c2a2580de35640, target branch v9) succeeded!

/test