bugfix: protobuf 版本锁定

Codecov Report

Merging #710 (7462234) into v2.6.x_develop (d326e15) will not change coverage.
The diff coverage is n/a.

@@               Coverage Diff               @@
##           v2.6.x_develop     #710   +/-   ##
===============================================
  Coverage           61.80%   61.80%
===============================================
  Files                 441      441
  Lines               28101    28101
===============================================
  Hits                17368    17368
  Misses              10733    10733

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Small bug fix and simplify messages + change env. var names

This is a small fix:
fix '/login' issue when use other schema name (it's related to #25)
fix some error message

Also fix for #28
Ready for merge @elitan :wink:


fixed typo

Pull request type

Please check the type of change your PR introduces:

[ ] Bugfix
[ ] Feature
[ ] Code style update (formatting, renaming)
[x] Refactoring (no functional changes, no api changes)
[ ] Build related changes
[ ] Documentation content changes
[ ] Other (please describe):

What is the current behavior?

Issue Number: N/A
What is the new behavior?

Other information

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 43.14%. Comparing base (b5d1297) to head (8276521).

Additional details and impacted files
@@            Coverage Diff             @@
##           master    #1375      +/-   ##
==========================================
+ Coverage   41.86%   43.14%   +1.27%
==========================================
  Files         351      288      -63
  Lines       35226    25736    -9490
==========================================
- Hits        14748    11103    -3645
+ Misses      19996    14181    -5815
+ Partials      482      452      -30

Flag
Coverage Δ

go-1.20.x
43.14% <ø> (-0.54%)
:arrow_down:

go-1.21.x
?

go-1.22.x
?

macOS
43.14% <ø> (+1.75%)
:arrow_up:

ubuntu
?

unit
43.14% <ø> (+1.27%)
:arrow_up:

windows
?

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Update manage-portal.md

Changed the steps for setting the owner of a portal app.  People have been selecting the enterprise app instead of the needed app registration.

Thanks @aapfau for the suggestion. I've implemented the suggested changes. The updated document will be published in the next document update cycle.
Closing this PR.


bot music Version 0.3.5

Soundcloud not working with update bot music 0.3.5
please solve the problem

Duplicate of #750


How to rotate tilemap?

Thank you for huge work. I saw, there are couple of methods setAxisAngle and rotationTo, but I have not clue how to use them. Please, can you help with that. Thank you!

I'm not sure which methods you are referring to, there are no such functions in this library.
Are you trying to rotate specific tiles, or rotate an entire layer? The former is supported and the rotation is done in Tiled, the later is not supported.

Closing this, I think this was in the wrong repo.


Move osprepare from ciao

Fixes: #110
Signed-off-by: Ganesh Maharaj Mahalingam<EMAIL_ADDRESS>

Coverage remained the same at 68.916% when pulling 6d2eecf0fd9b619ecadfef784a1b7e0cdec2f217 on ganeshmaharaj:move-osprepare into 4004e359fba715a6d15665b60e90c5fc063805c3 on intel:master.


github sample fails to comple

Howdy. I'm not able to replicate the github project. When I attempt to run npm build, I get the following error:
`
FunkBook-Pro:github pdavisjones$ npm run build

<EMAIL_ADDRESS>build /Users/pdavisjones/Documents/Coding/apps-script/gmail-add-ons-samples/github
gulp

fs.js:25
'use strict';
^
ReferenceError: internalBinding is not defined
at fs.js:25:1
at req_ (/Users/pdavisjones/Documents/Coding/apps-script/gmail-add-ons-samples/github/node_modules/natives/index.js:137:5)
at Object.req [as require] (/Users/pdavisjones/Documents/Coding/apps-script/gmail-add-ons-samples/github/node_modules/natives/index.js:54:10)
at Object. (/Users/pdavisjones/Documents/Coding/apps-script/gmail-add-ons-samples/github/node_modules/graceful-fs/fs.js:1:37)
at Module._compile (internal/modules/cjs/loader.js:816:30)
at Object.Module._extensions..js (internal/modules/cjs/loader.js:827:10)
at Module.load (internal/modules/cjs/loader.js:685:32)
at Function.Module._load (internal/modules/cjs/loader.js:620:12)
at Module.require (internal/modules/cjs/loader.js:723:19)
at require (internal/modules/cjs/helpers.js:14:16)
npm ERR! code ELIFECYCLE
npm ERR! errno 1
npm ERR<EMAIL_ADDRESS>build: gulp
npm ERR! Exit status 1
npm ERR!
npm ERR! Failed at the<EMAIL_ADDRESS>build script.
npm ERR! This is probably not a problem with npm. There is likely additional logging output above.
npm ERR!      /Users/pdavisjones/.npm/_logs/2019-05-16T20_48_36_612Z-debug.log
`

What version of node are you using?

Looks related to https://github.com/gulpjs/gulp/issues/2246 and just verified workaround there works. I'll take a look at updating the dependencies shortly.
Until then, this should work on Node 11+:
npm install
npm install<EMAIL_ADDRESS>npm run build

Thanks, Steve. I'll try to replicate steps with the workaround on my end.

Totally works. Thanks! 👍

Reopening to track fixing this in package.json


Nested Arrays

Is there a way to get the 1st value out of a nested array?
https://phantombuster.s3.amazonaws.com/12AdE4Q3Tac/ss3CH6otUeWB7fL14cmpXA/rsn-linkedin-profile-scraper.json
I use query as my filter. I’m able to get basic information such as first name {{general.firstname}}. However I’m not sure if I’m able to grab job titles with the current code. {{jobs.jobtitle}} won’t work because jobs is an array where they may have 4 or 8 job titles.
If I was able to get even the 1st or current job title that’d be great.

@Illest-Maestro thanks for pointing out this opportunity to improve the code.  I added support for nested arrays as described in your use case.  Please try it and let me know if you have issues.


More enhancements to the join retry flow

Couple things I saw playing more with it.

Remembers threadName on a retry request
If progress was dismissed and then user tries to accept the invite again, it will undismiss the progress so they have some feedback

okay, this guy is gtg. slipped in ui for feedback on notification based invite accept.
flow is, click notification accept -> sends user to the Groups screen so they can see the joining feedback -> opens the group if it's successful


custom buttons aren't working

just want to add id's to 2 buttons, here is code:
var viewer = OpenSeadragon({
id: "heaven1",
prefixUrl: "/assets/images/manuscripts/heaven/",
toolbar: "navigation-pane",
zoomInButton:   "zoom-in",
zoomOutButton:  "zoom-out",
showNavigator: true,
panHorizontal:  true,
defaultZoomLevel:   1,
minZoomLevel:   1,
maxZoomLevel:   3,
visibilityRatio:    1,
constrainDuringPan: true,
tileSources: [{
type: 'legacy-image-pyramid',
levels: [{
url: "assets/images/manuscripts/heaven/heaven4.jpg",
height: 2133,
width: 1500
}],}]
});
This doesn't add  the IDs to the buttons and shows all normal buttons.

I am still having this problem.
These are my custom zoom in and out buttons
<div class="plotMap__zoom-controls">
     <button id="ZoomIn">+</button>
     <button id="ZoomOut">-</button>
</div>

And in OpenseaDragon I add them like this
OpenSeadragon({
    id: "example-xmlhttprequest-for-info-json",

    prefixUrl: "https://static.zoomhub.net/openseadragon-images/",

    tileSources: {
      type: "image",
      url: "imgurl",
    },

    visibilityRatio: 1,
    constrainDuringPan: true,

    showNavigator: true,
    showNavigationControl: false,
    navigatorAutoFade: false,
    navigatorPosition: "ABSOLUTE",
    navigatorTop: "24px",
    navigatorLeft: "24px",
    navigatorHeight: this.navigatorImgHeight,
    navigatorWidth: "145px",
    zoomPerClick: 1,

    defaultZoomLevel: 1,
    minZoomLevel: 1,
    zoomInButton: "ZoomIn",
    zoomOutButton: "ZoomOut",
});

But when I click my custom buttons, nothing happens. I added a video of clicking the buttons.
https://gyazo.com/1b278ab8f8cdc3336cb7f5f2bce7d11c

@liekeheijne This isn't well documented, but the zoom buttons use zoomPerClick to know how much to zoom. Since you've set it to 1 it's not zooming at all. I assume you set it that way to disable click to zoom? An alternate way to do so is with gestureSettingsMouse: { clickToZoom: false }.


Capture useful trigger log queries

There's lots of useful queries for exploring the trigger log table that we seem to provide to customers regularly. If we could capture those in CLI commands that could be really useful.

Hi @iamjem I am curious? Which would those queries be?

@codingjoe an implicit part of this is the Connect team going through past emails and support tickets to find the most common/useful queries we've helped customers come up with.

I see.
@sigmavirus24 completely off topic, but some colleges of mine put all PyCQA linters on AWS lambda and integrated them via GitHubs new Check API. I'd really like to get your opinion on that: https://lambdalint.github.io/ (all open source of course)


new use and useOptimistic hooks in React Native

New Version
<EMAIL_ADDRESS>Old Version
<EMAIL_ADDRESS>Issue and Reproduction Steps
TL;DR — bumping React to canary (e.g<EMAIL_ADDRESS>won't work. Don't try it.
I wanted to use the new

use (https://react.dev/reference/react/use) and
useOptimistic (https://react.dev/reference/react/useOptimistic) hooks in React Native.

So, I bumped react to canary.
Then I got a runtime error:

dispatcher.use is not a function (it is undefined)
dispatcher.useOptimistic is not a function (it is undefined)

Then I tried to figure out what's going on.
I finally stumbled upon: https://github.com/facebook/react-native/blob/main/packages/react-native/Libraries/Renderer/README.md
Seems like we're going to need to wait until React Native implements these new hooks on the dispatcher side of things before we can use them.
It was very hard to find all this out, so I'm putting this here to help others trying to find out this info.

TL;DR — bumping React to canary (e.g<EMAIL_ADDRESS>won't work. Don't try it.

Exactly you can't just bump the React version. It's explained here:
https://github.com/facebook/react-native/blob/main/packages/react-native/Libraries/Renderer/README.md
You'll have to wait for a stable release of React with the new hooks, and then we'll include them in a stable release of React Native


Regenerate policies based on GUI changes

The GUI is going to whack the database directly.  Once it does so we need to regenerate policies based on those changes.

Addressed in PR #54


Implement full-text indexing for attached documents

Full-text indexing with the ES Mapper Attachments Plugin
I propose to use this plugin to implement the indexing of attached documents:
Mapper Attachments Plugin
It is a fast and easy solution, maintened by the Elasticsearch team.
As described in the link above, it uses the Tika library to analyze the content of a file.
A first example
The Mapper attachment plugin for elasticsearch provides you a new field type named attachment.  Here for instance i create a tind-doc index, with a tind_document type, with 3 properties [filename, insert_date, file]. The file properties has the type attachment with his configuration:
PUT tind-doc/
{
    "mappings": {
      "tind_document": {
        "_source":{
          "excludes":["file"]
        },
        "properties": {
          "file": {
            "type": "attachment",
            "fields": {
              "content": {
                "type": "string",
                "term_vector": "with_positions_offsets",
                "store":"yes"
              },
              "author": {
                "type": "string"
              },
              "title": {
                "type": "string"
              },
              "name": {
                "type": "string"
              },
              "date": {
                "type": "date",
                "format": "strict_date_optional_time||epoch_millis"
              },
              "keywords": {
                "type": "string"
              },
              "content_type": {
                "type": "string"
              },
              "content_length": {
                "type": "integer"
              },
              "language": {
                "type": "string",
                "store":"yes"
              }
            }
          },
          "filename": {
            "type": "string"
          },
          "insert_date": {
            "type": "date",
            "format": "strict_date_optional_time||epoch_millis"
          }
        }
      }
    }
}

Once you defined the  "type":"attachment" there are several field provide automatically by the Tika parser that could be set up with a proper mapping customization.  (by default the language recognition is disabled, look at the link to enable it).
Anyway i found that most of this field , in our case, are not properly recognited, and we can get rid of them.
The most important is the content field that is where our file will be inserted, the "term_vector" option is required for the highlights feature that will be showed later.
Index a document
For indexing a document ES require a base64 encoded string. Below i show a working script for encode the document and put it into ES.
class TindDocument(DocType):
    filename = String()
    insert_date = Date()
    file = Attachment(fields={
        'content': String(term_vector="with_positions_offsets", store=True),
    })

    class Meta:
        index = 'tind-doc'

connections.create_connection(hosts=['localhost'])

for input_file in doc_files:
    with open(input_file, "rb") as ifd:
        b = base64.b64encode(ifd.read())

    attachment = dict(
        _content=b,
        _indexed_chars=-1,
        _detect_language=True,
    )

    firstdoc = TindDocument(
        filename=input_file, insert_date=datetime.now(), file=attachment)
    firstdoc.save()

There are some options that you can provide.

The _detect_language if you want to say ES to try to detect the language of the document ( i found that it fails for arabic and chinese) .
You can use the _indexed_chars to limit the index to a fixed amount of char ( -1 for the full document, 100k default )

Search
Here are some search examples:
Note the highlights feature in the results, and the bad recognition of the chinese language.

Aggregations:

Some performance measures
More tha 300 documents indexed in less than 20 seconds (from 20k to 9M per document):

Some measure made with ES Marvel. The first is about the index.

The second about the node (the number of documents comprehend even the kibana and marvel data)

Next step:
Figure out how to integrate this feature in invenio

Sprint planned for 2016-10-19 09:00. cc @inveniosoftware/developers

Looks like the work to integrate it is mostly is invenio-records-files: https://github.com/inveniosoftware/invenio-records-files/issues/47


Allow legends on leaflet heatmaps

A container for the legend will have to be specified in order for it to
work with leaflet maps.

+1, perhaps one or two extra pointers at http://www.patrick-wied.at/static/heatmapjs/example-legend-tooltip.html

+1


URI updates

Lots of "little tidyups" (which I've separated into separate commits for clarity), but the main thing this fixes is that the GitHub API token wasn't being passed to all GitHub API requests, which meant that if GitHub was being rate-limited, then running any of the commands listed at https://github.com/raspberrypi/rpi-update?tab=readme-ov-file#using-github-artifacts-from-automated-builds would just fail with a cryptic "Invalid git hash specified" error. I bet you'll never guess how I discovered this error... :laughing:

I think all the commits look sane.
And rpi-update with default options still runs for me.
Lets merge it and see.


More missing event types

May we please have a refresh on available event types and their definitions?
AtpGoodMail, Expire (multiple Actions) and Receive (multiple Actions) events are several that are missing.
Thank you

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

ID: 1fb20809-8f21-dfd3-23bf-bbfb82679619
Version Independent ID: be54b158-1672-5ae9-6a6d-139a7850c67b
Content: Get-MailTrafficReport (exchange)
Content Source: exchange/exchange-ps/exchange/reporting/Get-MailTrafficReport.md
Service: exchange-powershell
GitHub Login: @chrisda
Microsoft Alias: chrisda

event types needing complete definitions:
Event types not listed in documentation.
AdvancedProtectionMalware
AtpGoodMail
DLPMessages
Expire
Receive
SpoofMail
TransportRuleMessages
thanks in advance!

@mrkeiths and @jdrecklessworld thank you for this feedback.
I'm adding these EventTypes with the description. If you want to double check, I will appreciate that.

@dariomws306  Thank you very much for the contribution and updating the documentation with PR. @mrkeiths Hope this update is helpful for you. Thanks for taking out some time to open the issue. Appreciate and encourage you to do the same in future also.


This makes Chem.SanitizeMol significantly faster when dealing with mo…

…lecules with lots of disconnected fragments (like a box of water).
The following is the runtime of Chem.SanitizeMol while adding 10,000
waters with explicit hydrogens when running Chem.SanitizeMol on every
1,000th water added.
Before:
0 add_water = 0.00007s
0 Chem.SanitizeMol = 0.01991s
1000 add_water = 0.00009s
1000 Chem.SanitizeMol = 0.99659s
2000 add_water = 0.00013s
2000 Chem.SanitizeMol = 3.94565s
3000 add_water = 0.00018s
3000 Chem.SanitizeMol = 8.94760s
4000 add_water = 0.00023s
4000 Chem.SanitizeMol = 15.75187s
5000 add_water = 0.00035s
5000 Chem.SanitizeMol = 24.59318s
6000 add_water = 0.00048s
6000 Chem.SanitizeMol = 37.23530s
7000 add_water = 0.00042s
7000 Chem.SanitizeMol = 47.70860s
8000 add_water = 0.00105s
8000 Chem.SanitizeMol = 62.21912s
9000 add_water = 0.00056s
9000 Chem.SanitizeMol = 80.08511s
After:
0 add_water = 0.00008s
0 Chem.SanitizeMol = 0.02371s
1000 add_water = 0.00006s
1000 Chem.SanitizeMol = 0.02986s
2000 add_water = 0.00013s
2000 Chem.SanitizeMol = 0.06513s
3000 add_water = 0.00018s
3000 Chem.SanitizeMol = 0.09535s
4000 add_water = 0.00025s
4000 Chem.SanitizeMol = 0.12644s
5000 add_water = 0.00044s
5000 Chem.SanitizeMol = 0.15263s
6000 add_water = 0.00050s
6000 Chem.SanitizeMol = 0.19130s
7000 add_water = 0.00040s
7000 Chem.SanitizeMol = 0.21398s
8000 add_water = 0.00046s
8000 Chem.SanitizeMol = 0.24383s
9000 add_water = 0.00054s
9000 Chem.SanitizeMol = 0.28527s
time_sssr_on_water.txt

Unfortunately, this change was too simplistic. Fragments with 3 atoms can actually be in a ring. In order to skip waters, will need to implement a more rigorous check in the case of 3 atoms to check the atom degrees in the fragment. Closing this pull request for now, will open another in a bit.


Error parsing syntax file markdown

Description of the problem or steps to reproduce
using the runtime/syntax/markdown.yaml from this git repo raises error:
Error parsing syntax file markdown: interface conversion: interface {} is nil, not []interface {}
to reproduce, just copy this file to ~/.config/micro/syntax/ and run micro
to workaround, i add rules: [] to the section with start/end.
Specifications
Version: 2.0.14
Commit hash: 04c5770
OS: Fedora 41 on WSL 2 on Windows 11
Terminal: Windows Terminal 1.21.2911.0

Hm, more or less easy to explain:
The removal of the empty rules: [] was introduced with #3458 like the support of it too.
These "new" rules are compatible with the master resp. nightly only, since there is no new 2.0.15 release yet.
Using them with the actual release is expected to fail.
For your release you should use the one included in the v2.0.14 tag:
https://github.com/zyedidia/micro/blob/04c577049ca898f097cd6a2dae69af0b4d4493e1/runtime/syntax/markdown.yaml#L49


Support for defaultProps will be removed

Hi, I become all the time this warning, it looks like you use defaultProps. Could you please fix this for production? Thanks!
Warning: ImageMapper: Support for defaultProps will be removed from function components in a future major release. Use JavaScript default parameters instead.
at ImageMapper (webpack-internal:///(ssr)/./node_modules/react-img-mapper/dist/ImageMapper.js:73:30)
at FloorPlan (webpack-internal:///(ssr)/./src/app/loungetool/Floorplan.tsx:23:96)
at div
at eval (webpack-internal:///(ssr)/./node_modules/@emotion/react/dist/emotion-element-6bdfffb2.esm.js:61:74)
at Container (webpack-internal:///(ssr)/./node_modules/@mui/system/esm/Container/createContainer.js:114:23)
at LoungeReservations (webpack-internal:///(ssr)/./src/app/loungetool/page.tsx:37:86)
at StaticGenerationSearchParamsBailoutProvider (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/static-generation-searchparams-bailout-provider.js:15:11)
at Lazy
at InnerLayoutRouter (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:239:11)
at RedirectErrorBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/redirect-boundary.js:71:9)
at RedirectBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/redirect-boundary.js:79:11)
at NotFoundBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/not-found-boundary.js:62:11)
at LoadingBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:313:11)
at ErrorBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/error-boundary.js:128:11)
at InnerScrollAndFocusHandler (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:151:9)
at ScrollAndFocusHandler (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:226:11)
at RenderFromTemplateContext (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/render-from-template-context.js:15:44)
at Lazy
at OuterLayoutRouter (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:322:11)
at Lazy
at InnerLayoutRouter (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:239:11)
at RedirectErrorBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/redirect-boundary.js:71:9)
at RedirectBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/redirect-boundary.js:79:11)
at NotFoundErrorBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/not-found-boundary.js:54:9)
at NotFoundBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/not-found-boundary.js:62:11)
at LoadingBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:313:11)
at ErrorBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/error-boundary.js:128:11)
at InnerScrollAndFocusHandler (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:151:9)
at ScrollAndFocusHandler (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:226:11)
at RenderFromTemplateContext (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/render-from-template-context.js:15:44)
at Lazy
at OuterLayoutRouter (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/layout-router.js:322:11)
at Lazy
at body
at ThemeProvider (webpack-internal:///(ssr)/./node_modules/@mui/private-theming/ThemeProvider/ThemeProvider.js:45:13)
at ThemeProvider (webpack-internal:///(ssr)/./node_modules/@mui/system/esm/ThemeProvider/ThemeProvider.js:58:13)
at ThemeProvider (webpack-internal:///(ssr)/./node_modules/@mui/material/styles/ThemeProvider.js:26:18)
at LocalizationProvider (webpack-internal:///(ssr)/./node_modules/@mui/x-date-pickers/LocalizationProvider/LocalizationProvider.js:41:25)
at html
at RootLayout (webpack-internal:///(ssr)/./src/app/layout.tsx:21:23)
at Lazy
at RedirectErrorBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/redirect-boundary.js:71:9)
at RedirectBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/redirect-boundary.js:79:11)
at ReactDevOverlay (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/react-dev-overlay/internal/ReactDevOverlay.js:66:9)
at HotReload (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/react-dev-overlay/hot-reloader-client.js:296:11)
at Router (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/app-router.js:155:11)
at ErrorBoundaryHandler (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/error-boundary.js:99:9)
at ErrorBoundary (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/error-boundary.js:128:11)
at AppRouter (webpack-internal:///(ssr)/./node_modules/next/dist/client/components/app-router.js:421:13)
at Lazy
at Lazy
at /Users/noahpique/Documents/GitHub/nightpilotapp/node_modules/next/dist/compiled/next-server/app-page.runtime.dev.js:35:381577
at /Users/noahpique/Documents/GitHub/nightpilotapp/node_modules/next/dist/compiled/next-server/app-page.runtime.dev.js:35:381577
at ServerInsertedHTMLProvider (/Users/noahpique/Documents/GitHub/nightpilotapp/node_modules/next/dist/compiled/next-server/app-page.runtime.dev.js:39:17605)

Hello @tecnovel, duplicate of https://github.com/img-mapper/react-img-mapper/issues/66


Creating new project in nativescript not working! Resource ID #0xfffffff6

From @tahir-jamil on November 6, 2018 18:45
hear is the error logs for new project

System.err: java.lang.RuntimeException: Unable to resume activity {org.nativescript.voteCandidate/com.tns.NativeScriptActivity}: android.content.res.Resources$NotFoundException: Resource ID #0xfffffff6

issue to reproduce
tns create new-angular --ng
tns debug android
Copied from original issue: NativeScript/nativescript-angular#1591

Issue moved to NativeScript/android-runtime #1205 via ZenHub

Issue moved to NativeScript/android-runtime #1204 via ZenHub


add check for when property at group and item level when determining required error state

What this PR does / why we need it:

fixes issue with required fields blocking when they're hidden

Which issue(s) this PR fixes:

Fixes # https://app.shortcut.com/replicated/story/72034/restore-hangs-when-using-rabbitmq-clusters
Special notes for your reviewer:

Steps to reproduce

Does this PR introduce a user-facing change?

none

Does this PR require documentation?

none

@rianfowler Please remove Fixes # https://app.shortcut.com/replicated/story/72034/restore-hangs-when-using-rabbitmq-clusters from the PR description.
as the fix for that issue is different and still in WIP

[sc-28650]


[VL]Bad memory usage with Spark speculation, possible memory leakage

Backend
VL (Velox)
Bug description
While running TPCDS with spark.speculation=true, we meet the Bad memory usafe problem. It seems that we have some memory unreleased after task is killed.
terminate called after throwing an instance of 'facebook::velox::VeloxRuntimeError'
  what():  Exception: VeloxRuntimeError
Error Source: RUNTIME
Error Code: INVALID_STATE
Reason: Bad memory usage track state: Memory Pool[op.0.0.0.TableScan LEAF MALLOC track-usage thread-safe]<unlimited max capacity unlimited capacity used 24.00KB available 1000.00KB reservation [used 24.00KB, reserved 1.00MB, min 0B] counters [allocs 27, frees 26, reserves 0, releases 1, collisions 0])>
Retriable: False
Expression: (usedReservationBytes_ == 0) && (reservationBytes_ == 0) && (minReservationBytes_ == 0)
Function: ~MemoryPoolImpl
File: /code/gluten/ep/build-velox/build/velox_ep/velox/common/memory/MemoryPool.cpp
Line: 393
Stack trace:
# 0  _ZN8facebook5velox7process10StackTraceC1Ei
# 1  _ZN8facebook5velox14VeloxExceptionC1EPKcmS3_St17basic_string_viewIcSt11char_traitsIcEES7_S7_S7_bNS1_4TypeES7_
# 2  _ZN8facebook5velox6detail14veloxCheckFailINS0_17VeloxRuntimeErrorERKSsEEvRKNS1_18VeloxCheckFailArgsET0_
# 3  _ZN8facebook5velox6memory14MemoryPoolImplD2Ev
# 4  _ZNSt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EE24_M_release_last_use_coldEv
# 5  _ZN8facebook5velox4exec4TaskD2Ev
# 6  _ZNSt15_Sp_counted_ptrIPN8facebook5velox4exec4TaskELN9__gnu_cxx12_Lock_policyE2EE10_M_disposeEv
# 7  _ZNSt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EE24_M_release_last_use_coldEv
# 8  _ZN6gluten34WholeStageResultIteratorFirstStageD0Ev
# 9  _ZNSt16_Sp_counted_baseILN9__gnu_cxx12_Lock_policyE2EE10_M_releaseEv
# 10 Java_io_glutenproject_vectorized_ColumnarBatchOutIterator_nativeClose
# 11 0x00007fc74e896768
# 12 0x00007fc74e47a37c

Spark version
Spark-3.3.x
Spark configurations
spark.speculation true
System information
The latest commit: e6ec25135ce53673e7020791772b36c78304fa98
OS: CentOS7.6
GCC: 12.1
Relevant logs
No response

@jackylee-ch thanks for reporting, could you please share more settings on speculation testing, other than spark.speculation=true ?
thanks, -yuan

Is it a valid commit revision ?
git log e6ec25135ce53673e7020791772b36c78304fa98
fatal: bad object e6ec25135ce53673e7020791772b36c78304fa98

Oh, sorry, the commit e6ec25135ce53673e7020791772b36c78304fa98 is from https://github.com/oap-project/gluten/pull/2888 before it is merged. The actual main commit is a06e4f0a4662d69623c3b62cd87d013237e33b45

Have you try to fix that? if not, I can submit a fix.

Have you try to fix that? if not, I can submit a fix.

I have not found the way to fix it. It' greate if you can fix it right now.

https://github.com/oap-project/gluten/pull/2965 this pr should fix above error, but I'm not sure this is the root cause.
The root cause we need to solve is release all memory when speculation task finished/killed.

Could you share the speculation task's execution plan? which means the executed operator/RDD of speculation task.

CC @zhztheplayer

Thanks! you can try that patch if you would to, and hope give more feedbacks on this case.

@Yohahaha I have tried the https://github.com/oap-project/gluten/pull/2965, and still find this problem in q3.
The related physical plan for the failed stage in q3 is bellow.
<img width="819" alt="image" src="https://github.com/oap-project/gluten/assets/10897625/0e961ee6-6cab-496d-9f61-5dd7624c8c22">

@jackylee-ch what about q60?

@jackylee-ch what about q60?

we still have the problem, it is not fixed

@jackylee-ch Was there any other abnormal log above the error message you pasted?

@jackylee-ch Also, is memory leak accurate to describe this issue? Can you elaborate on the leakage part?

@jackylee-ch Also, is memory leak accurate to describe this issue? Can you elaborate on the leakage part?

Compared with memory leak, I prefer that some memory is not closed normally during task killing, because each time this problem is reported, it is accompanied by TaskKilledException .

Compared with memory leak, I prefer that some memory is not closed normally during task killing, because each time this problem is reported, it is accompanied by TaskKilledException .

Is the executor still alive after getting this error?

Is the executor still alive after getting this error?

No, it is terminated because of this problem.

@zhztheplayer @Yohahaha  Have you tried run TPCDS with speculation? It should be easy to reproduct.

@zhztheplayer @Yohahaha Have you tried run TPCDS with speculation? It should be easy to reproduct.

I'll have a try. Is spark.speculation=true enough for reproducing the issue?

Basically, spark.speculation=true can reproduce the problem. However if your environment is relatively good overall and rarely run speculative tasks, consider setting more aggressive configurations. Such as spark.speculation.multiplier=1.1, spark.speculation.quantile=0.3


Error: Unsupported package manager version.

What version of Turborepo are you using?
@latest
What package manager are you using / does the bug impact?
pnpm
What operating system are you using?
Mac
Describe the Bug
unable to install turborepo from scratch using a mac (m1) / pnpm
Expected Behavior
install turborepo
To Reproduce
dst@MBP Playground % npm -v
8.9.0
dst@MBP Playground % node -v
v18.2.0
dst@MBP Playground % pnpm -v
6.11.0
dst@MBP Playground % pnpx create-turbo@latest
✔ Install the following package: create-turbo@latest? (Y/n) · true
Packages: +156
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Packages are hard linked from the content-addressable store to the virtual store.
Content-addressable store is at: /Users/dst/.pnpm-store/v3
Virtual store is at:             node_modules/.pnpm
Progress: resolved 156, reused 156, downloaded 0, added 156, done
/Users/dst/.pnpm-store/v3/tmp/_npx/25248/5:

create-turbo 1.4.5

TURBOREPO

Welcome to Turborepo! Let's get you set up with a new codebase.

? Where would you like to create your turborepo? ./my-turborepo
? Which package manager do you want to use? pnpm
Aborting installation.
Unexpected error. Please report it as a bug:
Error: Unsupported package manager version.
at run (/Users/dst/.pnpm-store/v3/tmp/_npx/25248/5/node_modules/.pnpm/create-turbo@1.4.5/node_modules/create-turbo/dist/index.js:324:11)
at process.processTicksAndRejections (node:internal/process/task_queues:95:5)
A new version of create-turbo is available!
You can update by running: yarn global add create-turbo
dst@MBP Playground %

Tried to figure it out over discord, a guy named "Matt" mentioned that this is probably the best way to find a solution. thanks in advance.

In v1.4.5, pnpm6 isn't supported: https://github.com/vercel/turborepo/blob/v1.4.5/packages/create-turbo/src/constants.ts#L26-L34
So we need a release after https://github.com/vercel/turborepo/pull/1837 was merged. cc @tknickman @nathanhammond

Release in flight: https://github.com/vercel/turborepo/actions/runs/3011563882
1.4.6 will address this.


ModuleNotFoundError: No module named 'duckietown_world'

When i run:
python log.py
I got this error:
Traceback (most recent call last):
File "log.py", line 7, in
from duckietown_rl.gym_duckietown.simulator import Simulator
File "../duckietown_rl/gym_duckietown/simulator.py", line 10, in
from duckietown_world.world_duckietown.pwm_dynamics import get_DB18_nominal, get_DB18_uncalibrated
ModuleNotFoundError: No module named 'duckietown_world'

Hi Shitianyu,
As the error says, you are lacking the module "duckietown_world" and you can resolve the issue by installing that module.
I assume you are executing the code on your local PC, cause there is no such error when executing the code on Colab. You might want to install the packages the way they are installed on Colab. But, one might install "duckietown_world" module with the following code:
pip install duckietown-world
The code on Colab does not actually install "duckietown-world" but another version of it which is specifically built for the "daffy" branch of "gym-duckietown" module (See here). And it's installed with the following code:
pip install duckietown-world-daffy==5.1.2

Thanks for your reply! It works now!👍


Autostyling histogram widget points: style by size or color? I say both explained here

@fdansv @javisantana @saleiva @andrewxhill
Need your opinions about this...
Talked with Fran today about autostyling for the histogram widget > point features and there is a question about autostyling size vs. color.
The questions are:

when do we use size vs. color?
if using size, is it based on the data's distribution (like we've defined for the color ramps)?

Here are my thoughts, and I'd love to hear what you think and/or if there is another way to think about this within the larger context that I haven't considered.
When to use size vs. color?
My initial thought here is to base default styling off the number of points with the following criteria

if we have a large number of points, default to color and introduce size through zoom
if we have less information, default to symbol size and color

What we'd be doing in both cases is conjugating visual variables and do what in cartography they refer to as redundant symbolization. In all cases, mutli-scale styling is important.
Here are the two workflows:
Large number of points

Autostyling for histogram widget is activated
Autostyling would color each point depending on its bin value using the ramp that we've defined for its  distribution
As we zoom in (zooming out would trigger the opposite behavior) the point symbols would keep their color through all zooms but at a certain zoom (TBD) the symbol would also get sized according to our classed proportional symbol specs

Small number of points

Autostyling for histogram widget is activated
Each point would get sized based on our classed proportional symbol specs and also get colored based on our defined ramp for its distribution

The reason I think we should do the redundant symbology is because if I remember correctly in Fran's demo during the last product meeting, the histogram bars on the widget get colored and function as a legend for the autostyled features on the map. So if we keep consistent with coloring and also use size through zoom level, it will be good. If for example we only used size, we wouldn't be able to associate the autostyled points with their associated values on the histogram bars.
What do you guys think?

Hey mamata I think is Great and it also removes some compkexity when
applying more than one style through the widgets.
Lets do that :)
On May 5, 2016 3:08 AM, "Mamata Akella"<EMAIL_ADDRESS>wrote:

@fdansv https://github.com/fdansv @javisantana
https://github.com/javisantana @saleiva https://github.com/saleiva
@andrewxhill https://github.com/andrewxhill
Need your opinions about this...
Talked with Fran today about autostyling for the histogram widget > point
features and there is a question about autostyling size vs. color.
The questions are:

when do we use size vs. color?
if using size, is it based on the data's distribution (like we've
defined for the color ramps)?

Here are my thoughts, and I'd love to hear what you think and/or if there
is another way to think about this within the larger context that I haven't
considered.
When to use size vs. color?
My initial thought here is to base default styling off the number of
points with the following criteria

if we have a large number of points, default to color and introduce
size through zoom
if we have less information, default to symbol size and color

What we'd be doing in both cases is conjugating visual variables and do
what in cartography they refer to as redundant symbolization. In all
cases, mutli-scale styling is important.
Here are the two workflows:
Large number of points

Autostyling for histogram widget is activated
Autostyling would color each point depending on its bin value using
the ramp that we've defined for its distribution
As we zoom in (zooming out would trigger the opposite behavior) the
point symbols would keep their color through all zooms but at a certain
zoom (TBD) the symbol would also get sized according to our classed
proportional symbol specs

Small number of points

Autostyling for histogram widget is activated
Each point would get sized based on our classed proportional symbol
specs and also get colored based on our defined ramp for its distribution

The reason I think we should do the redundant symbology is because if I
remember correctly in Fran's demo during the last product meeting, the
histogram bars on the widget get colored and function as a legend for the
autostyled features on the map. So if we keep consistent with coloring and
also use size through zoom level, it will be good. If for example we only
used size, we wouldn't be able to associate the autostyled points with
their associated values on the histogram bars.
What do you guys think?
—
You are receiving this because you were mentioned.
Reply to this email directly or view it on GitHub
https://github.com/CartoDB/deep-insights.js/issues/340

@saleiva ok! @fdansv or anyone else, if you need my help or any other information, please don't hesitate!

@javisantana and I discussed maybe doing this based on the number of records since as he said, figuring out density is more complicated. I'm open to test it out whenever.

@saleiva @javisantana
Here are some examples of styling for a different amount of points with zoom dependent styling. When appropriate, the map changes to proportional symbols but also keeps the color from smaller zooms.
Wanted to try this out based on a couple conversations about using size... I still think we should do both!
The styling isn't perfect, but just to get the idea.
These examples are all on dark matter... be sure to zoom in!!
7K Points
https://team.cartodb.com/u/mamataakella/viz/72108174-198b-11e6-85c7-0ea31932ec1d/embed_map
27K Points
https://team.cartodb.com/u/mamataakella/viz/c7fa0150-1995-11e6-baa7-0ecd1babdde5/embed_map
83K Points
https://team.cartodb.com/u/mamataakella/viz/378193ce-197f-11e6-8c27-0ecfd53eb7d3/embed_map


failed to open window

When I try to execute the compiled examples (e.g. 01shader_vbo1) I only get
failed to open window

Do you have any idea what the problem might be?

Insufficient OpenGL versions are the most likely cause. That specific
example should require 3.3. What gl version (try "glxinfo | grep
version" on linux), gpu or driver are you using?
Am 25.02.2016 12:13, schrieb Martin Thoma:

When I try to execute the compiled examples (e.g. 01shader_vbo1) I
only get
failed to open window

Do you have any idea what the problem might be?

Reply to this email directly or view it on GitHub:
https://github.com/progschj/OpenGL-Examples/issues/7

Ok, that was the problem.
glxinfo | grep version
server glx version string: 1.4
client glx version string: 1.4
GLX version: 1.4
    Max core profile version: 0.0
    Max compat profile version: 2.1
    Max GLES1 profile version: 1.1
    Max GLES[23] profile version: 2.0
OpenGL version string: 2.1 Mesa 11.3.0-devel (git-9d9aeb9 2016-02-25 wily-oibaf-ppa)
OpenGL shading language version string: 1.20
OpenGL ES profile version string: OpenGL ES 2.0 Mesa 11.3.0-devel (git-9d9aeb9 2016-02-25 wily-oibaf-ppa)
OpenGL ES profile shading language version string: OpenGL ES GLSL ES 1.0.16

This laptop does not have a GPU (Intel HD Graphics). When I used it on my tower, it worked :-)
You could add a requirements section to the README.md.


Add FixedWidthRows to the arrow-row

Is your feature request related to a problem or challenge? Please describe what you are trying to do.

Describe the solution you'd like

Describe alternatives you've considered

Additional context

Closing this as I believe the consensus reached was not to proceed with this, feel free to reopen if I am mistaken


Add keyboard shortcut to open variable inspector

I imagine one could set a shortcut for this with user overrides to the settings, but it's unclear what the name of the command would be. Do you have a way to set up a shortcut for this already?

@stefanuddenberg when looking around at a number of other jupyterlab extensions (e.g. code formatter) they typically recommend setting shortcuts in the user keybindings file. so something like:
{"variableinspector:open":{
    "command": "variableinspector:open",
    "keys": ["Ctrl K"],
    "selector": ".jp-Notebook"
}}

I'm only guessing at the command here, but looks about right from the source: index.ts
personally, I'd be more interested in seeing this set at the extension level (rather than user keybinds), and involving the settings registry to edit the keybind. however, I havent seen any examples of it implemented this way, and the developer documentation for jupyterlab right now is quite lacking...


Start markdown

I'm learning github at all in africa, so i'm following this basic steps that shows that i've created a markdown

[ ] Turn on git hub pages
[ ] Add a read me file
[ ] Introduce yourself to the world


Update stable version in repo from 0.6.4 to 0.6.6

Think about update stable version to 0.6.6
Version: stable=0.6.4 (104 days old) => latest=0.6.6 (20 days old)
Installs: stable=1160 (62.27%), latest=96 (5.15%), total=1863
Click to use developer portal
Click to edit
Do not close this issue manually as a new issue will be created if condition for update still exists.
Please drop a comment if any reason exists which blocks updating to version 0.6.6 at this time.
Note: This is an automatically generated message and not personally authored by bluefox!
@mcm1957 for evidence

0.6.6 has too many bugs. Maybe next release :)

Thanks for confirmation.
If you need any help, please let us know.
And THANKS A LOT for spending your time to support ioBroker.


pom.xml:398: currently, atomizer is broken:...

The puzzle 178-c020c175 from #178 has to be resolved:
https://github.com/pragmatic-objects/oo-atom/blob/a7afe924ca017c9fcec5e88923819ed144ade50d/pom.xml#L398-L398
The puzzle was created by Kapralov Sergey on 04-Jun-18.
Estimate: 0 minutes,
If you have any technical questions, don't ask me, submit new tickets instead. The task will be "done" when the problem is fixed and the text of the puzzle is removed from the source code. Here is more about PDD and about me.

@skapral please pay attention to this new issue.


Use address and port options

The address and port command line arguments weren't getting passed through to the web server.

Ah my bad. This is fix in #11
Thanks!


completing Flovatar transactions and adding mainnet address

Hello,
Since my smart contract has been deployed to mainnet a couple days ago, I thought it would be a good idea to add all the transactions I use on the site with FCL and include the mainnet address as well.
Please let me know if you have any questions!
Thanks a lot,
Luca

LGTM

Thanks so much for the super quick turnaround! Really appreciate it.


Tests: lowerbound on errors?

When building for x86_64-darwin, this line fails because (?) the error's too small:
https://github.com/mapillary/OpenSfM/blob/9766a11e11544fc71fe689f33b34d0610cca2944/opensfm/test/test_reconstruction_incremental.py#L42
From the logs:
python3.9-OpenSfM>         # Sanity check that GCP error is similar to the generated gcp_noise
python3.9-OpenSfM> >       assert 0.01 < errors["absolute_gcp_rmse_horizontal"] < 0.03
python3.9-OpenSfM> E       assert 0.01 < 0.0099943180974112547

Hi @SomeoneSerge,
Thanks for the report, feel free to make a PR to modify this lower bound, this change is under acceptable tolerance.
Yann


Update OWNERS

/verify-owners
/lgtm
/approve

/ok-to-test

/verify-owners

/verify-owners

/verify-owners


cmd/test: tests that take less than 10ms don't have accurate timing

Times for go test are only displayed for every test to two decimal places, so many tests are reported as 0.00s. It would be nice to have a way to increase precision on the time to millisecond precision.

@ianlancetaylor could you please tag this as a proposal? I'd be happy to own this change.
I would like to expose a flag on `go test

I'm not sure it needs to be a full-blown proposal, but, sure.
That said, I don't know that adding a new flag is really what we want.  That just turns into something else we need to maintain but that approximately nobody will use.  It would be better to do something automatic if possible.

Is this necessary? When is this information useful? When testing performance, one usually writes benchmarks, not tests. And the test's duration is primarily of interest when it is large.

This is not necessary, but would be very useful because at the moment the times reported for each test can not add up to the times reported per package. I am OK with reducing package time output to two digits of precision as well, or just changing this to output three digits. It seems from this Godoc that this behavior may even be a bug.
It is nice to be able to parse go test output to jUnit XML or the like and keep timeline data of test runs in Jenkins, for instance. When most tests fall under the 10ms time, they all appear as 0s. This is not useful. Given that the only reason the format is what it is at the moment is that the formatting directive on a Printf is chosen to have two significant digits, and the more precise data is already present, I can't see a good argument for not allowing it to be expressed.

Alternatively to my original idea, instead of being able to specify precision digits it would be nicer, I think, just to leverage time.Duration.String() directly, with a --duration-precise flag or something to keep default behavior from changing.

not lgtm for adding another flag. If there is a change to be made here it would be to extend the precision of the output to 3 decimal places. With that said, I agree with @dominikh that doing accounting on tiny amounts of time just to report them on a graph with a scale in sub human timescales doesn't feel like it pays for the change.

@davecheney if the precision were to be extended to milliseconds, would the package duration then be the sum of the test durations, or does that duration also take into account other overhead?

@stevekuznetsov my suggestion was to change the format here https://github.com/golang/go/blob/master/src/testing/testing.go#L255

@davecheney Yes, sorry. I understood that. I was wondering as a follow-up question, once that precision was increased for tests, would the sum of durations for all tests in a package sum to the duration printed for the package? Package durations already print with three digits of precision.

@stevekuznetsov the precision of the test timing is unchanged, only the string format.

It is impossible to get the times to add up exactly, even ignoring overhead.  Suppose you printed timing rounded to the millisecond.  If you have 2 tests each of which runs in 0.4 milliseconds, you need to print 0 milliseconds for the two tests, but 1 millisecond for the total.

Of course, there won't be perfect congruence at any point. It's just annoying to see a vast majority of tests taking 0.00s to run - if the majority of tests don't take long enough to register, why bother printing the time? If the inconvenience is not worth the effort to change %0.2f to %0.3f, at least, then so be it.

if the majority of tests don't take long enough to register, why bother printing the time?

That's why it's not on by default, you asked for it with -v

That's not a particularly convincing argument... I want useful verbosity when I ask for -v.

We're trying to understand the problem you're having.
The reason we print the times today is so that you can find long-running tests and fix them.  For that 2 decimal digits is more than enough.
I'm not sure what you're using these timings for.  You mentioned parsing the test output to jUnit.  But then you said the 0 times were annoying, implying a human is reading them, not a program.
If a program is reading them, just ignore the 0 entries.  If a human is reading them, do they really care (or notice) that the times don't add up?
Even with 3 digits of precision, simple tests are probably still going to report 0 time.

I was attempting to get a nice breakdown of "how much time is spent doing what" during a full test run, and tests with zero timing are not useful there. When I first looked I expected the reason for only displaying two digits of precision was a limitation in the timing mechanism, but since time.Since was used I wasn't sure why the output of time.Duration.String() wasn't used for this field and instead the time was formatted.  If the purpose of that time slot is to find long-running tests, then I am misusing the feature. In that case, I'll close this issue.

What you want is probably better satisfied by the go test -json proposal.
See #2981.

Yes ultimately if that is being implemented that is better.


Camera option not coming on browse click button html file using Advanced-WebView android version 6

Hi,
I tried to load a URL with the help of Android-AdvancedWebView. Works fine but when I click on browse button from the HTML Page there is no option coming to capture photo from camera and upload the same to page.

Thanks for your question!
Can you please check if https://github.com/delight-im/Android-AdvancedWebView/issues/10 or https://github.com/delight-im/Android-AdvancedWebView/issues/16 or https://github.com/delight-im/Android-AdvancedWebView/issues/20 is helpful to you?

how to solution ? the same issue, i already check #10 #16 #20 but not found solution


Box Elder County, Utah

Currently at library in Brigham City, UT... Middle of nowhere. Found their service!
http://gis.boxeldercounty.org/arcgis/rest/services/Webmap/Cadastral_Layers/MapServer/0

❤

Curious about that Tetris piece in the west.


feat: allowing additional lines to be added to pg_ident file

As described in the issue, we would like a way to add lines to the pg_ident.conf file.
I followed the same approach as pg_hba, it's basically a 1 on 1 mapping.
The pull request contains unit test and e2e test. Documentation needs to be added still.
Closes #3362

Hello @nilsbrenkman We will look into this ASAP

/test limit=local

Hello @nilsbrenkman , can you add the documentation?

/ok-to-merge E2E tests passed

Hello @nilsbrenkman , can you add the documentation?

Will do!


Colour the license lozenges differen colours for Unknown License and licenses that are incompatible with the App Store.

Also, remove the OSI logo for "Unknown License" (but not incompatible licenses).

Glad to see this change. Thanks for responding to my feedback, @daveverwer.
I think that red may not be the best treatment for "unknown", as it indicates an error. Most design systems treat unknown would associate gray or yellow for this state.
Also, I didn't realize that the color corresponded to App Store compatibility. If you aren't doing this already, you might consider calling this out in a "title" attribute or some other kind of onhover disclosure.

👍
I was planning to use red even for unknown licenses as I think it's as bad as an incompatible license. Unlicensed/unknown code is more urgent and important than the absence of something generally is and shouldn't be ignored. I think red is warranted in that situation.
Also, clicking a "red" license will take the viewer to the FAQ too (#203).

Based on that description, I'd say yellow would be more appropriate. For me, it's:

Green: OK, good to go
Yellow: Warning, proceed with caution
Red: Error, this is a problem
Gray: Not sure, invalid, N/A, or to be determined

I suspect that we'll see more variation in open source licenses in the coming years, as folks experiment with new commercial and ethical standards. I worry that red unnecessarily conflates "different" with "harmful".


[Question/Feedback]: PE schema adjustments

Check for previous/existing GitHub issues

[X] I have checked for previous/existing GitHub issues

Description
Opening this issue in correspondence with https://github.com/Azure/bicep-registry-modules/issues/946 to track PE schema adjustments.

https://github.com/Azure/bicep-registry-modules/issues/946


How to do negative sampling

From Models.py Lines 267, 292 and main.py Line 168, I see the "labels" argument for the negative sampling is set to be a placeholder and needed to be specified by the user? If so, what is that used in the paper "Spine: structural identity preserved inductive network embedding"? Thank you.

You can find corresponding codes in minibatch.next_minibatch_feed_dict(), which describes the rpr sampling method for training pairs.


Fix preview crash on local files during upload

Title (required)
Fixes App crashes when tapping on an image during multiple share #1653
Description (required)
Fixes App crashes when tapping on an image during multiple share #1653

Add string length check in Utils.
If file is local, set the URL to local URI.
If there is no filename (i.e. local), do not try to fetch.

Tests performed (required)
Tested on Samsung Galaxy S6 Android 7.0 API 24, with Debug
Gradle build via AndroidStudio
Request from reviewer: Which build tasks do I run to do verification or is the default build from Android Studio sufficient?

Thanks @albendz this works as intended :) Are you willing to also work on #1734 ? Since you get familiar with related codes.

And, I didn't experienced the difficulty about " building with gradle due to dexcount plugin: https://github.com/KeepSafe/dexcount-gradle-plugin/issues/234. In testing, disabled the plugin." you mentioned. Did you solve that problem?

I can take a look at #1734
I fixed the dexcount by not upgrading the gradle version when prompted by android studio. I hadn't realized this is what was causing my issues.


Change coursera broken link to cloudskillsboost

I tried to access the first link that refers to the GCP fundamentals course and could not access it, I believe it no longer exists, so I replaced it with the course link from Google's internal training platform, cloudskillsboost

@Lsubatin , can you please review this issue?

Thanks @italovinicius18 ! 🦄


Issue 12961 grafana

https://github.com/zulip/zulip/issues/12951
Testing Plan:
Test included per webhooks standard in zerver/webhooks/grafana/tests.py.

Closing in favor of #13627.


Option to download videos with list= as a playlist and retain video order

Make sure you are using the latest version: run youtube-dl --version and ensure your version is 2018.11.07. If it's not, read this FAQ entry and update. Issues with outdated version will be rejected.

[x] I've verified and I assure that I'm running youtube-dl 2018.11.07

Before submitting an issue make sure you have:

[x] At least skimmed through the README, most notably the FAQ and BUGS sections
[x] Searched the bugtracker for similar issues including closed ones
[x] Checked that provided video/audio/playlist URLs (if any) are alive and playable in a browser

What is the purpose of your issue?

[ ] Bug report (encountered problems with youtube-dl)
[ ] Site support request (request for adding support for a new site)
[x] Feature request (request for a new functionality)
[ ] Question
[ ] Other

Description of your issue, suggested solution and other information
From what I've seen if a URL like https://www.youtube.com/watch?v=_fAOe8oz8qM&list=PLyqf6gJt7KuHBmeVzZteZUlNUQAVLwrZS is fed to youtube-dl it will only download it as a single video. Is it possible to have an option for youtube-dl to download the video according to the playlist given in the URL?
For example if the above URL is the 3rd video in the PLyqf6gJt7KuHBmeVzZteZUlNUQAVLwrZS playlist and the playlist has 10 videos, youtube-dl will download the playlist video starting from the 3rd video through to the 10th (end) of the playlist.

It will download the whole playlist by default for this URL.

https://github.com/rg3/youtube-dl#video-selection


cannot start a project / amplify pull

Note: If your issue/bug is regarding the AWS Amplify Console service, please log it in the
Amplify Console GitHub Issue Tracker

Describe the bug
cannot pull any env made by cli or console
Amplify CLI Version
4.38 - 4.38.2
To Reproduce
Steps to reproduce the behavior or terminal output if applicable
create backend in console
run env's amplify pull command
2020-12-09T20:33:53.658Z - error: uncaughtException: ENOENT: no such file or directory, open '/Users/amlcodes/Developer/projects/dapperduck/mosey/mosey/amplify/logs/amplify-cli-2020-12-09.log' date=Wed Dec 09 2020 15:33:53 GMT-0500 (Eastern Standard Time), pid=2474, uid=501, gid=20, cwd=/Users/amlcodes/Developer/projects/dapperduck/mosey/mosey, execPath=/Users/amlcodes/.nvm/versions/node/v15.3.0/bin/node, version=v15.3.0, argv=[/Users/amlcodes/.nvm/versions/node/v15.3.0/bin/node, /Users/amlcodes/.nvm/versions/node/v15.3.0/bin/amplify, pull, --appId, d1e01uyof7nx9n, --envName, staging], rss=361578496, heapTotal=310370304, heapUsed=260802448, external=10905134, arrayBuffers=9347476, loadavg=[11.96923828125, 6.8623046875, 4.888671875], uptime=494190, trace=[], stack=[Error: ENOENT: no such file or directory, open '/Users/amlcodes/Developer/projects/dapperduck/mosey/mosey/amplify/logs/amplify-cli-2020-12-09.log']

Expected behavior
A clear and concise description of what you expected to happen.
pulls the env
Screenshots
If applicable, add screenshots to help explain your problem.

@ammarkarachi you're a madman, thanks so much for bug squashing. You're really making this usable for us.


Add configuration step to link a git repo for dags, plugins etc.

[x]  In get_me_ready.sh: Add a step to link repos where dags, plugins etc. are located (or create those as optional environment variables?!)

[x] Add the possibility to create a cron job OR write a script to explicitly pull/update the files from the linked git repo

[x] Remove the /dags folder and the push_dags.sh script

Switched to docker-compose only setup


⚠ ClamAV has degraded performance

In 44f1a68, ClamAV (https://spamassassin.apache.org/) experienced degraded performance:

HTTP code: 200
Response time: 223 ms

Resolved: ClamAV performance has improved in 935f39c.


System.Reflection.Emit support

Does it support System.Reflection.Emit?

HybridCLR doesn't support System.Reflection.Emit because il2cpp doesn't implement this library.


Running TFX tests failed with error

I am executing TFX code on top of beam on ray. I saw the following error. Need further investigation.
2023-01-11 22:06:21,746 INFO worker.py:1538 -- Started a local Ray instance.
(ray_execute_bundle pid=932030) 2023-01-11 22:06:26.138460: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
(ray_execute_bundle pid=932030) To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(ray_execute_bundle pid=932030) 2023-01-11 22:06:26.273821: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
(ray_execute_bundle pid=932030) 2023-01-11 22:06:26.273868: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
(ray_execute_bundle pid=932030) 2023-01-11 22:06:27.034191: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
(ray_execute_bundle pid=932030) 2023-01-11 22:06:27.034290: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
(ray_execute_bundle pid=932030) 2023-01-11 22:06:27.034306: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
INFO:absl:MetadataStore with DB connection initialized
ERROR:absl:Execution 6 failed.
INFO:absl:Cleaning up stateless execution info.
Traceback (most recent call last):
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 624, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/beam/beam_dag_runner.py", line 90, in process
    self._run_node()
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/beam/beam_dag_runner.py", line 99, in _run_node
    launcher.Launcher(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/launcher.py", line 573, in launch
    executor_output = self._run_executor(execution_info)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/launcher.py", line 448, in _run_executor
    executor_output = self._executor_operator.run_executor(execution_info)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/beam_executor_operator.py", line 112, in run_executor
    return python_executor_operator.run_with_executor(execution_info, executor)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/python_executor_operator.py", line 58, in run_with_executor
    result = executor.Do(execution_info.input_dict, output_dict,
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/components/example_gen/base_example_gen_executor.py", line 283, in Do
    (example_split
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 597, in __exit__
    self.result = self.run()
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 574, in run
    return self.runner.run_pipeline(self, self._options)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 198, in run_pipeline
    return self.execute_pipeline(stage_context, stages)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 227, in execute_pipeline
    result = self._run_stage(runner_execution_context, bundle_ctx, queue)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 274, in _run_stage
    ) = self._run_bundle(
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 348, in _run_bundle
    result = ray.get(next(result_generator))
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
    return func(*args, **kwargs)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/ray/_private/worker.py", line 2309, in get
    raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(ValueError): ray::ray_execute_bundle() (pid=932030, ip=<IP_ADDRESS>)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/execution.py", line 113, in ray_execute_bundle
    result_future = worker_handler.control_conn.push(instruction_request)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py", line 380, in push
    response = self.worker.do_instruction(request)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 597, in do_instruction
    return getattr(self, request_type)(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 635, in process_bundle
    bundle_processor.process_bundle(instruction_id))
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 1003, in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 227, in process_encoded
    self.output(decoded_value)
  File "apache_beam/runners/worker/operations.py", line 526, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 528, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 237, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 1021, in apache_beam.runners.worker.operations.SdfProcessSizedElements.process
  File "apache_beam/runners/worker/operations.py", line 1030, in apache_beam.runners.worker.operations.SdfProcessSizedElements.process
  File "apache_beam/runners/common.py", line 1432, in apache_beam.runners.common.DoFnRunner.process_with_sized_restriction
  File "apache_beam/runners/common.py", line 815, in apache_beam.runners.common.PerWindowInvoker.invoke_process
  File "apache_beam/runners/common.py", line 877, in apache_beam.runners.common.PerWindowInvoker._should_process_window_for_sdf
  File "apache_beam/runners/common.py", line 884, in apache_beam.runners.common.PerWindowInvoker._should_process_window_for_sdf
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/sdf_utils.py", line 62, in __init__
    raise ValueError(
ValueError: Initialize ThreadsafeRestrictionTracker requiresRestrictionTracker.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "./feature_skewness.py", line 75, in <module>
    BeamDagRunner().run(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/tfx_runner.py", line 124, in run
    return self.run_with_ir(pipeline_pb, run_options=run_options_pb, **kwargs)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/beam/beam_dag_runner.py", line 297, in run_with_ir
    logging.info('Node %s is scheduled.', node_id)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 597, in __exit__
    self.result = self.run()
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 574, in run
    return self.runner.run_pipeline(self, self._options)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/direct/direct_runner.py", line 131, in run_pipeline
    return runner.run_pipeline(pipeline, options)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 199, in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 212, in run_via_runner_api
    return self.run_stages(stage_context, stages)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 442, in run_stages
    bundle_results = self._execute_bundle(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 770, in _execute_bundle
    self._run_bundle(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 999, in _run_bundle
    result, splits = bundle_manager.process_bundle(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 1309, in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py", line 380, in push
    response = self.worker.do_instruction(request)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 597, in do_instruction
    return getattr(self, request_type)(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 635, in process_bundle
    bundle_processor.process_bundle(instruction_id))
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 1003, in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 227, in process_encoded
    self.output(decoded_value)
  File "apache_beam/runners/worker/operations.py", line 526, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 528, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 237, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 623, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "apache_beam/runners/common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
  File "apache_beam/runners/common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 623, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "apache_beam/runners/common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
  File "apache_beam/runners/common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
  File "apache_beam/runners/worker/operations.py", line 324, in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 905, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 1507, in apache_beam.runners.common.DoFnRunner._reraise_augmented
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 624, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/beam/beam_dag_runner.py", line 90, in process
    self._run_node()
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/beam/beam_dag_runner.py", line 99, in _run_node
    launcher.Launcher(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/launcher.py", line 573, in launch
    executor_output = self._run_executor(execution_info)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/launcher.py", line 448, in _run_executor
    executor_output = self._executor_operator.run_executor(execution_info)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/beam_executor_operator.py", line 112, in run_executor
    return python_executor_operator.run_with_executor(execution_info, executor)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/python_executor_operator.py", line 58, in run_with_executor
    result = executor.Do(execution_info.input_dict, output_dict,
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/components/example_gen/base_example_gen_executor.py", line 283, in Do
    (example_split
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 597, in __exit__
    self.result = self.run()
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 574, in run
    return self.runner.run_pipeline(self, self._options)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 198, in run_pipeline
    return self.execute_pipeline(stage_context, stages)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 227, in execute_pipeline
    result = self._run_stage(runner_execution_context, bundle_ctx, queue)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 274, in _run_stage
    ) = self._run_bundle(
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 348, in _run_bundle
    result = ray.get(next(result_generator))
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
    return func(*args, **kwargs)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/ray/_private/worker.py", line 2309, in get
    raise value.as_instanceof_cause()
RuntimeError: ray.exceptions.RayTaskError(ValueError): ray::ray_execute_bundle() (pid=932030, ip=<IP_ADDRESS>)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/execution.py", line 113, in ray_execute_bundle
    result_future = worker_handler.control_conn.push(instruction_request)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py", line 380, in push
    response = self.worker.do_instruction(request)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 597, in do_instruction
    return getattr(self, request_type)(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 635, in process_bundle
    bundle_processor.process_bundle(instruction_id))
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 1003, in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 227, in process_encoded
    self.output(decoded_value)
  File "apache_beam/runners/worker/operations.py", line 526, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 528, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 237, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 1021, in apache_beam.runners.worker.operations.SdfProcessSizedElements.process
  File "apache_beam/runners/worker/operations.py", line 1030, in apache_beam.runners.worker.operations.SdfProcessSizedElements.process
  File "apache_beam/runners/common.py", line 1432, in apache_beam.runners.common.DoFnRunner.process_with_sized_restriction
  File "apache_beam/runners/common.py", line 815, in apache_beam.runners.common.PerWindowInvoker.invoke_process
  File "apache_beam/runners/common.py", line 877, in apache_beam.runners.common.PerWindowInvoker._should_process_window_for_sdf
  File "apache_beam/runners/common.py", line 884, in apache_beam.runners.common.PerWindowInvoker._should_process_window_for_sdf
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/sdf_utils.py", line 62, in __init__
    raise ValueError(
ValueError: Initialize ThreadsafeRestrictionTracker requiresRestrictionTracker. [while running 'Run[FileBasedExampleGen]']

@pabloem can you shed some light on this?

This must have something to do with our internal beam class that reads parquet file. After using apache_beam.io.ReadFromParquet instead of  bytebeam.io.ReadFromParquet now it is a different error now:
(ray_execute_bundle pid=1067832) 2023-01-12 01:33:00.663969: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
(ray_execute_bundle pid=1067832) To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
(ray_execute_bundle pid=1067832) 2023-01-12 01:33:00.800820: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
(ray_execute_bundle pid=1067832) 2023-01-12 01:33:00.800869: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
(ray_execute_bundle pid=1067832) 2023-01-12 01:33:01.542184: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
(ray_execute_bundle pid=1067832) 2023-01-12 01:33:01.542287: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
(ray_execute_bundle pid=1067832) 2023-01-12 01:33:01.542303: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
INFO:absl:MetadataStore with DB connection initialized
ERROR:absl:Execution 11 failed.
INFO:absl:Cleaning up stateless execution info.
Traceback (most recent call last):
  File "./feature_skewness.py", line 75, in <module>
    BeamDagRunner().run(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/tfx_runner.py", line 124, in run
    return self.run_with_ir(pipeline_pb, run_options=run_options_pb, **kwargs)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/beam/beam_dag_runner.py", line 297, in run_with_ir
    logging.info('Node %s is scheduled.', node_id)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 597, in __exit__
    self.result = self.run()
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 574, in run
    return self.runner.run_pipeline(self, self._options)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/direct/direct_runner.py", line 131, in run_pipeline
    return runner.run_pipeline(pipeline, options)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 199, in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 212, in run_via_runner_api
    return self.run_stages(stage_context, stages)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 442, in run_stages
    bundle_results = self._execute_bundle(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 770, in _execute_bundle
    self._run_bundle(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 999, in _run_bundle
    result, splits = bundle_manager.process_bundle(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py", line 1309, in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py", line 379, in push
    response = self.worker.do_instruction(request)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 596, in do_instruction
    return getattr(self, request_type)(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 634, in process_bundle
    bundle_processor.process_bundle(instruction_id))
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 1003, in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 227, in process_encoded
    self.output(decoded_value)
  File "apache_beam/runners/worker/operations.py", line 526, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 528, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 237, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 623, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "apache_beam/runners/common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
  File "apache_beam/runners/common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 623, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "apache_beam/runners/common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
  File "apache_beam/runners/common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
  File "apache_beam/runners/worker/operations.py", line 324, in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 905, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 624, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/beam/beam_dag_runner.py", line 90, in process
    self._run_node()
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/beam/beam_dag_runner.py", line 99, in _run_node
    launcher.Launcher(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/launcher.py", line 573, in launch
    executor_output = self._run_executor(execution_info)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/launcher.py", line 448, in _run_executor
    executor_output = self._executor_operator.run_executor(execution_info)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/beam_executor_operator.py", line 112, in run_executor
    return python_executor_operator.run_with_executor(execution_info, executor)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/orchestration/portable/python_executor_operator.py", line 58, in run_with_executor
    result = executor.Do(execution_info.input_dict, output_dict,
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/components/example_gen/base_example_gen_executor.py", line 283, in Do
    (example_split
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 597, in __exit__
    self.result = self.run()
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/pipeline.py", line 574, in run
    return self.runner.run_pipeline(self, self._options)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 198, in run_pipeline
    return self.execute_pipeline(stage_context, stages)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 227, in execute_pipeline
    result = self._run_stage(runner_execution_context, bundle_ctx, queue)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 274, in _run_stage
    ) = self._run_bundle(
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/ray_fn_runner.py", line 348, in _run_bundle
    result = ray.get(next(result_generator))
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/ray/_private/client_mode_hook.py", line 105, in wrapper
    return func(*args, **kwargs)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/ray/_private/worker.py", line 2309, in get
    raise value.as_instanceof_cause()
ray.exceptions.RayTaskError(UnicodeDecodeError): ray::ray_execute_bundle() (pid=1067832, ip=<IP_ADDRESS>)
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 624, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/transforms/core.py", line 1879, in <lambda>
    wrapper = lambda x: [fn(x)]
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/components/example_gen/utils.py", line 102, in dict_to_example
    pyval = pyval.decode(_DEFAULT_ENCODING)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x8d in position 6: invalid start byte

During handling of the above exception, another exception occurred:

ray::ray_execute_bundle() (pid=1067832, ip=<IP_ADDRESS>)
  File "/home/wilson.wang/ads_infra/ray_beam_runner/ray_beam_runner/portability/execution.py", line 113, in ray_execute_bundle
    result_future = worker_handler.control_conn.push(instruction_request)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py", line 379, in push
    response = self.worker.do_instruction(request)
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 596, in do_instruction
    return getattr(self, request_type)(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/sdk_worker.py", line 634, in process_bundle
    bundle_processor.process_bundle(instruction_id))
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 1003, in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/runners/worker/bundle_processor.py", line 227, in process_encoded
    self.output(decoded_value)
  File "apache_beam/runners/worker/operations.py", line 526, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 528, in apache_beam.runners.worker.operations.Operation.output
  File "apache_beam/runners/worker/operations.py", line 237, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 1021, in apache_beam.runners.worker.operations.SdfProcessSizedElements.process
  File "apache_beam/runners/worker/operations.py", line 1030, in apache_beam.runners.worker.operations.SdfProcessSizedElements.process
  File "apache_beam/runners/common.py", line 1432, in apache_beam.runners.common.DoFnRunner.process_with_sized_restriction
  File "apache_beam/runners/common.py", line 817, in apache_beam.runners.common.PerWindowInvoker.invoke_process
  File "apache_beam/runners/common.py", line 981, in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
  File "apache_beam/runners/common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
  File "apache_beam/runners/common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 1491, in apache_beam.runners.common.DoFnRunner._reraise_augmented
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 837, in apache_beam.runners.common.PerWindowInvoker.invoke_process
  File "apache_beam/runners/common.py", line 981, in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
  File "apache_beam/runners/common.py", line 1581, in apache_beam.runners.common._OutputHandler.handle_process_outputs
  File "apache_beam/runners/common.py", line 1694, in apache_beam.runners.common._OutputHandler._write_value_to_tag
  File "apache_beam/runners/worker/operations.py", line 240, in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
  File "apache_beam/runners/worker/operations.py", line 907, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/worker/operations.py", line 908, in apache_beam.runners.worker.operations.DoOperation.process
  File "apache_beam/runners/common.py", line 1419, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 1507, in apache_beam.runners.common.DoFnRunner._reraise_augmented
  File "apache_beam/runners/common.py", line 1417, in apache_beam.runners.common.DoFnRunner.process
  File "apache_beam/runners/common.py", line 624, in apache_beam.runners.common.SimpleInvoker.invoke_process
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/apache_beam/transforms/core.py", line 1879, in <lambda>
    wrapper = lambda x: [fn(x)]
  File "/home/wilson.wang/miniconda3/lib/python3.8/site-packages/tfx/components/example_gen/utils.py", line 102, in dict_to_example
    pyval = pyval.decode(_DEFAULT_ENCODING)
UnicodeDecodeError: 'utf-8 [while running 'InputToRecord/ToTFExample']' codec can't decode byte 0x8d in position 6: invalid start byte

I fixed this issue, this is related to tfx protobuf deserialization.


feat: built ui runs on gotham

When running cargo run, we're supposed to get all static deps from /dist/, right? In the browser I'm getting:
404 GET | http://localhost:3000/web_modules/react.js
404 GET | http://localhost:3000/web_modules/react-dom.js

We should provide those libs statically I guess?

When running cargo run, we're supposed to get all static deps from /dist/, right? In the browser I'm getting:
404 GET | http://localhost:3000/web_modules/react.js
404 GET | http://localhost:3000/web_modules/react-dom.js

We should provide those libs statically I guess?
Edit: alternatively some README description how to run this would be helpful.

Found the problem! let me fix it on this PR

When running cargo run, we're supposed to get all static deps from /dist/, right? In the browser I'm getting:
404 GET | http://localhost:3000/web_modules/react.js
404 GET | http://localhost:3000/web_modules/react-dom.js

We should provide those libs statically I guess?
Edit: alternatively some README description how to run this would be helpful.

Fixed and added some more info the root README