the blocked_expressions list somehow gets erased again and again

Trying to reproduce it, it seems like saving anything in the general tab resets the readability tab (but not the other way around).
Another issue is that you can make a change in one tab, switch to another and then save - only the changes in the current tab will be saved, even though there was no warning. I think your code should probably consider all the tabs as one form .

Actually, saving any tab will cause the settings of other tabs to be erased (except for the general tab, which retains its settings).

Fixed in https://github.com/nischayn22/PageQuality/commit/301c28c76fb1726d6abfd8545bba33507eea8057

Great


Add default usage of custom commands again, fixes #2633

The Problem/Issue/Bug:
In case of missing usage annotation no command name is shown anymore. This was accidentally removed with https://github.com/drud/ddev/commit/c34907d7d6cd836e0571ad0b0effcaa1d48a7b83.
How this PR Solves The Problem:
This patch reintroduces the default value again.
Manual Testing Instructions:
Create a custom command without the usage annotation and check the command name is shown properly on the help screen.
Automated Testing Overview:

Related Issue Link(s):
#2633
#2452
Release/Deployment notes:

Rebased again. Hope to review and get these in this week.


[BUG] 2.10 - Cannot drain a node from the UI

Rancher Server Setup

Rancher version: 2.10.0
Installation option (Docker install/Helm Chart): Helm

If Helm Chart, Kubernetes Cluster and version (RKE1, RKE2, k3s, EKS, etc): microk8s 1.30.7

Proxy/Cert Details: cert-manager, internal PKI

Information about the Cluster

Kubernetes version: 1.30.7
Cluster Type (Local/Downstream): Both

User Information

What is the role of the user logged in? Admin

Describe the bug
When on the Nodes page, select a node, then click Drain. None of the buttons or selections in this pop up work any more, they were working in the previous version. We can no longer drain/cordon nodes from the UI. This happens for local and downstream clusters.
To Reproduce

Navigate to nodes page
Select a node's checkbox
Click on Drain at the top
try to use any of the options to drain the node

Result
Options are not working
Expected Result

Should be able to drain/cordon a node from the UI.
Screenshots

Thank you, I had not seen that other issue.


Documentation

After PR: #58

Codecov Report
Base: 55.59% // Head: 54.49% // Decreases project coverage by -1.10% :warning:

Coverage data is based on head (3bb58a4) compared to base (4736730).
Patch coverage: 43.55% of modified lines in pull request are covered.

Additional details and impacted files
@@            Coverage Diff             @@
##             main      #64      +/-   ##
==========================================
- Coverage   55.59%   54.49%   -1.11%
==========================================
  Files          31       37       +6
  Lines        1126     1246     +120
  Branches      332      356      +24
==========================================
+ Hits          626      679      +53
- Misses        253      303      +50
- Partials      247      264      +17

Impacted Files
Coverage Δ

...ip_cpp/include/amlip_cpp/types/status/NodeKind.hpp
0.00% <0.00%> (ø)

...p_cpp/include/amlip_cpp/types/status/StateKind.hpp
0.00% <0.00%> (ø)

amlip_cpp/src/cpp/dds/Participant.cpp
58.62% <ø> (ø)

...src/cpp/types/multiservice/MsReferenceDataType.cpp
48.68% <ø> (ø)

...p/src/cpp/types/multiservice/MsRequestDataType.cpp
42.85% <ø> (ø)

amlip_cpp/src/cpp/node/StatusNode.cpp
36.53% <7.14%> (-12.18%)
:arrow_down:

amlip_cpp/src/cpp/dds/impl/Reader.ipp
46.77% <13.33%> (-0.40%)
:arrow_down:

amlip_cpp/src/cpp/types/GenericDataType.cpp
58.92% <32.50%> (-18.71%)
:arrow_down:

...c/cpp/dds/multiservice/impl/MultiServiceClient.ipp
36.84% <33.33%> (+0.30%)
:arrow_up:

amlip_cpp/src/cpp/node/ComputingNode.cpp
48.38% <45.00%> (-4.95%)
:arrow_down:

... and 16 more

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

:umbrella: View full report at Codecov.
:loudspeaker: Do you have feedback about the report comment? Let us know in this issue.


feat: Gamify apps api endpoint with mockdata

I've also added Cas as an optional reviewer. (You don't have to await his feedback, know he is busy on another project 😅 )


The Fail SSL is appear and make my App is hangs

When I use Firebase Analytics, I saw in my log this line
2017-10-19 12:27:03.812035+0800 waave[17437:136184] [Firebase/Analytics][I-ACS900000] Uploading data. Host: https://app-measurement.com/a
2017-10-19 12:27:03.812 waave[17437]  [Firebase/Analytics][I-ACS900000] Uploading data. Host: https://app-measurement.com/a
And then it fail
2017-10-19 12:27:13.902154+0800 waave[17437:136236] TIC TCP Conn Failed [13:0x604000176080]: 3:-9802 Err(-9802)
2017-10-19 12:27:24.037516+0800 waave[17437:136178] TIC TCP Conn Failed [14:0x604000176080]: 3:-9802 Err(-9802)
2017-10-19 12:27:24.109948+0800 waave[17437:136135] TIC TCP Conn Failed [15:0x600000175540]: 3:-9802 Err(-9802)
2017-10-19 12:27:24.110584+0800 waave[17437:136135] NSURLSession/NSURLConnection HTTP load failed (kCFStreamErrorDomainSSL, -9802)
2017-10-19 12:27:24.110686+0800 waave[17437:136135] Task .<1> HTTP load failed (error code: -1200 [3:-9802])
2017-10-19 12:27:24.111256+0800 waave[17437:136207] Task .<1> finished with error - code: -1200
2017-10-19 12:28:56.884913+0800 waave[17437:137290] TIC Read Status [1:0x0]: 1:57
2017-10-19 12:28:56.885066+0800 waave[17437:137290] TIC Read Status [1:0x0]: 1:57
2017-10-19 12:30:55.047956+0800 waave[17437:138073] TIC Read Status [2:0x0]: 1:57
2017-10-19 12:30:55.048071+0800 waave[17437:138073] TIC Read Status [2:0x0]: 1:57
2017-10-19 12:30:56.888043+0800 waave[17437:136135] TIC Read Status [5:0x0]: 1:57
2017-10-19 12:30:56.888166+0800 waave[17437:136135] TIC Read Status [5:0x0]: 1:57
And it make my App is hangs
I have added "Allow arbitrary Loads" as Yes under NSAppTransportSecurity. And I am getting this error for iOS11
Please help me.

Hey @ttnhathuy1987, sorry for the late response.
There's not quite enough information here to debug your issue. Error -9802 is a generic SSL failure and can be caused by a number of factors outside of Firebase. Are you able to reproduce this in a new project?


Continuous Evaluation in Training mode on even though evaluation stopped

In Training Mode I run the function as per red below. System turned on Continuous Evaluation on and we can see 5 lines evaluated as per green below:

Now, I made a move 17.Qc7 and the coach replied 17...Rc7 (red below). Comment Box is updated with a note The Coach played 17...Rc7 (blue below), however the Continuous Evaluation button is still on. It should be turned off (green below)

Fixed


Ionic 2 Android 4.4

Short description of the problem:
The Tabbar does not correctly work on Android 4.4.4. It apperas under the header bar (the header bar is in top of it).
Steps to reproduce:

Create a tabbed template with ionic

Which Ionic Version? 1.x or 2.x
Newest (2 rc1)

Hello, would you mind posting a screenshot of what you are seeing? Thanks!

@jgw96 there is not really much to show. On a page which has a header navbar and a tab component the header of the tab component will not be shown since it is rendered beneath the header navbar.

Your system information:
Cordova CLI: 6.4.0
Gulp version:  CLI version 3.9.1
Gulp local:
Ionic CLI Version: 2.1.4
Ionic App Lib Version: 2.1.2
OS: Windows 7 SP1
Node Version: v6.7.0

It occurred in UC-Browser

Hello all! Does this still occur in rc3? Also, are you all able to repro this in the Android 4.4.4 simulator? I am not able to unfortunately.

Hello! Because i am not able to reproduce this issue I am going to close this one for now. Thanks and feel free to comment if you are still having this issue!


Feature Request: running query under cursor

It mostly feels convenient to have multiple queries on the same file, but having to visually select a query to run just one is a pain. It would be more convenient to just have to execute the query under cursor with a new command like "SqlsExecuteQueryCursor".

@sigzegv, I use this:
nnoremap <silent> <Leader>qe :<C-U>silent! '{,'}SqlsExecuteQuery<CR>


⚠ Site ANTS has degraded performance

In baa42e1, Site ANTS (https://ants.gouv.fr) experienced degraded performance:

HTTP code: 502
Response time: 26472 ms

Resolved: Site ANTS performance has improved in 2b0fe2d after 1 hour, 55 minutes.


Add support Typescript

It would be great if you could support Typescript like what you did with React.

This is not the place for feature requests. Take it to https://phabricator.babeljs.io


Bump Eirini to 0.0.21

Description
Using latest eirini release.
Test plan
Install kubecf with latest cf-operator. Run cf push afterwards.
Problems
cf push is not working. But this is related to https://github.com/cloudfoundry-incubator/cf-operator/issues/648

@kramerul The bump to 0.0.21 seems good. I tested with cf-operator on commit https://github.com/cloudfoundry-incubator/cf-operator/commit/c193b5b616ef22a3a65489e4ff573109480a5c62, which is part of https://github.com/cloudfoundry-incubator/cf-operator/pull/661, and the failure I get is due to the opi-task-downloader init container not being able to connect to blobstore.service.cf.internal, which makes perfect sense given that it is in a different namespace and it's not using our aliases on the CF namespace. I pushed a commit on the PR while it was on the SCF side that fixed this. I'll accept this PR as is and I'll push a fix for that in a separate PR.


The simulation is running too slowly

Bug description
When I run the OpenFAST using input file 5MW_Land_DLL_WTurb and WP_VSP_WTurb, I got an unbelievable "Total Real Time". The test for 5MW_Land_DLL_WTurb toke total run time about 120 seconds for 60 seconds' simulation, and the WP_VSP_WTurb toke total run time about 59 seconds for 40 seconds' simulation. Is this situation normal? I am new to OpenFAST, but according to my previous experience with FASTv8, this is unbelievable.
To Reproduce
Steps to reproduce the behavior:

Compile with 'gnu'
Run '5MW_Land_DLL_WTurb' case with 'DLL unused' settings, and run 'WP_VSP_WTurb' case with raw settings.
The problem is that I don't know if this is normal?

Expected behavior
I expect that this simulation can take less time, at least lower than the simulation time.
OpenFAST-v2.0.0-dirty
**************************************************************************************************
 OpenFAST

 Copyright (C)  National Renewable Energy Laboratory
 Copyright (C)  Envision Energy USA LTD

 This program is licensed under Apache License Version 2.0 and comes with ABSOLUTELY NO WARRANTY.
 See the "LICENSE" file distributed with this software for details.
 **************************************************************************************************

 OpenFAST-v2.0.0
 Compile Info:
  - Architecture: 64 bit
  - Precision: double
  - Date: Mar  6 2019
  - Time: 17:19:38
 Execution Info:
  - Date: 11/29/2018
  - Time: 09:28:55

System Information (please complete the following information):

OS: Ubuntu 16.04
Compiler:  GFortran 5.4
Compiler settings: Release version and static library and any other things is follow raw setting

@smilke 120 seconds wall time for a 60 second simulation does seem a bit long, but this could depend on multiple factors. OpenFAST has been configured to run nightly tests on one of NREL’s clusters. Last night the test reported a run time of about 72 seconds as can be seen here.
https://my.cdash.org/viewTest.php?buildid=1622580

Also keep in mind that double precision is much slower than single precision. Are you comparing the same numerical precision in fast 8 vs openfast?

In fact, I did compile OpenFAST into double precision, and I don't know if FASTv8 is single-precision or double-precision, because I used to use the archive version under Windows, I will check it out. I currently need to run OpenFAST in real time, so I must ask his actual execution time to be less than the simulation time. Do you have any suggestions?
Also, I need to use a 5MW model or a 1.5MW model. In fact, I can reduce the computational accuracy requirements, as long as it can run fast enough.

I have solved  the problem by changing double precision to single precision. Thanks for your advise. But I am still confused about how to improve the running speed of FAST as much as possible

Dear @smilke,
Yes, I would encourage you to compile in single precision when running many simulations.  Single precision should be sufficiently accurate and much faster than double.
We've also had a discussion on our forum about how to reduce the time necessary to run FAST / OpenFAST simulations--see: https://wind.nrel.gov/forum/wind/viewtopic.php?f=4&t=1416&p=12380.
Best regards,

Dear @jjonkman
Thank you so much, the link you gave is very helpful.

Thanks for the added info, @jjonkman

Dear @Smilke,
Yes, I would encourage you to compile in single precision when running many simulations. Single precision should be sufficiently accurate and much faster than double.
We've also had a discussion on our forum about how to reduce the time necessary to run FAST / OpenFAST simulations--see: https://wind.nrel.gov/forum/wind/viewtopic.php?f=4&t=1416&p=12380.
Best regards,

Dear @jjonkman and @rafmudaf,
When clicking on the link, I cannot find the issue directly. Is it possible to give me this link again ? Maybe due to possible website update, the link is not working well.
Best regards,

Dear @hbasbas,
Unfortunately the deep links changed when switching from the old to new forum, so, while the forum posts/topics still exist, many of these cross-references are broken.  However, here is one forum topic that is relevant and is likely the one I had previously linked to: https://forums.nrel.gov/t/fast-computation-time-and-improvement/1235.
Best regards,

Dear @jjonkman
Thank you for this link. Useful !


TypeError: list indices must be integers or slices, not tuple

I changed the dataset and ran the SSD_training.ipynb.
I keep getting this error.

TypeError                                 Traceback (most recent call last)
 in ()
1 for i, img in enumerate(images):
2     # Parse the outputs.
----> 3     det_label = results[0][:, 0]
4     det_conf = results[0][:, 1]
5     det_xmin = results[0][:, 2]
TypeError: list indices must be integers or slices, not tuple
How can I remove this error?

How did you remove this error?

It was because pkl file wasn't made properly. I re-created the pkl file and teaining worked without problems.

Why is this issue related to any pkl file? This error occurs during prediction.
Additionally, if it is a pkl file issue, what was the issue? As in, how was it made incorrectly?

For me, the problem was the num of classes. It was wrong value.
I followed this instruction:
https://noteoneverything.blogspot.com/2018/03/single-shot-multibox-detector-how-to.html


set all data from the .env file only in memory instead of using os.SetEnv

without CGO SetEnv is noop and doesn't actually see the data from the env file into the os env vars, but if that happens it will expose the private key even for encrypted keys to anyone that has access to the machine. Instead just load the env file and set files in the Config or pass around the map to the components that need it.

done in https://github.com/cryptoriums/telliot/commit/d69e0f7a38a5f9d4aefa91a822aa9dd06368bba8


picher

actually i need help you can help me
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Closed #81 https://github.com/zzzprojects/zzzcode.ai/issues/81 as
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kodak


[Release Radar Request] JSON Visio

Open Source Project name
JSON Visio
What is your project?
JSON Visio is an app to view JSON data into graphs without having to restructure the initial data.
Version
1.0
Date
February 17, 2022
Description of breaking changes
nil
GitHub Repo
https://github.com/AykutSarac/jsonvisio.com
Website
https://jsonvisio.com/
Link to changelog
https://github.com/AykutSarac/jsonvisio.com/releases/tag/v1.0.0
Social media
https://twitter.com/aykutsarach/status/1494329405086187528
Anything else to add?
No response

Congrats on being featured in the February 2022 Release Radar 🥳

Read the blog here
Feel free to retweet Mish's tweet featuring you


Program crashes on attempting to save file that does not exist

Steps to recreate:

Create a new chart.
Delete the chart file.
Attempt to save the file.

This is an incredibly easy fix: create a check to see if the file still exists, and if it doesn't, create one and write to it.

Can't reproduce, must be user error.


Tween.call is called before the previous action really ended, on oChange event will be called after "call"

I have
createjs.Tween.get(myShape,{onChange:update)}).to({x : 100}, 2000, createjs.Ease.quartInOut).call(ended);

one more update will be called after ended :(

A workaround: this is how you identify the last onChange event so that you can use it instead of the call function.
createjs.Tween.get(myShape,{onChange:update)}).to({x : 100}, 2000, createjs.Ease.quartInOut).call(ended);
function update(evt) {
evt.target.duration == evt.target.position
}

This is expected behavior. The change event is triggered after each tick is resolved, which includes both property updates and action execution. If you want to tie some code into the VERY end of the tween, then use the complete event.
I've updated the documentation to make this more clear.

I understand. Once you update the documentation there should be no confusion. Thanks.

The docs for change were updated to:
Dispatched whenever the tween's position changes. It occurs after all tweened properties are updated and actions are executed.


Most of my 3D models does not appear in view

Most of my 3D models does not appear in the view widget
For unknown reasons, only 1 of 10 models appears in the ARView(gltf)
I use type: NodeType.webGLB and type: NodeType.localGLTF2 models (*.glb , *.gltf appropriately)
No errors no warnings
For gltf
[ +142 ms] flutter: iOS platform view created!
[ +174 ms] flutter: [ObjectTEST from iOS]
For glb
[ +153 ms] flutter: iOS platform view created!
[  +49 ms] flutter: [ObjectTEST from iOS]
[ +131 ms] Async Model Downloading Task completed:  finished
client:
IOS 14.7.1 IPHONE SE(old model)
environment:
ar_flutter_plugin: ^0.6.1
Flutter (Channel master, 2.6.0-12.0.pre.675, on Mac OS X 10.15.7 19H524 darwin-x64, locale en-UA)
Xcode - develop for iOS and macOS (Xcode 12.4)
VS Code (version 1.48.2)
Please help to solve the issue, my project strongly relies on the AR objects displayed

that's really strange, especially if there are no errors... can you send me a link to the webGLB model that you use so I can have a look at the problem?

that's really strange, especially if there are no errors... can you send me a link to the webGLB model that you use so I can have a look at the problem?

Yes of course
The models that are not displayed at all neither with type: NodeType.webGLB, nor type: NodeType.localGLTF2
https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fpteranodon.glb?alt=media&token=f34c1730-6f77-4903-94da-f0aeebb66bbf
https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Ft_rex.glb?alt=media&token=168ddba9-5902-47f1-a127-4e0ef803bcea
The model that is displayed succesfully using type: NodeType.webGLB, or type: NodeType.localGLTF2
https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fbrachiosaurus.glb?alt=media&token=f8f9b491-7441-4641-ad7f-d47e15d03180

i have the same issue too, i use a 3d model from blender with glb format, use Node Type.localGLTF2 but it unnable to load the assets, i have check the pubspec.yaml.it appears on 3d model view though

that's really strange, especially if there are no errors... can you send me a link to the webGLB model that you use so I can have a look at the problem?

Yes of course
The models that are not displayed at all neither with type: NodeType.webGLB, nor type: NodeType.localGLTF2 https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fpteranodon.glb?alt=media&token=f34c1730-6f77-4903-94da-f0aeebb66bbf https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Ft_rex.glb?alt=media&token=168ddba9-5902-47f1-a127-4e0ef803bcea
The model that is displayed succesfully using type: NodeType.webGLB, or type: NodeType.localGLTF2 https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fbrachiosaurus.glb?alt=media&token=f8f9b491-7441-4641-ad7f-d47e15d03180

hey @svyazist2005 , I justed wanted to have a look at your problem but unfortunately I get "Error 403: permission denied" on the links to your models, could you make them public please?

that's really strange, especially if there are no errors... can you send me a link to the webGLB model that you use so I can have a look at the problem?

Yes of course
The models that are not displayed at all neither with type: NodeType.webGLB, nor type: NodeType.localGLTF2 https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fpteranodon.glb?alt=media&token=f34c1730-6f77-4903-94da-f0aeebb66bbf https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Ft_rex.glb?alt=media&token=168ddba9-5902-47f1-a127-4e0ef803bcea
The model that is displayed succesfully using type: NodeType.webGLB, or type: NodeType.localGLTF2 https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fbrachiosaurus.glb?alt=media&token=f8f9b491-7441-4641-ad7f-d47e15d03180

hey @svyazist2005 , I justed wanted to have a look at your problem but unfortunately I get "Error 403: permission denied" on the links to your models, could you make them public please?

Should work now
https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fpteranodon.glb?alt=media&token=9a553d30-ffda-4588-81c9-2412d2b7172c
https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Ft_rex.glb?alt=media&token=177b7085-13f4-4870-97fd-38a52973921a
https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fbrachiosaurus.glb?alt=media&token=9f0f3650-456c-42ad-b2ed-4c1249512d61

Just tested this with your first model (https://firebasestorage.googleapis.com/v0/b/stridenseek.appspot.com/o/files%2FAR_Models%2Fpteranodon.glb?alt=media&token=9a553d30-ffda-4588-81c9-2412d2b7172c). It downloads just fine, but during runtime I get the following error:
F/libc    (15851): Fatal signal 11 (SIGSEGV), code 2 (SEGV_ACCERR), fault addr 0x78f2f7bfe4 in tid 16459 (AsyncTask #5), pid 15851 (_plugin_example)

According to this ARCore SDK issue, this hints towards a broken 3D model (please note that being able to open a model with 3D viewers like Blender does not mean they are error-free, many of the viewers can handle minor errors that ARCore or ARKit cannot handle). I suspect that when you test on iOS, you don't get any errors because they are more secretive in terms of memory corruption errors, but it should still be the same cause.
I checked your model with the official glTF Validator and there are several errors, so this seems to be a problem with the models you use (or the missing error-tolerance of ARCore and ARKit), but not with this plugin.

Try to add your model in blender into a empty object first.


Allow Symfony 7

Thank you for this contribution
I'm always late on that kind of thing
Do you think you can update the testing matrix to also run the code on symfony 7 ?

As I saw you had some trouble with tests, I did it on another PR https://github.com/yokai-php/batch-src/pull/111


Generic batching decorators

Purpose
There are a lot of operations that will need to be batch processed over fovs for large cohorts.  This PR seeks to add a way to easily add batch support for 'per-fov' operations.
Implementation
Adds the batch_utils.py file, which holds functions for creating generic 'batching strategies' as well as a function decorator @make_batch_function(func, strategy).   So far, this successfully implements batching for the spatial enrichment calculation functions, and is able to automatically determine the appropriate function signature to compare with the user provided docstring.  See spatial_analysis.batch_channel_spatial_enrichment.
Remaining issues
Not really sure how to test batch_utils.  Also, getting the autodocs working for these functions is the largest reason for the added complexity involving exec().  If the complexity doesn't seem worth clean docs, then setting the docs conf.py to ignore argument checks on functions prefixed with batch_ may be in order, but this necessitates stronger review of documentation on batch_ functions...

Stale, closing for now


Null id's on inner objects

Hello,
I'm starting now using the plugin, and I have now noticed that by default, nested objects get null id fields when indexing.
Using the samples as an example, in the Team object, the nested object Country gets an null id field after the document is indexed, even if the Country instance passed has an id field.
Is there any specific reason for this?
Any help is greatly appreciated.

Maybe I rushed into creating the issue; from my refreshed understanding, an id is only inherent to a document indexed, not to an object.
Assuming that I am right, it now seems that I need to implement my own id in java if I want to do something like: on updating a country object, update all the teams that have that country as an inner object. Am I right?


Don't include "save-agent" on Windows because of the missing libcurl dependency

Converted to draft as discussed with @petertrr.


Using scopes on Security() changes dependency inheritance

First Check

[X] I added a very descriptive title to this issue.
[X] I used the GitHub search to find a similar issue and didn't find it.
[X] I searched the FastAPI documentation, with the integrated search.
[X] I already searched in Google "How to X in FastAPI" and didn't find any information.
[X] I already read and followed all the tutorial in the docs and didn't find an answer.
[X] I already checked if it is not related to FastAPI but to Pydantic.
[X] I already checked if it is not related to FastAPI but to Swagger UI.
[X] I already checked if it is not related to FastAPI but to ReDoc.

Commit to Help

[x] I commit to help with one of those options 👆

Example Code
async def get_authenticated_user(security_scopes: SecurityScopes,
                                 session: Session = Depends(get_session),
                                 token: str = Depends(oauth2_scheme),
                                 ):

    print(f"get_authenticated_user: {id(session)}")
    return

@router.post('/activate', status_code=204)
async def user_activate(session: Session = Depends(get_session),
                        user: UserAccountInDatabase = Security(
                            get_authenticated_user,
                            scopes=["activate"])):
    print(f"user_activate: {id(session)}")
    return

Description
As you can see I have scopes=["activate"] defined in this Security() example.
The result will print:
get_authenticated_user:<PHONE_NUMBER>28496
user_activate:<PHONE_NUMBER>12848

As you can see the IDs of both sessions are different, this is unexpected to me as I was under the impression that arguments propagate through dependencies.
The weird thing is that when I remove scopes=["activate"] from Security() I do get the expected result:
get_authenticated_user:<PHONE_NUMBER>43088
user_activate:<PHONE_NUMBER>43088

I figured this out when I tried to commit a change in the UserAccountInDatabase object and sqlalchemy complained that the object does not belong to the same Session.
I'm wondering if this has anything to do with the instantiation of a SecurityScopes at some point by Security(). I tried manually adding the security scopes like this:
activation_security_scope = SecurityScopes(["activate"])
@router.post('/activate', status_code=204)
async def user_activate(session: Session = Depends(get_session),
                        security_scopes: SecurityScopes = activation_security_scope,
                        user: UserAccountInDatabase = Depends(
                            get_authenticated_user)):
    print(f"user_activate: {id(session)}")
    print(security_scopes.scope_str)

But this actually will just show that security_scopes is empty, it almost seems like it's being overwritten somewhere (maybe by the Depends(get_authenticated_user).
As I'm new to FastAPI there's a big chance I'm misunderstanding something.
Operating System
Linux
Operating System Details
No response
FastAPI Version
0.87.0
Python Version
3.11.0
Additional Context
No response

Dependant object has a cache_key attribute which the dependency resolver of fastapi uses it to cache dependencies and use the already resolved dependencies (get_session in this case).
according to this line of Dependant class the cache_key is generated using the dependency function reference and security scopes.
when you use get_authenticated_user as a security dependency every param in get_authenticated_user gets the security scopes of the parent api (user_activate).
so when resloving dependencies from user_activate with scopes, the param session: Session = Depends(get_session) gets saved in dependency_cache with a key like (<function get_session at 0x7fb87827c9d0>, ('activate'))
when resloving dependencies from user_activate with no scopes, the param session: Session = Depends(get_session) gets saved in dependency_cache with a key like (<function get_session at 0x7fb87827c9d0>, ())
i think this behavior might be a security feature.


Actual type checking for .children in components like If, Switch, etc.

I keep forgetting to do () => (
...
) instead of just putting

 which feels more natural; this causes a runtime error.

how does it cause an error ?


Setup npm package 🚀

This PR converts the requires and setup the package for npm!

Wrong repo sorry!


irmin-pack: Pack_store assumes that index entries are valid

The GC routine doesn't clean up index for simplicity. In exchange, we should be really careful in pack_store.ml to never assume that if a key exists in index it then exists in the pack files (i.e. suffix and prefix).
The GC is not the only source of such problems. The user could be holding corrupted keys. We already have mechanisms and policies in place in pack_store.ml to deal with such corrupted keys, but these mechanisms should be revised now that the GC exists.

@vect0r-vicall found a problem when re-commiting a commit that was previously GCed.
IIUC, the unsafe_append function in pack_store.ml skips the saving of this commit because it sees this hash in index.

Fixed with https://github.com/mirage/irmin/pull/2070


Calculate boot time with sub-second precision

If we do the "triple vdso sandwich" a couple of times and take the
results from the iteration that has the lowest time delta between the
first and last clock_gettime(), we can get pretty good precision.
My test showed ~30ns of accuracy.
Test plan:
$ sudo bpftrace -e 'i:s:1 { printf("%s\n", strftime("%D %H:%M:%S %P %Z", 0)); }'
Attaching 1 probe...
08/17/20 18:28:19 pm PDT

Which corresponds to my last reboot time:
$ last reboot | head -n1
reboot   system boot  5.7.12-arch1-1   Mon Aug 17 18:28   still running

Checklist

[NA] Language changes are updated in docs/reference_guide.md
[NA] User-visible and non-trivial changes updated in CHANGELOG.md
[x] The new behaviour is covered by tests

cc @suyuee

Awesome, looks so nice!


Fix typo in placeholder styling for the Internet Explorer

Displayed in Internet Explorer 11, text placeholder looks same as input text. Please check my fiddle with Internet Explorer 11.

(Screen Capture from my fiddle)
===
This mistake is caused by typo in selecting pseudo class -ms-input-placeholder, so I fixed it. When fixing, I looked this MSDN document.
And I used !important in some error case because I had to get higher specificity than other style like below.
.ui.form .field.error input[type='text']

@blackawa :clap: thanks for a very clear and easy to merge pull request

Thank you for merging! I am proud to contribute Semantic-UI. :love_letter:

Altough typo is fixed on 2.2 milestone, the issue is still reproducible. I solved this by adding these lines to my main css file.
.form.ui input:not([type]), .form.ui input[type=text], .form.ui input[type=email], .form.ui input[type=search], .form.ui input[type=password], .form.ui input[type=date], .form.ui input[type=datetime-local], .form.ui input[type=tel], .form.ui input[type=time], .form.ui input[type=url], .form.ui input[type=number] {     color: rgba(191, 191, 198, 1); }
and
.ui.dropdown > .default.text {     color: rgba(191,191,198,1); }


could not load templates

when i run nuclei on your tamplates , some of them excluded . i don't know why?

Some of the templates are excluded based upon nuclei settings, you can read more about that here: https://nuclei.projectdiscovery.io/nuclei/get-started/#template-exclusion.
I'll look into CVE-2020-19625.yaml and fix the unknown escape character and with the header-blind-ssrf.yaml, you'll need to make sure the payload paths exist, or edit the payload paths to match whatever payloads you want to use. By default, those payloads are located in the helpers directory, which you can find here: https://github.com/projectdiscovery/nuclei-templates/tree/master/helpers

CVE-2020-19625.yaml is fixed. Let me know if you have any more issues.


Refactor / Optimisation: Improve Suite size / cucumber rake time

The second of a few small(er) issues I'm tagging as "Good for newcomers"
This one is only a 1liner, but is potentially trickier.

Try to refactor all of the htm pages (Including home.htm and section_experiments.htm) into several smaller pages. This will make triaging and runtimes slightly better as well as reducing the amount of suite overhead.

Pitfalls to watch out for

Once fixing this up, dependent on your route there will be then some cucumber timings that might be thrown off, these should be self-evident though.
For bonus points see if you can then tweak the JS delays to be lower (Anything down to 750ms will give us a massive improvement - anything lower than 250ms gets flaky), to improve the suite runtime on travis

Feel free to ask if there are any issues. This one is a potential for being done in 2 PR's as it's quite intertwined.

With #351 this issue is now closer to being "close-able"


Update portal version on preprod and prod

In order to make MAP working well, we need to deploy<EMAIL_ADDRESS>to preprod, prod.

deployed<EMAIL_ADDRESS>to demo, preprod


Fix https://github.com/zfcampus/zf-mvc-auth/issues/106

This PR is part of the fix for https://github.com/zfcampus/zf-mvc-auth/issues/106
Associated PR is available here: https://github.com/zfcampus/zf-mvc-auth/pull/107

@weierophinney
Work done as promised on IRC. Please review.
Thank you for your time.

After more thinking, I think that the solution provided here is bad because this involve too much kaking in existents listener (eg, resetting response and so on). Right now, close this PR. I'll provide a new one soon.


Extend MTEB with French datasets

Adding:

French evaluation script
Bitext Mining

Flores
DiaBLa

Classification

MasakhaNews

Pair Classification

Opusparcus
Add multilingual management

Clustering

Dataset creation for HAL S2S clustering and upload on Hugging Face
Script creating data for AlloProf dataset
AlloProfClusteringP2P
AlloProfClusteringS2S
AlloProfClusteringP2P
MLSUMClusteringS2S
MasakhaNewsClusteringS2S
MasakhaNewsClusteringP2P

Retrieval

AlloprofRetrieval
BSARDRetrieval
HagridRetrieval
SyntecRetrieval

Reranking

AlloprofReranking
SyntecReranking

STS

STSBenchmarkMultilingualSTS
SickFrSTS

Summariaztion

SummEvalFrSummarization

If you can update with the changes on main, maybe we can merge this soon? 🚀
I think that we'll have >30 French datasets with this, so I can create a new Overall leaderboard for it so we can now what's the best french embedding model! 👍

Yeah ! 🚀 I made the change, do you need the json results ?

Yes that would be great!

Yeah ! 🚀 I made the change, do you need the json results ?

Yes that would be great!

Hey @Muennighoff, do you need the results to be merged in this repository https://huggingface.co/datasets/mteb/results, or can we juste give you the json files we have ?

Yeah ! 🚀 I made the change, do you need the json results ?

Yes that would be great!

Hey @Muennighoff, do you need the results to be merged in this repository https://huggingface.co/datasets/mteb/results, or can we juste give you the json files we have ?

Yeah feel free to directly open a PR there e.g. like this one: https://github.com/embeddings-benchmark/mteb/pull/218#issuecomment-1954251913
You just need to create a folder for each model and place the files in there; You can clone the repo with git clone ... ; instructions are also here https://huggingface.co/datasets/mteb/results/discussions?new_pr=true

Yeah ! 🚀 I made the change, do you need the json results ?

Yes that would be great!

Hey @Muennighoff, do you need the results to be merged in this repository https://huggingface.co/datasets/mteb/results, or can we juste give you the json files we have ?

Yeah feel free to directly open a PR there e.g. like this one: #218 (comment)
You just need to create a folder for each model and place the files in there; You can clone the repo with git clone ... ; instructions are also here https://huggingface.co/datasets/mteb/results/discussions?new_pr=true

I think we are good with the changes, and the results are there : https://huggingface.co/datasets/mteb/results/discussions/28

Yeah ! 🚀 I made the change, do you need the json results ?

Yes that would be great!

Hey @Muennighoff, do you need the results to be merged in this repository https://huggingface.co/datasets/mteb/results, or can we juste give you the json files we have ?

Yeah feel free to directly open a PR there e.g. like this one: #218 (comment)
You just need to create a folder for each model and place the files in there; You can clone the repo with git clone ... ; instructions are also here https://huggingface.co/datasets/mteb/results/discussions?new_pr=true

I think we are good with the changes, and the results are there : https://huggingface.co/datasets/mteb/results/discussions/28

Amazing! I think this one would still be nice https://github.com/embeddings-benchmark/mteb/pull/218#discussion_r1495008081 if okay with you but other than that we can merge both!

Yeah ! 🚀 I made the change, do you need the json results ?

Yes that would be great!

Hey @Muennighoff, do you need the results to be merged in this repository https://huggingface.co/datasets/mteb/results, or can we juste give you the json files we have ?

Yeah feel free to directly open a PR there e.g. like this one: #218 (comment)
You just need to create a folder for each model and place the files in there; You can clone the repo with git clone ... ; instructions are also here https://huggingface.co/datasets/mteb/results/discussions?new_pr=true

I think we are good with the changes, and the results are there : https://huggingface.co/datasets/mteb/results/discussions/28

Amazing! I think this one would still be nice #218 (comment) if okay with you but other than that we can merge both!

@Muennighoff we made the changes for #218 (comment), can you please have a look at AbsTaskClustering, MasakhaNEWSClusteringP2P and MasakhaNEWSClusteringS2S ?

Yes let's merge ! 💯

Still need to update MasakhaNEWS files in https://huggingface.co/datasets/mteb/results/discussions/28 I think & then I will add a French leaderboard tab if you want! 🙌 Should I just link to your GitHub accounts / this PR for the Credits of the new tabs or are you planning to write a paper on it?

I think the leaderboard(s) would consist of the following:
TASK_LIST_CLASSIFICATION_FR = [
    "AmazonReviewsClassification (fr)",
    "MasakhaNEWSClassification (fra)",
    "MassiveIntentClassification (fr)",
    "MassiveScenarioClassification (fr)",
]

TASK_LIST_CLUSTERING_FR = [
    "AlloProfClusteringP2P",
    "AlloProfClusteringS2S",
    "HALClusteringS2S",
    "MLSUMClusteringP2P",
    "MLSUMClusteringS2S",
    "MasakhaNEWSClusteringP2P (fra)",
    "MasakhaNEWSClusteringS2S (fra)",
]

TASK_LIST_PAIR_CLASSIFICATION_FR = [
    "OpusparcusPC (fr)",
    "PawsX (fr)",
]

TASK_LIST_RERANKING_FR = [
    "AlloprofReranking",
    "SyntecReranking",
]
TASK_LIST_RETRIEVAL_FR = [
    "AlloprofRetrieval",
    "BSARDRetrieval",
    "MintakaRetrieval",
    "MultiLongDocRetrieval",
    "SyntecRetrieval",
    "XPQARetrieval",
]
TASK_LIST_STS_FR = [
    "STS22 (fr)",
    "STSBenchmarkMultilingualSTS (fr)",
    "SICKFr",
]
TASK_LIST_SUMMARIZATION_FR = ["SummEvalFr"]

It's a total of 25 so also enough for an overall leaderboard tab imo.
Let me know if I am missing anything!
Also I added a few other French tasks like xPQA etc. not from this PR - would be great if you could eval on them too 🙌

We will re-run the evaluations on MasakhaNEWS and update de the files, we will also run evals on the datasets you added. The PR will be updated soon.
For the Credits, we have a paper that is under review for the moment. You can still add our GitHub accounts maybe ?
Concerning the list of tasks for the leaderboard, I think you can add these two tasks in TASK_LIST_CLASSIFICATION: "MTOPDomainClassification", "MTOPIntentClassification".

We will re-run the evaluations on MasakhaNEWS, we will also run evals on the datasets you added. The PR will be updated soon.

Amazing!

For the Credits, we have a paper that is under review for the moment. You can still add our GitHub accounts maybe ?

Cool! Happy to help if I can be useful! I will put your GitHubs in the meantime 👍

Concerning the list of tasks for the leaderboard,

Good catch - 27 datasets then!

@Muennighoff do you need models charcteristics like their size, embedding dim and max token lenght for the leaderboard ? We have already gathered them into these two files (CSV or JSON, you choose what suits you most):
JSON: https://github.com/Lyon-NLP/mtebscripts/blob/main/script_mteb_french/results_analysis/model_specs.json
CSV: https://github.com/Lyon-NLP/mtebscripts/blob/main/script_mteb_french/results_analysis/models_characteristics.csv

Do you also want to run the French split of MultiLongDocRetrieval and include it? I saw it wasn't included in the result files

I have preliminary added the French leaderboard: https://huggingface.co/spaces/mteb/leaderboard 🇫🇷🚀
Let me know if we should change anything / feel free to open a PR! Also would be cool to still include MultiLongDocRetrieval I think :)

I have preliminary added the French leaderboard: https://huggingface.co/spaces/mteb/leaderboard 🇫🇷🚀 Let me know if we should change anything / feel free to open a PR! Also would be cool to still include MultiLongDocRetrieval I think :)

That's so great, thanks ! Just a small comment, could you please add @schmarion in the credits section ?
Also, I think we evaluated 46 models, but I'm seeing only 23 on the leaderboard (text-embedding-ada-002 is missing for example, same for sentence-t5-** and multilingual-e5-**), do you know why ?
I've seen that the evaluation for SummEvalFr is also missing.
We'll check MultiLongDocRetrieval and will open a PR with the results soon.

Thanks a lot ! So good to finally see the results there 🤩 . Could you please rebind my name in the credits. I happen to have change my name recently and the link is broken... @MathieuCiancone

Hi guys! I just want to congratulate everybody who has worked on this! You made my day!

I have preliminary added the French leaderboard: https://huggingface.co/spaces/mteb/leaderboard 🇫🇷🚀 Let me know if we should change anything / feel free to open a PR! Also would be cool to still include MultiLongDocRetrieval I think :)
Edit: A few models still missing, updating....

I looked into the dataset and it is actually quite huge (not even talking about the English subset 😅). Even for text embedding API (which tend to be cheap), embedding the whole corpus would lead to significant API costs (including openai 3 embedding model, mistral, voyage and cohere). I think we will save this for smaller datasets, as a greater variety of datasets is more insightful that bigger datasets... 🤔

I looked into the dataset and it is actually quite huge (not even talking about the English subset 😅). Even for text embedding API (which tend to be cheap), embedding the whole corpus would lead to significant API costs (including openai 3 embedding model, mistral, voyage and cohere). I think we will save this for smaller datasets, as a greater variety of datasets is more insightful that bigger datasets... 🤔

So for French, it's 20 queries & 10K docs w/ 9.6K avg characters per doc. I think it's comparable to TREC-COVID which is 171K docs but only ~900 avg characters per doc. TREC-COVID is one of the cheapest English Retrieval datasets. Also for many models that cannot handle the long sequence length of 9.6K characters it'll be cheaper. But ofc up to you, no worries if you don't want to include it 👍


testnet network support - akk1s7ifu5oma48 - validator,rpc,api

@equiknoxxc, Your Moniker and validator addresses are required, please update the PR with those details.

@equiknoxxc, Your Moniker and validator addresses are required, please update the PR with those details.

@equiknoxxc, Your Moniker and validator addresses are required, please update the PR with those details.

Moniker: equiknoxxc
Address: akashvaloper13anhrmul629dzz4q4nzn0hsjwdqw8smh7ve04g

@equiknoxxc, Your Moniker and validator addresses are required, please update the PR with those details.

Moniker: equiknoxxc
Address: akashvaloper13anhrmul629dzz4q4nzn0hsjwdqw8smh7ve04g


Silent compiler warning: unused function

Status
IN DEVELOPMENT/READY
Migrations
NO
Description
When compiling with reduced configuration compiler causes warnings by default because of unused function. This PR silents those warnings
Related PRs
#92
Todos

[x] Tests

build mbed-os3-frdm-k64f-armcc fails because of missing ARMCC compiler in CI (ISGTESTINF-1041)

Did "static inline" not work?

trying another approach by using attribute unused: #95 . Closing this for now

Did "static inline" not work?

no it did not for some reason.


FSDP checkpoint loading fails

Bug description
I have a sharded checkpoint which was saved via  trainer.save_checkpoint("/path/to/cp/dir/", weights_only=False which I am trying to load during test via trainer.test(dataloaders=test_dataloader, ckpt_path="/path/to/cp/dir") but the loading part bugs out.
Here is a partial stack trace:
File "virtualenv/lib/python3.10/site-packages/site-packages/torch/distributed/checkpoint/state_dict_loader.py", line 226, in read_data
all_reads = storage_reader.read_data(final_local_plan, planner)
File "/tmp/ray/session_2024-10-23_03-46-10_056159_1/runtime_resources/pip/191a23b956de22e15c5c2fb65461774803fa6c56/virtualenv/lib/python3.10/site-packages/site-packages/torch/distributed/checkpoint/filesystem.py", line 665, in read_data
target_tensor.size() == tensor.size()
AssertionError: req MetadataIndex(fqn='model.model.model.embed_tokens.weight', offset=torch.Size([0, 0]), index=0) mismatch sizes torch.Size([1571]) vs torch.Size([1571, 3072]

I was able to load the checkpoint into the model state dict via a notebook without facing an exception.
I have also manually inspected the metadata file and it seems to be in order. The sizes of the shards are also well within expectations.
Would appreciate any help or tips for further debugging. Thanks!
What version are you seeing the problem on?
v2.4
How to reproduce the bug
No response
Error messages and logs
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) File "/tmp/ray/session_2024-10-23_03-46-10_056159_1/runtime_resources/pip/191a23b956de22e15c5c2fb65461774803fa6c56/virtualenv/lib/python3.10/site-packages/site-packages/torch/distributed/checkpoint/state_dict_loader.py", line 226, in read_data
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) all_reads = storage_reader.read_data(final_local_plan, planner)
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) File "/tmp/ray/session_2024-10-23_03-46-10_056159_1/runtime_resources/pip/191a23b956de22e15c5c2fb65461774803fa6c56/virtualenv/lib/python3.10/site-packages/site-packages/torch/distributed/checkpoint/filesystem.py", line 665, in read_data
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) target_tensor.size() == tensor.size()
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) AssertionError: req MetadataIndex(fqn='model.model.model.layers.26.self_attn.v_proj.weight', offset=torch.Size([0, 0]), index=0) mismatch sizes torch.Size([32]) vs torch.Size([32, 3072])
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) Traceback (most recent call last): (RANK 31)
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) File "/tmp/ray/session_2024-10-23_03-46-10_056159_1/runtime_resources/pip/191a23b956de22e15c5c2fb65461774803fa6c56/virtualenv/lib/python3.10/site-packages/site-packages/torch/distributed/checkpoint/utils.py", line 249, in all_gather
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) result = map_fun()
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) File "/tmp/ray/session_2024-10-23_03-46-10_056159_1/runtime_resources/pip/191a23b956de22e15c5c2fb65461774803fa6c56/virtualenv/lib/python3.10/site-packages/site-packages/torch/distributed/checkpoint/logger.py", line 66, in wrapper
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) result = func(*args, **kwargs)
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) File "/tmp/ray/session_2024-10-23_03-46-10_056159_1/runtime_resources/pip/191a23b956de22e15c5c2fb65461774803fa6c56/virtualenv/lib/python3.10/site-packages/site-packages/torch/distributed/checkpoint/state_dict_loader.py", line 226, in read_data
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) all_reads = storage_reader.read_data(final_local_plan, planner)
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) File "/tmp/ray/session_2024-10-23_03-46-10_056159_1/runtime_resources/pip/191a23b956de22e15c5c2fb65461774803fa6c56/virtualenv/lib/python3.10/site-packages/site-packages/torch/distributed/checkpoint/filesystem.py", line 665, in read_data
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) target_tensor.size() == tensor.size()
(RayTrainWorker pid=2657016, ip=<IP_ADDRESS>) AssertionError: req MetadataIndex(fqn='model.model.model.layers.27.self_attn.q_proj.weight', offset=torch.Size([0, 0]), index=0) mismatch sizes torch.Size([96]) vs torch.Size([96, 3072])

Environment

Current environment

CUDA:
- GPU:
- NVIDIA H100 80GB HBM3
- NVIDIA H100 80GB HBM3
- available:         True
- version:           12.1
Lightning:
- torch:             2.4.0
Packages:
- appdirs:           1.4.4
- argon2-cffi:       21.1.0
- attrs:             21.2.0
- babel:             2.8.0
- backcall:          0.2.0
- beautifulsoup4:    4.10.0
- beniget:           0.4.1
- bleach:            4.1.0
- blinker:           1.4
- bluorion:          0.0.0
- brotli:            1.0.9
- chardet:           4.0.0
- cryptography:      3.4.8
- cycler:            0.11.0
- dbus-python:       1.2.18
- decorator:         4.4.2
- defusedxml:        0.7.1
- distro:            1.7.0
- distro-info:       1.1+ubuntu0.2
- entrypoints:       0.4
- filelock:          3.16.1
- fonttools:         4.29.1
- fs:                2.4.12
- fsspec:            2024.10.0
- gast:              0.5.2
- git-crecord:       20201025.0
- html5lib:          1.1
- httplib2:          0.20.2
- importlib-metadata: 4.6.4
- ipykernel:         6.7.0
- ipython:           7.31.1
- ipython-genutils:  0.2.0
- ipywidgets:        6.0.0
- jedi:              0.18.0
- jeepney:           0.7.1
- jinja2:            3.0.3
- jsonschema:        3.2.0
- jupyter-client:    7.1.2
- jupyter-core:      4.9.1
- jupyterlab-pygments: 0.1.2
- keyring:           23.5.0
- kiwisolver:        1.3.2
- launchpadlib:      1.10.16
- lazr.restfulclient: 0.14.4
- lazr.uri:          1.0.6
- lxml:              4.8.0
- lz4:               3.1.3+dfsg
- markupsafe:        2.0.1
- matplotlib:        3.5.1
- matplotlib-inline: 0.1.3
- more-itertools:    8.10.0
- mpmath:            0.0.0
- nbclient:          0.5.6
- nbconvert:         6.4.0
- nbformat:          5.1.3
- nest-asyncio:      1.5.4
- networkx:          3.4.2
- notebook:          6.4.8
- numpy:             1.21.5
- nvidia-cublas-cu12: <IP_ADDRESS>
- nvidia-cuda-cupti-cu12: 12.1.105
- nvidia-cuda-nvrtc-cu12: 12.1.105
- nvidia-cuda-runtime-cu12: 12.1.105
- nvidia-cudnn-cu12: <IP_ADDRESS>
- nvidia-cufft-cu12: <IP_ADDRESS>
- nvidia-curand-cu12: <IP_ADDRESS>
- nvidia-cusolver-cu12: <IP_ADDRESS>
- nvidia-cusparse-cu12: <IP_ADDRESS>
- nvidia-nccl-cu12:  2.20.5
- nvidia-nvjitlink-cu12: 12.6.77
- nvidia-nvtx-cu12:  12.1.105
- oauthlib:          3.2.0
- olefile:           0.46
- packaging:         21.3
- pandocfilters:     1.5.0
- parso:             0.8.1
- pexpect:           4.8.0
- pickleshare:       0.7.5
- pillow:            9.0.1
- pip:               22.0.2
- ply:               3.11
- prometheus-client: 0.9.0
- prompt-toolkit:    3.0.28
- ptyprocess:        0.7.0
- py:                1.10.0
- pygments:          2.11.2
- pygobject:         3.42.1
- pyjwt:             2.3.0
- pyparsing:         2.4.7
- pyrsistent:        0.18.1
- python-apt:        2.4.0+ubuntu4
- python-dateutil:   2.8.1
- pythran:           0.10.0
- pytz:              2022.1
- pyyaml:            5.4.1
- pyzmq:             22.3.0
- scipy:             1.8.0
- secretstorage:     3.3.1
- send2trash:        1.8.1b0
- setuptools:        59.6.0
- six:               1.16.0
- soupsieve:         2.3.1
- sympy:             1.9
- terminado:         0.13.1
- testpath:          0.5.0
- torch:             2.4.0
- tornado:           6.1
- traitlets:         5.1.1
- triton:            3.0.0
- typing-extensions: 4.12.2
- ufolib2:           0.13.1
- unattended-upgrades: 0.1
- unicodedata2:      14.0.0
- wadllib:           1.3.6
- wcwidth:           0.2.5
- webencodings:      0.5.1
- wheel:             0.37.1
- widgetsnbextension: 2.0.0
- zipp:              1.0.0
System:
- OS:                Linux
- architecture:
- 64bit
-
- processor:         x86_64
- python:            3.10.12
- release:           5.15.0-122-generic
- version:           #132-Ubuntu SMP Thu Aug 29 13:45:52 UTC 2024

More info
I am using Ray for orchestration.
cc @awaelchli

Hey @Nilabhra really hard to debug this case with sparse info. Would you be able to provide a minimal repro? Or the checkpoints eventually randomly re-initialized?
This
AssertionError: req MetadataIndex(fqn='model.model.model.layers.26.self_attn.v_proj.weight', offset=torch.Size([0, 0]), index=0) mismatch sizes torch.Size([32]) vs torch.Size([32, 3072])

and
AssertionError: req MetadataIndex(fqn='model.model.model.layers.27.self_attn.q_proj.weight', offset=torch.Size([0, 0]), index=0) mismatch sizes torch.Size([96]) vs torch.Size([96, 3072])

look really suspect, because the lhs doesn't have any embedding dimension, which is very weird for v_proj and q_proj even sharded.
What did you end up doing in the notebook in order to load the checkpoint in the end?

Hi @lantiga! Thanks for your reply. For now, I have commented out this line here: https://github.com/Lightning-AI/pytorch-lightning/blob/056bb0834b8fca739dec3e731b01f2f6631be142/src/lightning/pytorch/trainer/trainer.py#L931 and that seems to be working for now. I still don't know what is a proper fix.


NPC Deliveries with Enchanted Items ignore Durability

What is your Quests version / build number (do not say "latest")?
3.9.6
Describe the problem and how to replicate it. Any console errors to post using Pastebin.com?
For the NPC Deliver objective, durability will be ignored on enchanted items with a max durability value. Meaning if the required Diamond Pickaxe quest item needs to have Curse of Vanishing, all diamond pickaxes with Curse of Vanishing, whether they are at full or low durability, count for the quest.
If applicable, can you provide an example quest from quests.yml using Pastebin.com?
https://pastebin.com/DC1wptwK

Thanks for the report. What is your server's Minecraft version?

We’re running 1.16.3.

I have been unable to replicate this issue on Minecraft 1.16. Using your example quest, I spawned a Diamond Pickaxe with Curse of Vanishing, proceeded to damage a few blocks of stone with it, and then tried to turn it in for the quest. The item was refused on grounds of durability not matching.

Feel free to request re-open should more information come to light. Thanks!


This article is really useful but I think that the PowerShell script refer to obsolete SKUs

GatewaySku HighPerformance
I don't think "High Perfomance" is still a SKU - maybe - VpnGw1 ?
I am not an expert PS user
FWIW this article was hugely useful to me.
I needed a policy based VPN but the one you get if you select "Policy" on the creation tab is a very very basic development VPN that does not meet many corporate needs. I found this article after quite a bit of searching and it might a big difference.
Thankyou
Document Details
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.

ID: b2c33f22-7243-bb33-38b9-fcf30e68ffe6
Version Independent ID: c1a3a25a-26d0-acdf-d5f2-1d1c057a3e5b
Content: Connect VPN gateways to multiple on-premises policy-based VPN devices - Azure VPN Gateway
Content Source: articles/vpn-gateway/vpn-gateway-connect-multiple-policybased-rm-ps.md
Service: vpn-gateway
GitHub Login: @cherylmc
Microsoft Alias: cherylmc

@seancull
Thanks for your feedback! We will investigate and update as appropriate.

@seancull ,
Thank you for the feedback, I have made the suggested change and it will go live soon. Thank you!


add binary_search functionality for Array

The functionality added:

binary_search
binary_search_by

See code for more.

Pull Request Test Coverage Report for Build 2877
Details

9 of 9 (100.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.03%) to 83.755%

Totals

Change from base Build 2876:
0.03%

Covered Lines:
3841

Relevant Lines:
4586

💛  - Coveralls

@guuzaa thanks for you first contribution.
I made two tweaks:

inline the callback in binary_search
use our functional loop to make the code easier to reason about


Support for python-wink 1.0.0

Description:

Door/windows sensors names have changed to include what is called their capability so what was once binary_sensor.front_door will now be called binary_sensor.front_door_opened
Wink Relays will now report three more sensors.

the gang's connection status, will most likely be called gang and probably doesn't have much of a purpose.
The top button as a binary sensor indicating if the button was pressed.
The bottom button as a binary sensor indicating if the button was pressed.
Only switches that are connect to a load will show up

You no longer need to set your user-agent in the home-assistant config to get access to the Wink Relay sensors.
Lutron connected bulb remotes will show up as a binary_sensor. The status of that sensor will be true if any button on the remote is pressed. The sensor has attributes for each button so new sensors can be made with a template sensor or automations can be made with template triggers. (Pico remotes aren't supported)
Quirky powerstrips now report three devices

Outlet 1
Outlet 2
The main power strip. Toggling the powerstrip device will turn on/off both outlets at once.

Canary cameras are support as an alarm control panel. With the following state translations.

Disarm = Home
Armed = Away
Armed Home = Night
There is currently no support for setting privacy mode in Home-Assistant (Haven't figured it out yet)

Nest smoke protectors now report two more sensors

Smoke severity (I think in a percentage)
CO severity also in a percentage I think.

Sprinklers are now support should show up as a binary switch
Door bells are supported as binary sensors

Motion
Button pressed

There is a new method of authentication. If you don't have a client_id and client_secret you can add just your email and password to the config and your access token will be pulled from the home-assistant.io site automatically during startup. @balloob You mentioned adding a web service to access the Wink token. If you can, please see if the method I am using is acceptable, I am using the current form on the home-assistant.io site. Once this is vetted we could remove the form and maybe change it to return JSON? This current method also grabs a new token on every restart which is what happens when setting a client_id and client_secret in the config today.

Related issue (if applicable): fixes stuff mentioned here https://community.home-assistant.io/t/ha-stops-reporting-wink-state-changes
Pull request in home-assistant.github.io with documentation (if applicable): home-assistant/home-assistant.github.io#<home-assistant.github.io PR number goes here>
Example entry for configuration.yaml (if applicable):
Config can now be set in three ways.
The original way, hard coded token requires manual refresh.
wink:
  access_token: TOKEN

If the user has their own client_id and client_secret, a new token is grabbed at every reboot and python-wink handles a token refresh when it is required.
wink:
  email: email
  password: password
  client_id: client_id
  client_secret: client_secret

A new token is grabbed from the home-assistant.io site at every startup. No refresh is done during the life time of the running hass instance.
wink:
  email: email
  password: password

Checklist:
If user exposed functionality or configuration variables are added/changed:

[ ] Documentation added/updated in home-assistant.github.io

If the code communicates with devices, web services, or third-party tools:

[ ] Local tests with tox run successfully. Your PR cannot be merged unless tests pass
[X] New dependencies have been added to the REQUIREMENTS variable (example).
[X] New dependencies are only imported inside functions that use them (example).
[X] New dependencies have been added to requirements_all.txt by running script/gen_requirements_all.py.

I have tested this PR and can confirm that solved a number of issues while extending functionality.

Looks good! :dolphin:

I do not control the Wink form. It is hosted by @loghound. His repo with the code is here: https://github.com/loghound/wink-token-generator


fix: Updating dbt extractor - to work on all json files

Summary of Changes
Fix for dbt example.
How is today:
The catalog.json file has the column names in uppercase. The manifest.json file has the column names in lowercase.
To work, there is a line in the dbt_extractor.py file applying an upper and this resolves for the example json.
But when I used it, it didn't work, because my two json files were already in lowercase.
At first, removing the upper worked for me, but the example stopped working. So I looked for a solution to work in my case and also in the example.
My suggestion to fix:
Remove from the dbt_extractor.py file the upper applied to the column names of the manifest.json.
And apply a lower on the reading of each json file.
That way, nobody needs to worry about the format of the dbt json files, because this solution will make both the same, and it will work in all projects.
Tests

Documentation

CheckList
Make sure you have checked all steps below to ensure a timely review.

[x] PR title addresses the issue accurately and concisely. Example: "Updates the version of Flask to v1.0.2"

In case you are adding a dependency, check if the license complies with the ASF 3rd Party License Policy.

[x] PR includes a summary of changes.
[x] PR adds unit tests, updates existing unit tests, OR documents why no test additions or modifications are needed.
[x] In case of new functionality, my PR adds documentation that describes how to use it.

All the public functions and the classes in the PR contain docstrings that explain what it does

unit tests fail:
=================================== FAILURES ===================================
_____________ TestCsvExtractor.test_dbt_file_inputs_as_json_dumps ______________

self = <tests.unit.extractor.test_dbt_extractor.TestCsvExtractor testMethod=test_dbt_file_inputs_as_json_dumps>

    @no_type_check
    def test_dbt_file_inputs_as_json_dumps(self) -> None:
        """
        Tests to ensure that the same content can be extracted when the manifest.json
        and catalog.json are provided as a file location or as a json.dumps() object
        """
        config_dict_1 = {
            f'extractor.dbt.{DbtExtractor.DATABASE_NAME}': self.database_name,
            f'extractor.dbt.{DbtExtractor.CATALOG_JSON}': self.catalog_file_loc,
            f'extractor.dbt.{DbtExtractor.MANIFEST_JSON}': self.manifest_data,
            f'extractor.dbt.{DbtExtractor.SOURCE_URL}': self.source_url
        }
        conf_1 = ConfigFactory.from_dict(config_dict_1)
        extractor_1 = DbtExtractor()
        extractor_1.init(Scoped.get_scoped_conf(conf=conf_1, scope=extractor_1.get_scope()))

        with open(self.catalog_file_loc, 'r') as f:
            catalog_as_json = json.dumps(json.load(f))

        with open(self.manifest_data, 'r') as f:
            manifest_as_json = json.dumps(json.load(f))

        config_dict_2 = {
            f'extractor.dbt.{DbtExtractor.DATABASE_NAME}': self.database_name,
            f'extractor.dbt.{DbtExtractor.CATALOG_JSON}': catalog_as_json,
            f'extractor.dbt.{DbtExtractor.MANIFEST_JSON}': manifest_as_json
        }
        conf_2 = ConfigFactory.from_dict(config_dict_2)
        extractor_2 = DbtExtractor()
        extractor_2.init(Scoped.get_scoped_conf(conf=conf_2, scope=extractor_2.get_scope()))

        result_1 = extractor_1.extract()
        result_2 = extractor_2.extract()
        self.assertEqual(result_1.name, result_2.name)
>       self.assertEqual(result_1.description.text, result_2.description.text)
E       AssertionError: 'the performance for third party vendors loss rate by day.' != 'The performance for third party vendors loss rate by day.'
E       - the performance for third party vendors loss rate by day.
E       ? ^
E       + The performance for third party vendors loss rate by day.
E       ? ^

tests/unit/extractor/test_dbt_extractor.py:126: AssertionError
______________ TestCsvExtractor.test_extraction_with_model_class _______________

self = <tests.unit.extractor.test_dbt_extractor.TestCsvExtractor testMethod=test_extraction_with_model_class>

    @no_type_check
    def test_extraction_with_model_class(self) -> None:
        """
        Test Extraction using model class
        """
        config_dict = {
            f'extractor.dbt.{DbtExtractor.DATABASE_NAME}': self.database_name,
            f'extractor.dbt.{DbtExtractor.CATALOG_JSON}': self.catalog_file_loc,
            f'extractor.dbt.{DbtExtractor.MANIFEST_JSON}': self.manifest_data,
            f'extractor.dbt.{DbtExtractor.SOURCE_URL}': self.source_url
        }
        self.conf = ConfigFactory.from_dict(config_dict)
        extractor = DbtExtractor()
        extractor.init(Scoped.get_scoped_conf(conf=self.conf,
                                              scope=extractor.get_scope()))

        # One block of tests for each type of model created
        extracted_classes = []

        result = extractor.extract()
        self.assertTrue(isinstance(result, TableMetadata))
        self.assertEqual(result.name, 'fact_third_party_performance')
>       self.assertEqual(result.description.text, 'The performance for third party vendors loss rate by day.')
E       AssertionError: 'the performance for third party vendors loss rate by day.' != 'The performance for third party vendors loss rate by day.'
E       - the performance for third party vendors loss rate by day.
E       ? ^
E       + The performance for third party vendors loss rate by day.
E       ? ^

tests/unit/extractor/test_dbt_extractor.py:60: AssertionError
______________ TestCsvExtractor.test_keys_retain_original_format _______________

self = <tests.unit.extractor.test_dbt_extractor.TestCsvExtractor testMethod=test_keys_retain_original_format>

    @no_type_check
    def test_keys_retain_original_format(self) -> None:
        """
        Test that the database name, cluster name, schema and table name do not
        have lowercase auto applied.
        """
        config_dict = {
            f'extractor.dbt.{DbtExtractor.DATABASE_NAME}': self.database_name.upper(),  # Force upper for test
            f'extractor.dbt.{DbtExtractor.CATALOG_JSON}': self.catalog_file_loc,
            f'extractor.dbt.{DbtExtractor.MANIFEST_JSON}': self.manifest_data,
            f'extractor.dbt.{DbtExtractor.FORCE_TABLE_KEY_LOWER}': False
        }
        conf = ConfigFactory.from_dict(config_dict)
        extractor = DbtExtractor()
        extractor.init(Scoped.get_scoped_conf(conf=conf, scope=extractor.get_scope()))

        result = extractor.extract()

        self.assertEqual(result.name, 'fact_third_party_performance')
        self.assertEqual(result.database, 'SNOWFLAKE')
>       self.assertEqual(result.cluster, 'DBT_DEMO')
E       AssertionError: 'dbt_demo' != 'DBT_DEMO'
E       - dbt_demo
E       + DBT_DEMO

tests/unit/extractor/test_dbt_extractor.py:153: AssertionError


Update chapter-5.md

just one missing word...

Thanks!

Thanks!

Many thanks to all of you for this great documentation!

Many thanks to all of you for this great documentation!


sequential compositor w/ static distances

Closes #7
This PR replaces the basic composition PR based on a suggestion from Salil. The internals are simpler, because the shared behavior captured in the AnyMeasure is just a function to sum distances.

Removed the EpsilonDelta struct, Midpoint/Tolerance traits, and binary search.
Replaced basic_composition with sequential_composition_with_static_distances

This is soft-blocked on the architectural changes in #233 amplification. The bindings layer doesn't know to wrap distances in AnyMeasureDistance structs instead of just AnyObjects. If we removed AnyMeasureDistances, then we'd no longer have the ambiguity.

Closing in favor of the approach in #424.


ARROW-6542 [R]: Add View() method to array types

Could you please add tests to call the new code? Otherwise LGTM.

+1 thanks!


Error when using the component into a built polymer application

When using the component into dev mode, or serving it from unbundled build, all it's ok, but when serving the application from a bundled build (polymer build) the following error raises :
Uncaught TypeError: this._PDF.getPage is not a function

fixed in version 2.1.0


support H2C (http2 clear text without TLS)

In the current version, the http2 with TLS works fine. But actually in the real 5G core network environment, usually the H2C is used, as the PDI or some other requirements. Please add this support and make it optional in the conf and the next release.
Thanks,
Daolin

I changed some related code today, and it seemed that H2C works when I run TestRegistration. If you like, I can share my changes to your group, and you can continue to add the parameter in conf to control this feature.

That sounds great!
How about give us a pull request and if there are something need to be added into the config, we could work together to complete this feature. 😃

Hi,
I didn't know how to use pull request. I attached the src and lib folder including all my changes (I didn't changed any other source code and config files). You can compare to
your base version.
src.zip
lib.zip

Hi,
We have patch an H2C version in v3.0.2.
Thanks for your inspiration. 👍


[Table] Is there a plan to add an enhancement of retaining table states after redirecting to edit page?

What package is this for?

React

Summary
As our team gets the requirement that the table component should keep the table state(filters, sorts for example) after redirecting to other pages(editing/adding page for example), leave a message to ask if there is a plan to add this enhancement to carbon-addons-iot-react package?

We don't handle multi-page states at the PAL React level, and it should likely stay that way, given that most teams such as Maximo have already created mature approaches for doing so.

We don't handle multi-page states at the PAL React level, and it should likely stay that way, given that most teams such as Maximo have already created mature approaches for doing so.


Partial exits

Are partial exits of a position possible?

Not a this moment. I made a shortcut in the beginning of the project by considering the trading process as simply entering a position at single point and exiting at single point. That helped me to get the ball rolling and I haven't needed partial enters or exits myself, so I haven't implemented support for those yet. I'd like to get those included some day though, but can't make any promises.
Anyway, thanks for checking out my project. If you have any other feedback, I'd love to hear it. :)


Making Custom Http Client Injection Singleton

@santhoshTpixler wrote:

I am using @TestPackageRoot("folder") for running tests. Also I am using custom HttpClient which produces access token. Access token is valid for one hour. So I store it in our Custom HttpClient. The problem is, HttpClient is created newly for every .json in the folder. Which means new access token is created for every .json file. We have limitation of 5 access token per minute. I have 10 json files in folder which roughly creates 10 access token, which is not possible with in a minute. I need to store the access token for the life cycle of all the tests. Is there any possibility? Looks like Junit creates new instance every time.

This could be overcome by using a static context variable i.e.

The token once generated can be held in a static context(i.e. save to a class level variable), then keep reading from that all the time until you renew the token and once you renew the token, update that static variable.

Santosh is already doing this way anyways. 👍
Note:
But The Http Client or the Kafka Client injection is supposed to be singleton already, hence fixing this make everyone's life better.

PR approved https://github.com/authorjapps/zerocode/pull/160

Fixed in version below-
<dependency>
    <groupId>org.jsmart</groupId>
    <artifactId>zerocode-rest-bdd</artifactId>
    <version>1.2.12</version>
</dependency>

Report view shows the one of the scenario twice - Reported by @santhoshTpixler on Gitter.
The singleton changes screwed it up while holding the RAW report-files in the memory.
It's minor issue - Fix is to initialize the scenario report for each scenario run in ZeroCodeMultiStepsScenarioRunnerImpl.java (as this is also singleton - Guice provided).

Fixed. PR here under review https://github.com/authorjapps/zerocode/pull/171

Fixed in
<dependency>
  <groupId>org.jsmart</groupId>
  <artifactId>zerocode-rest-bdd</artifactId>
  <version>1.2.16</version>
</dependency>


Revamp preview cards and tags

Redesign preview cards and tags. The idea is to incorporate language icons (#32) to the cards and declutter them as much as possible. Tags should be revamped either in the form of chips or more plain-text alternatives without as many borders. Expertise indicators might be placed in two distinct places as to provide more dense icon-based information, while allowing tags to be decluttered.
Some of these changes will also be applied to the snippet page cards and simple cards for increased design consistency.

Design notes

Category tag + expertise will be added as a visual section to the left of the title to allow easy scanning
Tags will be collapsed as a comma-separated list, as to deemphasize them and declutter the area
The shadow will be toned down to declutter the listing
All of these changes will also be copied to the snippet page
Card padding or individual margins will decrease on mobile to provide a better experience


Can't find code for extracting tables-text examples from wikipedia

Hi,
I am unable to find the code for extracting tables-text examples from wikipedia in the repo. Could you kindly point me to the same.
Thank you.

Hi @rchanumo sadly we do not have that code to share at this point basically because we are using an pre-parsed internal Wikipedia dump as a source. But we have shared the resulting pre-training dataset in https://github.com/google-research/tapas/blob/master/PRETRAIN_DATA.md
But there's nothing special about the logic and I believe there are other public repositories that contain logic to parse directly from a Wikipedia dump, for example there's a pipeline directly from html files here: https://github.com/wenhuchen/WikiTables-WithLinks/blob/master/preprocessing/pipeline.py and there are a few other parsers from the custom Wikimedia format. Let me know if that helps!

Thank you for the pointer @eisenjulian. @wenhuchen's code is sufficient for my use case.


Wrap EOFError as a dbus error

Happens on connection drop/close
Logger: homeassistant.config_entries
Source: components/homekit_controller/connection.py:198
First occurred: 8:53:38 PM (1 occurrences)
Last logged: 8:53:38 PM

Error setting up entry VOCOlinc-VS1-185620 for homekit_controller
Traceback (most recent call last):
  File "/usr/src/homeassistant/homeassistant/config_entries.py", line 365, in async_setup
    result = await component.async_setup_entry(hass, self)
  File "/usr/src/homeassistant/homeassistant/components/homekit_controller/__init__.py", line 41, in async_setup_entry
    await conn.async_setup()
  File "/usr/src/homeassistant/homeassistant/components/homekit_controller/connection.py", line 198, in async_setup
    await self.pairing.async_populate_accessories_state(force_update=True)
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/pairing.py", line 564, in async_populate_accessories_state
    await self._async_populate_accessories_state(force_update)
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/pairing.py", line 111, in _async_wrap
    return await func(self, *args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/client.py", line 75, in _async_wrap
    return await func(*args, **kwargs)
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/pairing.py", line 576, in _async_populate_accessories_state
    await self._populate_accessories_and_characteristics(force_update)
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/pairing.py", line 607, in _populate_accessories_and_characteristics
    await self._async_pair_verify()
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/pairing.py", line 387, in _async_pair_verify
    session_id, derive = await drive_pairing_state_machine(
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/client.py", line 257, in drive_pairing_state_machine
    decoded = await _pairing_char_write(client, char, iid, request)
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/client.py", line 211, in _pairing_char_write
    data = await char_write(client, None, None, handle, iid, next_write)
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/client.py", line 194, in char_write
    pdu_status, data = await ble_request(
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/client.py", line 99, in ble_request
    await _write_pdu(client, encryption_key, opcode, handle, iid, data, tid)
  File "/usr/local/lib/python3.10/site-packages/aiohomekit/controller/ble/client.py", line 126, in _write_pdu
    await client.write_gatt_char(handle, write, True)
  File "/usr/local/lib/python3.10/site-packages/bleak/backends/bluezdbus/client.py", line 695, in write_gatt_char
    reply = await self._bus.call(
  File "/usr/local/lib/python3.10/site-packages/dbus_fast/aio/message_bus.py", line 337, in call
    await future
  File "/usr/local/lib/python3.10/site-packages/dbus_fast/aio/message_bus.py", line 404, in _message_reader
    if self._unmarshaller.unmarshall():
  File "/usr/local/lib/python3.10/site-packages/dbus_fast/_private/unmarshaller.py", line 332, in unmarshall
    self._read_header()
  File "/usr/local/lib/python3.10/site-packages/dbus_fast/_private/unmarshaller.py", line 271, in _read_header
    self.read_to_offset(HEADER_SIGNATURE_SIZE)
  File "/usr/local/lib/python3.10/site-packages/dbus_fast/_private/unmarshaller.py", line 174, in read_to_offset
    raise EOFError()
EOFError

Actually thinking about this, its probably expected and it should be trapped in bleak

looks like there is already an issue for that https://github.com/hbldh/bleak/issues/409

This really isn't a dbus error.  Its a separate error when the dbus get closed unexpectedly.
Probably should be handled downstream

dbus-fast has additional error types besides a d-bus error, it could be worth adding a new one for this that gives a better explanation of what the error actually means and how to recover from it.

I think we could have a named exception that inherits from EOFError that explains the stream disconnected

I hit this issue this weekend in Bleak. I also noticed that if you call bus.call(Message(...)) after the bus socket is disconnected, the call hangs forever. Instead it should raise the same BusDisconnectedError.

This error still shows up with bleak 19.5. I also had a spotty connection due to far distance.

Traceback
Traceback (most recent call last):
  File "/home/ifos/connect.py", line 136, in run_in_background                                                                                task = asyncio.create_task(coro)
  File "/usr/lib/python3.10/asyncio/tasks.py", line 336, in create_task
    loop = events.get_running_loop()
RuntimeError: no running event loop

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/ifos/connect.py", line 532, in <module>
    connect.start()
  File "/home/ifos/connect.py", line 160, in start
    dev.connect()
  File "/home/ifos/connect.py", line 206, in connect
    self.task = run_in_background(self.run_forever())
  File "/home/ifos/connect.py", line 138, in run_in_background
    asyncio.run(coro)
  File "/usr/lib/python3.10/asyncio/runners.py", line 44, in run
    return loop.run_until_complete(main)
  File "/usr/lib/python3.10/asyncio/base_events.py", line 646, in run_until_complete
    return future.result()
  File "/home/ifos/connect.py", line 231, in run_forever
    await self.open_bridges()
  File "/home/ifos/connect.py", line 240, in open_bridges
    await bridge.start(self.bleak_client)
  File "/home/ifos/connect.py", line 485, in start
    await client.start_notify(uuid, new_handler)
  File "/home/ifos/.local/lib/python3.10/site-packages/bleak/__init__.py", line 649, in start_notify
    await self._backend.start_notify(characteristic, wrapped_callback, **kwargs)
  File "/home/ifos/.local/lib/python3.10/site-packages/bleak/backends/bluezdbus/client.py", line 877, in start_notify
    reply = await self._bus.call(
  File "/home/ifos/.local/lib/python3.10/site-packages/dbus_fast/aio/message_bus.py", line 371, in call
    await future
  File "src/dbus_fast/aio/message_reader.py", line 24, in dbus_fast.aio.message_reader.build_message_reader._message_reader
  File "src/dbus_fast/_private/unmarshaller.py", line 659, in dbus_fast._private.unmarshaller.Unmarshaller._unmarshall
  File "src/dbus_fast/_private/unmarshaller.py", line 533, in dbus_fast._private.unmarshaller.Unmarshaller._read_header
  File "src/dbus_fast/_private/unmarshaller.py", line 283, in dbus_fast._private.unmarshaller.Unmarshaller._read_to_pos
EOFError

RuntimeError: no running event loop

This makes me thing the issue is deeper than just wrapping the EOFError.
I haven't had a chance to get back to it yet, but I think https://github.com/hbldh/bleak/pull/1100/commits/9472a10f2324caee532c4cfdc7e9381212931e35 could help with the issue (and hopefully avoid the EOFError altogether).


Transients for HAMT deletion operations

Also some other small bug-fixes and improvements.
FYI @omer-s @harryhk

Codecov Report

Merging #213 (f5ebe48) into master (8155414) will decrease coverage by 0.11%.
The diff coverage is 72.88%.

@@            Coverage Diff             @@
##           master     #213      +/-   ##
==========================================
- Coverage   91.59%   91.48%   -0.12%
==========================================
  Files         114      114
  Lines       10766    10896     +130
==========================================
+ Hits         9861     9968     +107
- Misses        905      928      +23

Impacted Files
Coverage Δ

immer/detail/hamts/node.hpp
86.02% <64.44%> (+0.37%)
:arrow_up:

immer/detail/hamts/champ.hpp
86.46% <68.31%> (-2.23%)
:arrow_down:

immer/map.hpp
97.75% <100.00%> (ø)

immer/map_transient.hpp
100.00% <100.00%> (ø)

immer/set.hpp
100.00% <100.00%> (ø)

immer/set_transient.hpp
100.00% <100.00%> (ø)

test/set_transient/generic.ipp
100.00% <100.00%> (ø)

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