What could cause WinAppDriver to exit immediately after start?

While I am trying to set up WinAppDriver to run as a different user on a CI agent, with the following command: (see my use case here: https://github.com/microsoft/WinAppDriver/issues/1983)
Start-Process -WorkingDirectory "C:\Users\Public" -FilePath "C:\Program Files (x86)\Windows Application Driver\WinAppDriver.exe" -Credential $credential -PassThru

WinAppDriver seems to exit immediately after it starts:
Windows Application Driver listening for requests at: http://<IP_ADDRESS>:4723/

Press ENTER to exit.

Exiting...

To rule out any user account related issues on the CI agent, with the same command but for notepad.exe:
Start-Process -WorkingDirectory "C:\Users\Public" -FilePath "C:\Windows\system32\notepad.exe" -Credential $credential -PassThru

it does not exit the newly started notepad process.
I'm aware that the env on the CI agent could be complicated and there might be something forcing the WinAppDriver process to exit. While it is hard to imagine what that something could be, I'm wondering if anyone else has similar experience or knows in what circumstances WinAppDriver could print out "Existing..." and exits?
Also, is the actual code that build WinAppDriver.exe in this repo? I was trying to search "Existing..." but did not find any related code in this repo?

You need to use double slash in the path for winappdriver

Thanks @anunay1 , double slash doesn't seem to be the cause of exiting. I managed to work it around by running another C# WinForm app which starts WinAppDriver once it starts. This way I can start the WinForm app as the non-admin user and then WinAppDriver inherits the runas user and does not exit, although I still didn't figure out why WinAppDriver exits immediately when it is directly started by Start-Process.

I'm having the same problem and this issue also seems to address this: https://github.com/microsoft/WinAppDriver/issues/588


"Mostly-mass-storage" indexes

On the persisting indexes to disk issue, it was mentioned (https://github.com/arangodb/arangodb/issues/209#issuecomment-193838232) that "mostly-mass-storage" indexes would require future work.
I just wanted to create an issue for tracking and discussion of that feature, since I couldn't find one.

This will be part of the upcomming arangodb 3.2 release. Please follow the release anouncements; I will close this issue now.


chore(BUX-641): remove unneeded config param for frontend in start.sh

Pull Request Checklist

[x] 📖 I created my PR using provided  : CODE_STANDARDS
[x] 📖 I have read the short Code of Conduct: CODE_OF_CONDUCT
[ ] 🏠 I tested my changes locally.
[x] ✅ I have provided tests for my changes.
[x] 📝 I have used conventional commits.
[x] 📗 I have updated any related documentation.
[x] 💾 PR was issued based on the Github or Jira issue.

testing 🧪

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Add headerComponent prop for the datatable columns

This PR adds possibility to render custom header for the DataTable columns.
Example from storybook:

In the future leave out build from the PR -> easier to merge features to master if there are multiple feature branches (that'd have different build files each).


Fix build and populate index in parallel

CC @eisengrau

Some rough measurements:
[INFO] [src/index/update.rs:27] Library index update took 322.893 seconds

# rayon within a directory
[INFO] [src/index/update.rs:28] Library index update took 172.079 seconds

# rayon both within a directory and across directories
[INFO] [src/index/update.rs:28] Library index update took 49.357 seconds

I tried to drop the caches before the last measurement, but I'm not sure it worked (ZFS on Linux). Tested on a Celeron J1900.

Left one minor question before merging, but this is a great change! Very promising numbers - although I assume it might be especially beneficial on the lower end CPU.

I think it's beneficial on slower drives because you get more IO operations at once. Even mechanical drives are fastest at 8 concurrent IOs or so.
On my CPU this still doesn't go above 50-80% overall usage (over the four coures), even with ZFS trying to uncompress the files.

Hello,
So yesterday I added my collection of about 200k mp3 files at the time of opening #85. Unforunately after a couple of hours it 'timed out' so it idexed just a few folders of it. I clikced on scan now again, once I restarted the container, it is the same CPU usage as yesterday, around 3% max. The music collection is on ZFS on linux (LZ4 compression) with an i5-4590.
Maybe this will fix it. I'm eagerly waiting for a new build. :)

Even if you closed the browser, the scan should have ran in the background (it runs periodically anyway).

ZFS on linux

:smile:

It's definately doing something:

I'll get back and try to find some logs once it stops. Does the polaris binary generate any, or at the moment it just runs in the background once launched?

teddybear

:smile:

I'll get back and try to find some logs once it stops. Does the polaris binary generate any, or at the moment it just runs in the background once launched?

It doesn't write to a file, but to console. On my distro I see them with journalctl and in Docker docker logs probably works, but I'm not sure what Debian and LXC do.

There's no logs for files scanned successfully
There is a log entry at the end of each scan, you've been using it for your benchmarks @lnicola :D

On Linux, running without the -f flag makes the output go to a polaris.log file under your $XDG_CACHE_HOME directory. Running with -f makes the process not daemonize and output to console.

As a datapoint @eisengrau, I run Polaris on a Raspberry Pi 3 with about 80k songs on a USB HDD and the initial indexing (cold cache) takes about 10-15 minutes IIRC.

@agersant I'm curious what effect this PR has on that.

Ok, I ran polaris -f, I could now see what has stopped the scanning:
10:09:26 [ERROR] [src/index/mod.rs:90] Error while updating index: Invalid directory path
Could be directories/file names with accented/invalid characters?

I think I fixed an issue causing it to give up on some errors, can you try with the latest version?

Should I git clone and recompile again, since previously I just unpacked the latest archive and used that.

Clone, cargo build --release and take the binary from target/release/polaris.


AssertionError in calling render_vis

Tensorflow 1.14.0
Numpy 1.17.4
the following stack just pop-up:
https://pastebin.com/mL4TUMxz
since your code calls on TF to get input Tensor, eval it and use it as input for show, and you use numpy to see the rank and stack and is nan and so on ... the bug may be somewhere there.
Also, i noticed you dont put kwargs in render_vis, in such a fashion that i cant pass w keyword arg and make the visualization bigger.
Still wondering why not to use matplotlib with jupyter ...
ps: i finally decided to switch to Lucid to do deep dream and other Artistic things, because it seems to be much more evolved than the initial deep dream code ...

will try tf 1.15., however the numpy 1.16 version of the tutorial may crash another libs to downgrade.

I cant get ride of the assertion error even with 0.3.8.

It sounds like you are running into numerical stability issues while visualizing your model. This could be caused by many issues -- for example, the objective you are visualizing could be exploding, your model may have unstable gradients, and much more.
Please keep in mind that lucid is research code.

I will close this issue since seems to be the same mentioned earlier, so we keep the discussion in the other issue.


fix: guard against reviews without reviewassignments. Fixes #3906.

Also fixes a typo that broke things but no-one complained. I wonder if we can find such typos programmatically yet?


Create new logger instead of reusing root logger

The current behaviour sets the log level of the root python logger to DEBUG which effects any other package also using this logger.
This change creates a new logger and leaves the log level at the default

hehe it was supposed to be removed a lot of iterations ago
thank you!


All commits have the end sequence in them

All of my commits end up having the <|im_end|> be visible.

In previous version, I use unstable model name. I just fixed it


feat: add google analytics config

This PR adds google analytics configuration to extension.
⚠ Still missing useful events.

Added the following events:

set_value: when user sets a value
copy_value: when a user copies a value
number_of_keys: number of keys that each user is saving
page_view:

Extension page: with the app version

extension_error

unhandled exceptions: exception reasons

As discussed offline, added the following metrics

view_value: when user sees value
delete_item: when users deletes an item
invalid_form: when the user doesn't fill correctly the form
number_of_keys: number of keys that each user is saving, grouping by type

@Marianarodrigues7 LMK if there's something else we should add in this scope 👍🏻


Community Detail "Explore" selection

Community detail pages have an option to "explore" more
Hard coded or based on a point? (Seems to be hard coded).

https://www.commonmoves.com/communities/winthrop


[core] Update @azure/core-tracing to 1.0.0

Now that @opentelemetry/api GA'd at 1.0.0 we can bump our own
core-tracing package to 1.0.0 as well.
This means we can finally GA @azure/core-tracing!
Reminder: not all packages are on the latest @opentelemetry/api... those that depend on @azure/core-rest-pipeline cannot be
upgraded yet.

I feel great about updating OT to 1.0, and I think I'm okay with getting core-tracing finally out of preview too.
@ramya-rao-a @chradek do you feel good about this?

we could put out another preview of core-tracing in July and then just do a pure version bump to GA it in august if that feels better?

I agree on doing GA for core-tracing later in August. We can use the time in July to see what else we want to change before GA


[HOT-FIX] Fix compilation (caused by 0131142d98b191f6cc112d383aa10582a3ac35bf)

I am merging it to branch-1.4 to fix compilation.

Merged.


Update installation instructions

Since the vim plugin is now sperate from the core racer, it is no longer nessessary to build racer after updating the plugin.
Also I've added the configuration for vim-plug.

Thanks @Eisfreak7 !


Replace snappy with cramjam

@taylorfturner please assign reviewers

Thanks for your patience @gliptak

please review

https://github.com/capitalone/synthetic-data/pull/346

@gliptak rebase onto dev and I'll approve

rebase or update branch on this and I'll approve @gliptak

green for your review @taylorfturner

@micdavis @ksneab7 please review/approve

@gliptak are you able to restore your cramjam1 branch?
This change fails tests locally on this command DATAPROFILER_SEED=0 python3 -m unittest discover -p "test*.py"
First issues is dataprofiler/dataprofiler/tests/test_dp_logging.py", line 27, in test_default_verbosity     self.assertEqual( AssertionError: 20 != 30
Second issue is dataprofiler/dataprofiler/tests/test_data_profiler.py", line 32, in test_set_seed     self.assertEqual(dp.settings._seed, None) AssertionError: 0 != None
main testing works locally and the only diff between main and dev is this PR

Checking out f8b3e5dbd4b76f0ecc291911ace9e8e21cf1ecb1 and running tests on that commit (one commit prior to this PR) ensures that tests did run on dev locally at that point in the history

Glad to ultimately do cramjam + python 3.11 -- these tests will just need to pass locally as well as remote

@taylorfturner restored branch
as the build was green for this PR, might that indicate that different library versions where used?

potentially -- I tried a bunch of different scenarios and wasn't able to find a setup where the above two tests passed locally

I did reproduce the fail locally and still cannot reproduce in GHA
the one difference I observed is that local is Python 3.10.12 while GHA is `CPython (3.10.13)


Villages are not removed from waiting list if troops are recruited or added by item

Fixed on TWOverflow/FarmOverflow#11


 Is it possible to change the resolution of the browser view and the web page rendered? In the demo project I've tried changing the height/width of the browserview component to 2560x1440, as well as the height and width of the ovr overlay external surface, but the webpage still renders as if the resolution is extremely small.  Thanks

Did you manage to accomplish this? How did you do it?


Add example tests for blocks

Description of the Change
To encourage testing React components, this PR adds basic tests for example block. There are two tests:

A snapshot test.
A test that a changing the rich text input calls setAttributes

These are good first tests and show some concepts.
Alternate Designs
I installed @testing-library/react in the theme. There are alternatives for example Enzyme that I could have used.
Benefits
Blocks start with useable tests
Possible Drawbacks
Not everyone is familiar with React testing. We have to keep @testing-library up to date.
Verification Process
I need to fix/ workaround #26 before testing this.

How did you verify that all new functionality works as expected?
How did you verify that all changed functionality works as expected?
How did you verify that the change has not introduced any regressions?

Checklist:

[ ] I have read the CONTRIBUTING document.
[ ] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[ ] I have updated the documentation accordingly.
[ ] I have added tests to cover my change.
[ ] All new and existing tests passed.

Applicable Issues
#27
Changelog Entry
ADDED: Example Jest unit tests in example block.

Hey @Shelob9, this is very cool. How did you get seeping the fact that most of the components that get used in the Blocks Edit React component are actually externals that jest won't have access to?
Since we want to avoid having to include our own version of all the @wordpress packages in our themes and plugins.
That's always what I find most challenging.

@fabiankaegy Thanks.

How did you get seeping the fact that most of the components that get used in the Blocks Edit React component are actually externals that jest won't have access to?

Good question. So, I havn't gotten there yet, got stuck trying to figure out #26  . In the past, I've made the WordPress dependency extraction webpack plugin conditional, so it doesn't run during testing. I've also imported the scripts in jest's setup script and used that to set window.wp.

I did a similar PR a while ago https://github.com/10up/wp-scaffold/pull/15/files
@Shelob9 The fact that pretty much all components are externals is the reason I wanted to build a jest-gutenberg package that would render the block-editor in jsdom so that we don't have to mock things cc @fabiankaegy
While I like the idea of adding example tests to the scaffold I think that in practice, engineers will get stuck if they have to mock everything.


Fix podman installation

Description of the change:
Motivation for the change:
Reviewer Checklist

[ ] Implementation matches the proposed design, or proposal is updated to match implementation
[ ] Sufficient unit test coverage
[ ] Sufficient end-to-end test coverage
[ ] Docs updated or added to /docs
[ ] Commit messages sensible and descriptive

Codecov Report

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The diff coverage is n/a.

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Installing postgresql client is unnecessary

Is there a reason why this is installed into the container?
XNAT itself doesn't need it, as it uses JDBC to connect to postgresql via a JAR file that's bundled into the WAR. I guess it could be handy for debugging, but I guess you could install it yourself as a once-off.
Happy to submit a PR if you agree.

closed via #29


Cleanup delete / add

Add distribution codename to url_filename Fix #55
remove file from pool when delete
remove package when NOT preserve-version
Add logging with logger
Add a -d``--debug option

Hi! Checking in on status of this PR, and if I could offer to help move it forward?

Closing in favor of #59, but trying to update it to resolve merge conflcits.


QuantumPlugin: CSS Clean removing css because of a rouge comment?

I'm seeing some strange CSS outputs when using QuantumPlugin.
I'm importing a compiled CSS file from another node module, and I have noticed that part of my resulting CSS bundle is commented out, and thus is removed via the cleancss (or uglify) functionality of fusebox.
I have managed to find the problem to be the last line of the node module's CSS file which contains the sourceMappingURL as:
/*# sourceMappingURL=react-draft-wysiwyg.css.map*/

But in my compiled (production) CSS it looks like this
body {
  background: red;
}

/*
.foo {
  color: blue;
}

Notice the loan comment - /* The only way I have managed to fix this,
Comparing this compiled (dev) CSS, it looks like this:
body {
  background: red;
}

/*# sourceMappingURL=/css-sourcemaps/01441df7f.map */
.foo {
  color: blue;
}

My QuantumPlugin configuration is a follows
QuantumPlugin({
    bakeApiIntoBundle: 'vendor',
    treeshake: true,
    uglify: true,
    css: {clean: true}
})

I'm also using the SassPlugin although I don't think its a problem with the Sass Plugin.
I was wondering if the QuantumPlugin is getting confused with the source map inline comment, and consequently is not correctly removing the entire of the sourceMapUrl?
My current work around is to ensure the import of the module's CSS file is always done last, and thus won't cause any problems, however I don't like this as it will require use of overriding css with !important.
Checklist

[x] You have removed the .fusebox folder in your project root
[x] Removed node_modules, (re-installed everything)
[x] Started the bundling process again.
[x] Read the documentation on your subject here -> fuse-box.org

@LukeHackett hang in there, there is a massive update coming. Follow twitter to be the first one to try ;-) I will bear in mind the issue.

Closed as related to v3.x which is no longer supported.


Preventing focal length refinement

Hi,
is it possible to prevent pycolmap from refining the focal length specified in the database during incremental_mapping? Using the GUI I would do that by deselecting refine_focal_length
Thanks!

PR https://github.com/colmap/pycolmap/pull/56 adds support for IncrementalMapperOptions, does this work for you?
 incremental_mapping(
    database_path, images_path, output_path, dict(ba_refine_focal_length=False),
)

Hi,
great, thanks! In order to work with the updated version I need to build pycolmap from source, right?
I'm working on a remote cluster with no root access, so I pip installed pycolmap, which avoided me to install COLMAP. Is there an alternative way to update it?
Thanks!

You can download the latest wheel from our CI: https://github.com/colmap/pycolmap/actions/runs/2017977100
Pick the right wheel, unzip, and pip install file.whl


Deploy production frontend on release & correctly time staging deployment

Fixes
Fixes #1557 by @sarayourfriend
Description

Deploys https://search-production.openverse.engineering whenever a release is cut in this repository. At least hopefully! We'll need to see if the GHCR configuration actually works for releases and if it will successfully trigger the "deploy-production" workflow to completion with the release tag. Unfortunately I'm not aware of any way to test this functionality other than by merging it and see if it works with a test release.
I also noticed that the staging deployment and the GHCR push to the main tag have a race condition. I've fixed that in this PR by only running the staging deployment after the GHCR image is uploaded after a push to the main branch.
Also: I've removed the old push_prod and push_staging workflows that were used to push images to ECR. We no longer use ECR, so those workflows will fail until they're removed.
Also: this adds the version.json requested by the Nginx sidecar issue. I think we can safely close that issue for now and in the future look into whether we want to use Nginx to serve static files. We don't currently do that, and the version.json endpoint isn't worth the extra complexity for now.
Testing Instructions

I think just merge and see how it goes. Note that the existing GHCR push should still work for this branch. You can see I did a bunch of test commits to get the action changes verified as working, in particular the tag extraction for the RELEASE build arg.
To test the build arg, checkout this branch and run:
docker build . --build-arg RELEASE=super-sweet-release-sha-1234abcd -t openverse-frontend:latest

Run the generated image and verify that you can reach the /version.json endpoint at http://localhost:8443/version.json:
docker run -p 8443:8443/tcp openverse-frontend:latest

Checklist

[x] My pull request has a descriptive title (not a vague title like Update index.md).
[x] My pull request targets the default branch of the repository (main) or a parent feature branch.
[x] My commit messages follow best practices.
[x] My code follows the established code style of the repository.
[N/A] I added or updated tests for the changes I made (if applicable).
[N/A] I added or updated documentation (if applicable).
[x] I tried running the project locally and verified that there are no visible errors.

Developer Certificate of Origin

Developer Certificate of Origin
Developer Certificate of Origin
Version 1.1

Copyright (C) 2004, 2006 The Linux Foundation and its contributors.
1 Letterman Drive
Suite D4700
San Francisco, CA, 94129

Everyone is permitted to copy and distribute verbatim copies of this
license document, but changing it is not allowed.

Developer's Certificate of Origin 1.1

By making a contribution to this project, I certify that:

(a) The contribution was created in whole or in part by me and I
    have the right to submit it under the open source license
    indicated in the file; or

(b) The contribution is based upon previous work that, to the best
    of my knowledge, is covered under an appropriate open source
    license and I have the right under that license to submit that
    work with modifications, whether created in whole or in part
    by me, under the same open source license (unless I am
    permitted to submit under a different license), as indicated
    in the file; or

(c) The contribution was provided directly to me by some other
    person who certified (a), (b) or (c) and I have not modified
    it.

(d) I understand and agree that this project and the contribution
    are public and that a record of the contribution (including all
    personal information I submit with it, including my sign-off) is
    maintained indefinitely and may be redistributed consistent with
    this project or the open source license(s) involved.

Let's try it! Regarding rollbacks, how were we going to handle those? Was it manual runs of the GitHub workflow with a tag input field?

Right! I forgot about that. I'll create a new "rollback production" workflow that can be dispatched with a ref input. It'll just call  through to the production-frontend-deploy action with the input ref.

I wanted to test the version route locally after building the dockerfile with something like docker build . -t openverse-frontend:latest --build-arg RELEASE=whatever but the Dockerfile doesn't build on an M1 mac.

I wanted to test the version route locally after building the dockerfile with something like docker build . -t openverse-frontend:latest --build-arg RELEASE=whatever but the Dockerfile doesn't build on an M1 mac.

Ah, this is a known issue that we decided to accept. It has to do with some permissions issue with the COPY commands, IIRC.
I've pushed an update to change the chmod to chown. @zackkrida can you try again?

I'm going to merge this as it's working in CI and for me locally, the worst case scenario is that it still doesn't build on an M1, but I think it should fix it. If not we can open another issue if we still wish to address this.


sklearn compatibility with feature_names_out

Expected Behavior
The behaviour of get_feature_names_out should be the same as for sklearn
Actual Behavior an explanation in doc.
At the moment feature_names_out_ attribute is set in fit and returned by get_feature_names_out function. In sklearn the get_feature_names_out function does not just return the values set in fit, but determines the output feature names from given input feature names if possible.
Examples

Target-like encoders encode the features one to one and hence return the same columns as output as the input.
Hashing encoding knows how many columns it will produce (and their names) based on n_components
For BaseN and OneHot encoding the column count depends on the number of distinct values. Hence a not fitted error must be raised.

I'd like to discuss this idea a little with the community. Please add some Pros and Cons of this approach. I'm sure I'm missing something
Pros

streamlined behaviour with sklearn. This might lead to better testing and less issues in some corner cases (pipelines etc)
allows you to get output column names without having to fit an encoder (for some encoders)

Cons

quite some work: all encoders need to be changed
most encoders are 1-1 anyway or would raise a not fitted error.

I agree that aligning with the updated sklearn version 1.2 would be very helpful.
In goes without saying that when using pipelines with multiple transformers, it is useful to have a df at the output end with features traceable to the input features.
The main benefit occurs downstream when the transformed dfs are passed on to predictors. For example, I have a situation currently wherein both XGBT and LGBM can take categorical features directly as an input without having to encode them. They rely on the categorical dtype of the column in the df to identify such features. Without a df output from the transformers in the pipeline with properly labelled columns, it is unnecessarily complicated if not virtually impossible to change the dtype to categorical within the pipeline before it goes on to the predictor.
I was very excited by this new feature in sklearn 1.2 hoping it would deal with it, but not realising that 3rd party transformers also have to play ball and support the api.
I therefore look forward to this being implemented soon!
Narayan

Yes, I agree with all comments. In fact I am playing with the TargetEncoder and I found that it causes problems when integrated in a Pipeline or in a ColumnTransformer of sklearn, because get_feature_names_out will be called with a parameter and you get this kind of error:
BaseEncoder.get_feature_names_out() takes 1 positional argument but 2 were given

After a more careful review, I think this more work than expected. The reason is that, if you want to include a category encoder in a pipeline, unless the encoder is in an initial position, the input that it will receive is a numpy ndarray, not a pandas dataframe. And so, the column names won't exist (they will default to integers from 0 to n-1). And this is not a good behaviour.
That's why you cannot rely on the names of the inputs you see during fitting, because they might not exist!
I think that, unfortunately, each category encoder should define its own method for this, because depending on the EncodingRelation they will have different behaviour. So that's much more work than expected...
Well, in the case of ONE_TO_ONE relationships it will be straightforward.
I have made a PR with the partial fix, to see if the main contributors of the project like the approach and we can continue the work.

Hi Jaime,
thanks for your work. When exactly does the pipeline example fail? I think we have tests for fit and transform methods using pipelines. But you call pipeline.get_feature_name_out to get the error, right?
I agree that it is a lot of work. Basically at the moment output feature names are calculated on the fly when fitting whereas in sklearn the logic to determine output feature names is in the get_feature_names_out function. Hence we need to look at every single encoder and understand what it does to obtain output colnames.

I think that, unfortunately, each category encoder should define its own method for this

This is exactly the point, and also the way sklearn does it.
But still I think it is worth the effort and as a maintainer I'd love to see it implemented. I tagged this issue as a good-first-issue not because it is easy (yet do-able) but working on it will give a good overview of the project and will enable a lot of future commits.

Thanks a lot!! I will share with you a google colab notebook to explain
more carefully the issue. Let me prepare it and I will post the link here
tomorrow.
El jue., 23 de febrero de 2023 18:54, PaulWestenthanner <
@.***> escribió:

Hi Jaime,
thanks for your work. When exactly does the pipeline example fail? I think
we have tests for fit and transform methods using pipelines. But you call
pipeline.get_feature_name_out to get the error, right?
I agree that it is a lot of work. Basically at the moment output feature
names are calculated on the fly when fitting whereas in sklearn the logic
to determine output feature names is in the get_feature_names_out
function. Hence we need to look at every single encoder and understand what
it does to obtain output colnames.
I think that, unfortunately, each category encoder should define its own
method for this
This is exactly the point, and also the way sklearn does it.
But still I think it is worth the effort and as a maintainer I'd love to
see it implemented. I tagged this issue as a good-first-issue not because
it is easy (yet do-able) but working on it will give a good overview of the
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Ok, here is the colab notebook explaining the issue and a way to a solution (I hope it makes sense!).
https://colab.research.google.com/drive/1lJJvXyAOoG9MBtNiH2qSTrqbzZtEPTeB?usp=sharing
As a side comment, I think in general the fact that inputs and outputs of sklearn objects can be either dataframes or np.arrays is very problematic and leads to lots of edge cases and needs for workarounds... But for me keeping track of the columns and how they transform during the preprocessing is very valuable.

Hi,
thanks for sharing the set_output docs. I think this is exactly what we need and should go for. Also the other Mixin mentioned there could be useful.
Regarding tests I agree that this is a good testing setup. I think we're missing tests for pipelines altogether, so we should really introduce them.
As for your questions:

Good question. I think I'd like to keep it. Our implementation does provide some features that the sklearn version does not have (i.e. handle_missing and handle_unkown = indicator and handle_unkown = return_nan and also drop_invariant). The handle_unkown=indicator might actually make problems in get_feature_names_out since it will add columns during predict time. On the other hand the sklearn version has the sparse option which is a nice feature that we miss. So it might make sense to reconsider this for the future. But for the time being I'd keep it.
No, this should probably be changed to use the get_feature_names_out function. But I think we probably cannot avoid the transform (although it is a little ugly) since for finding invariant columns we need to do a transform

Ok, good. Yes, I will try to follow as much as possible the sklearn path. So there are two things to adapt, that I will try to include in the PR:

get_feature_names_out (using Mixins when possible).
set_output. This change was available in sklearn since version 1.2.0. I have a couple of questions regarding this:

Should we modify the API of category_encoders? I guess it makes a lot of sense to remove arguments like return_df, because this should be handled by using set_output as all sklearn estimators now.
But, if so, probably this will imply a new version of the library. Is that ok?
I am not sure how this is configured at the level of tests. For example, if I include tests using set_output, those tests should only be performed for the new version of the library. Do I need to include this kind of configuration in the tox.ini file, or anywhere? Sorry for the question, I am not familiar with this kind of things.

Anyway, the second question is a technical point, I think I can start and we can adjust later. It's more important for me to be clear if we want to change the API (regarding the return_df input).

Perfect!
I agree that we should remove the return_df argument in the long run and replace it by set_output. However, since this is a breaking change and is actually the default option we can't replace it without a transition period. So for the time being I think we should introduce a future warning. I think a lot of user rely on getting a dataframe as output and they'd need to adjust on their ends.
Currently we're on version 2.6.0. If we only release a future warning but keep return_df I'd release your PR as version 2.6.1, and then maybe in 2.7 or even 2.8 (depending on how frequent we'll release) we could drop the return_df. I'd like to give the users at least a couple of months to adopt.
Regarding tests we're actually not using the tox file in our pipeline. Our pipeline will just test different versions of python and the latest versions of pandas/numpy/sklearn not all versions specified in the requirements file. So if we rely on set_output we'd basically need to bump the sklearn version to 1.2 which is rather new. This is also basically a trade-off between being fast paced and ensuring stability/compatibility where as a maintainer I favour the latter.
Considering this, we should maybe just introduce a future warning for the return_df parameter and wait to replace the parameter.
Alternatively, we could change what the return_df parameter does: Instead of returning a df in the base encoder we could call self.set_output(transform="pandas") in the __init__ function of the encoder. This would be a compromise, keeping backwards compatibility (and the argument) but already removing any custom logic and hence aligning more with sklearn.
What do you think?

Thank you. Yes, this could be a good idea...
However, to be honest, I am feeling less and less comfortable and confident with this PR. I started early this morning preparing the new test suites, following the order of the encoders, and I panicked when I discovered how entangled this library is with having pandas dataframes as inputs and outputs. I am not saying that I don't understand this rationale, but it's a big (very big) change from how sklearn treats inputs and outputs. In sklearn, inputs and outputs are expected to be either pandas dataframes or numpy ndarray. Both options are allowed. And this is reflected (among other things) in the parameters of the transformers. For example, for the OrdinalEncoder of sklearn, if you wish to specify the order in which you want to encode the categories, you can use this attribute:
categories: ‘auto’ or a list of array-like, default=’auto’
        Categories (unique values) per feature:
        ‘auto’ : Determine categories automatically from the training data.
        list : categories[i] holds the categories expected in the ith column. The passed categories should not mix strings and numeric values, and should be sorted in case of numeric values.

However, to achieve similiar functionality with the OrdinalEncoder of category_encoders, you have to use the mapping parameter:
mapping: list of dicts
        a mapping of class to label to use for the encoding, optional.
        the dict contains the keys 'col' and 'mapping'.
        the value of 'col' should be the feature name.
        the value of 'mapping' should be a dictionary or pd.Series of 'original_label' to 'encoded_label'.
        example mapping: [
            {'col': 'col1', 'mapping': {None: 0, 'a': 1, 'b': 2}},
            {'col': 'col2', 'mapping': {None: 0, 'x': 1, 'y': 2}}
        ]

The big difference is that category_encoders is using the names of the columns, instead of the order in which they appear, hence it's implicitely expecting a pandas dataframe as input. I know that if the input of fit is a numpy ndarray, it's converted into a dataframe, but this is a hack that plays (IMHO) against the composability of the transformer. As showed in the Colab example, when the transformer is part of a Pipeline or a ColumnTransformer, if a previous transformer outputs a numpy ndarray, then this is what will be received by the fit method. And the hack of converting X to a pandas dataframe will make the mapping incorrect and create subtle bugs when the encoder is part of a complex object. I have created an example showing that problem.
And it's not so easy to get around this problem because the mapping is not only a parameter that can be used by the user to specify how to map the categories to the new values, but it's also used quite a lot internally. Honestly I don't know how to get around this problem... I think this asks for a big redesign of the whole library and I don't feel capable of doing that.
The assumption of the input being a dataframe is everywhere!
So I think there are two possible paths:

Redesign the whole library removing the implicit assumption of X being a dataframe. This will be a big breaking change. In the long term it's maybe the best solution (for achieving the bigest compatibility with sklearn and the way it works) and it will give more clarity, but it will be a hard path. I don't feel capable of doing that.
Use the new set_output API of sklearn to ensure that, even if the CategoryEncoder is part of a Pipeline, all estimators will ouptut pandas dataframes. I am talking about doing this:

In utils.BaseEncoder.fit():
from sklearn import set_config
set_config(transform_output="pandas")

In utils.BaseEncoder.transform():
from sklearn import set_config
set_config(transform_output="pandas")

Well, before setting the config, we should retrieve the current config value and restore it in the end, and returning an output value according to the config and to the return_df parameter. But this can be achieved easily by converting the dataframe to a numpy ndarray in the end. This might be ugly, but it will be the simplest solution given the current design.
What do you think?

I have tested the second solution and it works ok. All tests pass without issues and only small modifications of the codebase were needed. If setting this configuration of sklearn is not that ugly, I think this solution could be very practical.
Please, check the PR

You're right, this library internally works with dataframes.
However I'd like to keep the behaviour that you can input arrays and lists and also not necessarily get a df back (return_df=False).
I've just been thinking about columns transformers: You need them if you only want to modify some columns and leave others untouched. This is basically what all encoders do! So I do not see a use-case where it makes sense to use a column transformer over integrating the encoder in a pipeline.
In case of using Pipelines you can manually set the previous step to output dataframes
categorical_preprocessor = Pipeline(
    steps=[
        ("imputation_constant", SimpleImputer(fill_value="missing", strategy="constant").set_output(transform='pandas')),
        ("ordinal", OrdinalEncoder(mapping=[{'col': 'col_a', 'mapping': {'a': 2, 'b': 1, 'c': 3}}])),
    ]
)

This is not very pretty but works. However I think if we can make the existing thing work, we should rather do this (and maybe add some docs on how to use with pipellines) rather than refactoring all of the code because we don't have (or at least I don't have) the resources for this.
Nevertheless we can include the functionality to get_feature_names_out right? even if we do not achieve full compatiblity with sklearn? It will be a step in the right direction.
Thanks for pointing all of this out. Great work so far! I'm also not super happy with the way it is ^^

Great stuff you've been doing. I'll review your code probably on Friday or the weekend, since I'll be a little busy for the rest of the week. Your support (and thorough knowledge about pipelines) is greatly appreciated

Thanks a lot for your kind words. It's been a pleasure. :)

Did #398 leave anything from this issue to do?  (If so, can you summarize it, maybe spinning off a new issue; and if not, close the issue?)

Hi Ben, I've summarized the open point in #406 and will close this one


KVM entry failure

Hi!.
This command
$ HERMIT_ISLE=uhyve HERMIT_CPUS=4 HERMIT_MEM=1G HERMIT_VERBOSE=1 bin/proxy x86_64-hermit/extra/benchmarks/stream
generates three errors
KVM: receive shutdown command
proxy: 0:KVM: entry failure: hw_entry_failure_reason=0x80000021
proxy: KVM: unhandled KVM_EXIT_IO / KVM_EXIT_MMIO at port 0x0

Hello,
what branch do you use? Do you get any error message from the kernel?

Hello.
I am using default branch, master. I get these message from the kernel:
[21510.136101] perf interrupt took too long (5026 > 5000), lowering kernel.perf_event_max_sample_rate to 25000
[   12.124842] kvm: VM_EXIT_LOAD_IA32_PERF_GLOBAL_CTRL does not work properly. Using workaround

Hi!
I am getting the same errors when using more than one core. Interestingly it fails most of the time but not always. I also got the following error a few times:
proxy: KVM: ioctl KVM_SET_SREGS failed: Invalid argument
Actually it seems like there is no mechanism to make sure that the boot cpu has initialized the static sregs variable before the other cpus set their sregs.

I never received such kind of failure. Which Linux kernel do you use?

I am using Linux kernel 3.16.0-4-amd64.

@bguala Please test the new version in the master branch. Do you still receive the error?
If you use the Debian packages, please remove all packages and reinstall the packages.

Stefan,
In this moment, I can't compile the new version of HermitCore. The command $ make produces the follow error message:
Install the project...
-- Install configuration: ""
[ 52%] Completed 'arch_x86_loader'
[ 52%] Built target arch_x86_loader
[ 52%] Built target arch_x86_kernel_asm
[ 52%] Built target libkern
[ 52%] Built target kernel
[ 52%] Built target drivers
[ 52%] Built target mm
[ 52%] Built target lwip
elfedit: Error: Unknown OSABI: Standalone
arch/x86_64/CMakeFiles/kernel-entry.asm.obj.dir/build.make:57: fallo en las instrucciones para el objetivo 'arch/x86_64/CMakeFiles/kernel-entry.asm.obj'
make[2]: *** [arch/x86_64/CMakeFiles/kernel-entry.asm.obj] Error 1
CMakeFiles/Makefile2:806: fallo en las instrucciones para el objetivo 'arch/x86_64/CMakeFiles/kernel-entry.asm.obj.dir/all'
make[1]: *** [arch/x86_64/CMakeFiles/kernel-entry.asm.obj.dir/all] Error 2
Makefile:149: fallo en las instrucciones para el objetivo 'all'
make: *** [all] Error 2
Previously, I ran $ sudo apt-get dist-upgrade, for update Debian packages. Nasm, Make and Binutils are in their most recent version.

We changed the value in the elf header (OSABI). For some unknown reasons, a dist-upgrade isn't enough. Please try following commands.

sudo apt-get remove binutils-hermit newlib-hermit pte-hermit gcc-hermit libomp-hermit libhermit
sudo apt-get update
sudo apt-get install binutils-hermit newlib-hermit pte-hermit gcc-hermit libomp-hermit libhermit

Now, the command $ cmake .. generates errors, they are :
**-- The C compiler identification is unknown
-- The CXX compiler identification is unknown
-- The Fortran compiler identification is unknown
/opt/hermit/libexec/gcc/x86_64-hermit/6.3.0/cc1: error while loading shared libraries: libmpfr.so.6: cannot open shared object file: No such file or directory
-- Check for working C compiler: /opt/hermit/bin/x86_64-hermit-gcc
-- Check for working C compiler: /opt/hermit/bin/x86_64-hermit-gcc -- broken
CMake Error at cmake/cmake-3.7.2-Linux-x86_64/share/cmake-3.7/Modules/CMakeTestCCompiler.cmake:51 (message):
The C compiler "/opt/hermit/bin/x86_64-hermit-gcc" is not able to compile a
simple test program.
It fails with the following output:
Change Dir: /home/bguala/Escritorio/Hermit3/libhermit/build/CMakeFiles/CMakeTmp
Run Build Command:"/usr/bin/make" "cmTC_2bb77/fast"
/usr/bin/make -f CMakeFiles/cmTC_2bb77.dir/build.make
CMakeFiles/cmTC_2bb77.dir/build
make[1]: se entra en el directorio
'/home/bguala/Escritorio/Hermit3/libhermit/build/CMakeFiles/CMakeTmp'
Building C object CMakeFiles/cmTC_2bb77.dir/testCCompiler.c.obj
/opt/hermit/bin/x86_64-hermit-gcc -o
CMakeFiles/cmTC_2bb77.dir/testCCompiler.c.obj -c
/home/bguala/Escritorio/Hermit3/libhermit/build/CMakeFiles/CMakeTmp/testCCompiler.c
/opt/hermit/libexec/gcc/x86_64-hermit/6.3.0/cc1: error while loading shared
libraries: libmpfr.so.6: cannot open shared object file: No such file or
directory
CMakeFiles/cmTC_2bb77.dir/build.make:65: fallo en las instrucciones para el
objetivo 'CMakeFiles/cmTC_2bb77.dir/testCCompiler.c.obj'
make[1]: *** [CMakeFiles/cmTC_2bb77.dir/testCCompiler.c.obj] Error 1
make[1]: se sale del directorio
'/home/bguala/Escritorio/Hermit3/libhermit/build/CMakeFiles/CMakeTmp'
Makefile:126: fallo en las instrucciones para el objetivo 'cmTC_2bb77/fast'
make: *** [cmTC_2bb77/fast] Error 2**
Is libmpfr the problem??. I'm not sure, I have libmpfr4 v3.1.4-1 installed.
I re-installed the follow packages correctly:
binutils-hermit, newlib-hermit, pte-hermit, gcc-hermit, libomp-hermit and libhermit.
Source: deb http://dl.bintray.com/hermitcore/ubuntu bionic main.

Ubuntu based on Debian, but they use different version of libmpfr. I recognize it on my Debian systems. I want to build "native" Debian packages. But I don't find the time.
Currently, the easiest way to use HermitCore on a Debian system, it the usage of my scripts at https://github.com/hermitcore/hermit-toolchain
It need some time, but it works...

The command $ ./toolchain.sh x86_64-hermit /home/bguala/Escritorio/hermit produces:
Makefile:372: fallo en las instrucciones para el objetivo 'lib_a-fix_grouping.o'
make[4]: *** [lib_a-fix_grouping.o] Error 127
make[4]: *** Se espera a que terminen otras tareas....
  Alto.
make: *** No hay ninguna regla para construir el objetivo 'install'.  Alto.
/home/bguala/.local/share/Trash/files/hermit-toolchain.2/hermit-toolchain/build
./toolchain.sh: línea 111: cmake: no se encontró la orden
make: *** No se especificó ningún objetivo y no se encontró ningún makefile.  Alto.
make: *** No hay ninguna regla para construir el objetivo 'install'.  Alto.

It doesn't work. The command $./toolchain x86_64-hermit /home/usr/hermit produces:
make: *** [all] Error 2
/ home / bguala / Desktop / HermitToolchain / hermit-toolchain / build
./toolchain.sh: line 102: cmake: order not found
In toolchain.sh the line 102 is:
cmake -DLIBOMP_ARCH=$TARGET_SHORT -DCMAKE_C_COMPILER=$TARGET-gcc -DCMAKE_CXX_COMPILER=$TARGET-g++ -DCMAKE_INSTALL_PREFIX=$PREFIX/$TARGET -DCMAKE_TRY_COMPILE_TARGET_TYPE=STATIC_LIBRARY -DHERMIT=1 -DLIBOMP_ENABLE_SHARED=OFF -DLIBOMP_FORTRAN_MODULES=OFF -DLIBOMP_OMPT_SUPPORT=OFF -DOPENMP_ENABLE_LIBOMPTARGET=OFF ../../openmp
TARGET is x86_64-hermit.
The build process generates "build" directory in hermit-toolchain. "build" contains hermit (is libhermit), within "hermit" I ran:

$ . cmake/local-cmake.sh
$ mkdir build
$ cd build
$ cmake ..
-DTOOLCHAIN_DIR_BIN=/home/usr/hermit/bin

but, I get:
The CMAKE_C_COMPILER:
/home/usr/hermit/bin/x86_64-hermit-gcc -->  is not a full path to an existing compiler tool.
The CMAKE_CXX_COMPILER:
/home/usr/hermit/bin/x86_64-hermit-g++ --> is not a full path to an existing compiler tool.
The CMAKE_Fortran_COMPILER:
/home/usr/hermit/bin/x86_64-hermit-gfortran --> is not a full path to an existing compiler tool.
The CMAKE_Go_COMPILER:
/home/usr/hermit/bin/x86_64-hermit-gccgo --> is not a full path to an existing compiler tool.
What is the full path for compiler tool???./home/usr/hermit/bin???.

Hm, which version of cmake do you use?

cmake 3.7.2

I am a little bit confused. I think the the OpenMP library doesn't work on your systems. Please test, if following command is working in the build director of libhermit.

cmake -DTOOLCHAIN_BIN_DIR=/home/user/hermit/bin -DCMAKE_INSTALL_PREFIX=/home/user/hermit ..
make

I looked in readme of the OpenMP library and found following note

This repository requires CMake v2.8.0 or later.

That is new for me. We switched to a new OpenMP version and we didn't recognize these changes.
Please download and install cmake from https://cmake.org/files/v3.8/ Afterwards, you should remove the directories openmp and final from the build\tmpdirectory and start the script again.

I haven't got any "hermit" directory in /home/bguala.

Ok, in this case delete the directory build\tmp in the directory of the git repository hermit-toolchain. Afterwards, try following commands:

mkdir /home/bguala/hermit
./toolchain x86_64-hermit /home/bguala/hermit

I ran following commands:

export PATH=/home/bguala/hermit/bin:$PATH
mkdir /home/bguala/hermit
./toolchain x86_64-hermit /home/bguala/hermit

but I get these messages:

-- Looking for pthread.h - not found
CMake Error at /home/bguala/Escritorio/HermitToolchain/hermit-toolchain/build/hermit/cmake/cmake-3.7.2-Linux-x86_64/share/cmake-3.7/Modules/FindPackageHandleStandardArgs.cmake:138 (message):
Could NOT find Threads (missing: Threads_FOUND)
CMake Error at cmake/cmake-3.7.2-Linux-x86_64/share/cmake-3.7/Modules/CMakeTestCCompiler.cmake:51 (message):
The C compiler "/home/bguala/hermit/bin/x86_64-hermit-gcc" is not able to
compile a simple test program.

Some libomp test failed, for example:
LIBOMP_HAVE_WNO_SELF_ASSIGN_FLAG
LIBOMP_HAVE_FINI_FLAG
I haven't got "x_86_64-hermit" directory in /home/bguala/hermit.

Ok, at the weekend I will create valid debian packets for you...

I try to build packages for Debian "stretch". A few packages are already published at https://bintray.com/hermitcore/debian
However, I am not able to build the final stage of the compiler. You find the log file at https://travis-ci.org/hermitcore/gcc/jobs/418020895
I have no idea why the build process was pending. @jbreitbart Do you have an idea? I don't have any problems on Fedora, CentOS and Ubuntu.

@stlankes My guess is that travis kills the job if it does not print anything for a 10 minutes and we suppress everything during the built on stdout. On Ubuntu we see warnings being printed on stderr, but Debian does not print any warnings and the job gets killed. I have created
https://github.com/hermitcore/gcc/pull/1
which will fill stdout :smile: If that works fine, we should re-enable bintray for debian and check if there is a more feasible way to get some output on stdout.

@bguala It take same time, but the packages are now available. Please use following repository:

$ echo "deb [trusted=yes] https://dl.bintray.com/hermitcore/debian stretch main" | sudo tee -a /etc/apt/sources.list
$ sudo apt-get -qq update
$ sudo apt-get install binutils-hermit newlib-hermit pte-hermit gcc-hermit libomp-hermit libhermit

I think that the problem is solved and close the issue. If the problem still exists, please reopen the issue.


Fix exception when header contains : in the value

For example MY_HEADER:{"param":"val"} would throw an exception

LGTM


[ALLUXIO-2743] Fix MultiUfsMountIntegrationTest with hadoop profiles

https://alluxio.atlassian.net/browse/ALLUXIO-2743
This PR aims to fix the build on hadoop-{1/2} profile

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/Alluxio-Pull-Request-Builder/14997/
Test PASSed.


Use GitHub's ‘releases’ system instead of versioning build-products (i.e. the zip-file)

Just a thought. (=

Might want to file it over at https://github.com/Afforess/Marathon, he's been doing a good job at maintaining this. It's the official fork now.


adds create_transaction_tag method

Quick followup from last PR. Adds a method for creating a transaction tag.

Awesome, thanks for the quick 👀 . I updated the comments to be more descriptive.


should add an isNaN() method

There should be a built-in "isNaN()" method to check if any of the color space values are invalid, just a basic function

There…is? Two in fact: isNaN() and Number.isNaN()

I’m gonna go ahead and close this, but if I minderstood what you were proposing, feel free to reopen!


Add a build step to check the Xcode project for absolute paths

These break the build on both the server and on subsequent checkouts: we should try to catch this early in automated builds.

Won't fix.


Fix DCGM_EXPORTER_LISTEN value of dcmg-exporter manifest file #94

Bug fix for https://github.com/NVIDIA/gpu-monitoring-tools/issues/94.

Answered on gitlab :) !


[openshift/packit-service.yml.j2] lower resources requests/limits

see https://github.com/packit-service/packit-service/pull/596
I'll merge this next week after we see how the above PR works in production.

Deployed to stg


Allow Drush version to be configurable.

When developing on the latest dev branch of Drupal (8.4.x) the symfony version is updated. This latest version does not work with Drush 8.
It would be great if the Drush version is configurable, so we could optionally use Drush 9 in the container.

Nowadays, drush usually comes with drupal itself like drupal console. So, if your project is composer-based you should have drush under vendor/ dir.

We now have drush launcher that will automatically use drush that comes with your composer-based project.


Upgrade to Kubernetes 1.17.0

Switch to Go Modules
Remove vendor directory

I'm pretty sure this is exactly what I just ran into. For anyone else trying to figure out what's happening, in kubernetes 1.17.0 deployments moved from beta into app/v1 From my troubleshooting, it looks like the operator fails to create the cluster with the following logs:
time="2020-01-14T22:21:59Z" level=error msg="Could not create client deployment: the server could not find the requested resource"
time="2020-01-14T22:21:59Z" level=error msg="Error creating client deployment the server could not find the requested resource"
time="2020-01-14T22:21:59Z" level=error msg="the server could not find the requested resource"

Just trying to add some context in case someone else runs across the same thing.
👍 to @cedbossneo for the PR, and hope to see it merged in the near future!

That would be my guess. In 1.16 you can reenable the disabled apis. I'm guessing you can in 1.17. You might be able to do that to verify its that issue.

Hello everyone, I'm new with helm charts, how can I use the code from this PR?
Since this repo hasn't been updated for a long time...
Can I consume the code from the branch directly?
like: helm repo add es-operator https://raw.githubusercontent.com/cedbossneo/elasticsearch-operator/master/charts/
Any help is appreciated! thanks

No, you'd have to compile the operator from the source branch.  The resource types in the code are incompatible with k8s v1.17.
I've done just that - but am not yet 100% successful.  Will update if things change.

Ok. This is now working for me with kubernetes v1.17.7: https://github.com/nikogura/elasticsearch-operator.
It builds on the excellent work by @cedbossneo ( thank you very much sir!).   I've updated the charts, and the dockerfile so that it can build locally if need be.
I'll PR my changes back to @cedbossneo for now, and to this repo when this PR is reviewed.
Please let me know if I can be of any help!  Love this project.


Allowing tf-controller to apply to terraform manifest targeting resources

Hello,
I'm moving some CD pipelines to tf-controller and I miss the option to allow me applying Terraform manifests targeting resources.
Let me share HashiCorp documentation about targeting resources
I think it could be interesting adding this feature as a field in TerraformSpec documented in this link
Best regards,
Marc

Hi @mcortinas
I think we have .spec.targets to support this feature:
https://github.com/weaveworks/tf-controller/pull/311


Automated Package Upgrade

:tada: This PR is included in version 5.0.553 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


Digital asset metadata

What kind of change does this PR introduce (bug fix, feature, docs update, ...)?
Adds LSP4 metadata class and upload functions

@frozeman Yes docs are automatically moved to docs page. You can see the changes in this PR here: https://github.com/lukso-network/docs/pull/104.
It hasn't been merged yet as these changes reflect an unreleased version of the library so doesn't make sense to publish the docs for it yet. It needs to be updated so it only pulls in docs from the released version


Vertical screen indicator (near screen icon) sometimes disappears

When using other applications/programs on mac and then go back to wallet vertical screen indicator disappears.
It happened few times on Testnet 5.2 and BeamX. I couldn't find the exact ways to reproduce it.

Correct view

won't fix


integration tests

Codecov Report

:exclamation: No coverage uploaded for pull request base (reliable_table_copy@81adf90). Click here to learn what that means.
The diff coverage is n/a.

@@                  Coverage Diff                   @@
##             reliable_table_copy    #5632   +/-   ##
======================================================
  Coverage                       ?   82.85%
  Complexity                     ?    11762
======================================================
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Cannot use hex strings or named matplotlib colors with DataFrame.plot

I was going to put this on SO but I think it might belong here instead:
I have a pandas DataFrame where I want to plot each column as a line with the same color. This might sound useless but I am showing groups of lines from certain selections of the DataFrame. The only problem is it appears that the DataFrame.plot method does not accept any matplotlib hex strings or named colors in the color kwarg.
A trivial example:
pd.DataFrame([range(10),range(10)]).plot(color='#008000')

gives a blank subplot with no errors, however,
pd.DataFrame([range(10),range(10)]).plot(color='g')

gives the expected result. To me this seems like a bug considering that color='g' works but not its hex string equivalent. The same issue occurs when trying to use a named matplotlib color like color='lightgray'. This does however work when using Series.plot or DataFrame.plot with one column or if a list of hex strings or named colors are given with length equal to the number of columns as in,
pd.DataFrame([range(10),range(10)]).plot(color=['#008000']*2)

Looks like we parser color='bgr' color line 1 blue, line 2 green, line 3 red. It tries to do that here when it sees a list of characters, but '#' isn't a valid color.
I'd be open to a pull request to support this.


Update/Add cfg80211 and mac80211 kernel subsystems and mac80211_hwsim module

Tool information

Tool name: cfg80211, mac80211, and mac80211_hwsim
Tool license: GPL
Add or update? Add
Desired version: latest
Approximate size:
If this is an add request:

Brief description of tool: 802.11 subsystem and testing tool for simulated testing of the 802.11 networking stack
URL for tool's homepage: https://www.kernel.org/doc/html/v4.14/driver-api/80211/index.html
Provide a basic test case to validate the tool's functionality: modprobe mac80211_hwsim

Area for Triage: Testing and code coverage
Question, Bug, or Feature?: Feature
Virtual environments affected

[ ] macOS 10.15
[x] Ubuntu 16.04 LTS
[x] Ubuntu 18.04 LTS
[x] Ubuntu 20.04 LTS
[ ] Windows Server 2016 R2
[ ] Windows Server 2019

Can this tool be installed during the build?
No, it has to be enabled in the kernel.
Tool installation time in runtime
Unknown
Are you willing to submit a PR?
Yes if can be pointed in the right direction.

Hi, @davidgoogle
Could you provide steps to install these cfg80211, mac80211, and mac80211_hwsim?

They would have to be compiled into the Ubuntu kernel on the image that is used for the azure instances. I believe the compile options to be enabled are CONFIG_CFG80211, CONFIG_MAC80211, and CONFIG_MAC80211_HWSIM.

I believe the compile options to be enabled are CONFIG_CFG80211, CONFIG_MAC80211, and CONFIG_MAC80211_HWSIM.

@andy-mishechkin

Thank you for feature request.
But we wouldn't like to perform this request for now. Modifying kernel is dangerous change that can bring maintenance issues on long term. This request covers very specific scenarios and we wouldn't like to take the risk since we need to be sure that our images are stable and healthy.

Hi,
I still have this issue and I need the mac80211_hswim kernel module. Sadly it can't even be installed through linux-modules-extra-uname -r since the Azure build, in contrast to the generic one, doesn't include that module. What is the proposed solution?


Added event plugin/swAjaxVariant/onHistoryChanged

1. Why is this change necessary?
Makes it possbile to register actions which should occur after history did change
2. What does this change do, exactly?
Adds a jquery event with $.publish
6. Checklist

[ ] I have written tests and verified that they fail without my change
[x] I have squashed any insignificant commits
[x] This change has comments for package types, values, functions, and non-obvious lines of code
[x] I have read the contribution requirements and fulfil them.

Hello,
thank you for creating this pull request.
I have opened an issue on our Issue Tracker for you. See the issue link: https://issues.shopware.com/issues/SW-23162
Please use this issue to track the state of your pull request.

Hi @danielwolf1, thank you very much for your contribution! 💙


Cannot find module '/node_modules/tailwindcss/plugin' when working with @formkit/tailwindcss

Reproduction
https://stackblitz.com/edit/formkit-nuxt-tailwind
Describe the bug
I'm trying to use @formkit/tailwindcss with FormKit and Nuxt 3 like explained in the docs. But I get the following error when I run dev:
Error [ERR_MODULE_NOT_FOUND]: Cannot find module '/home/projects/formkit-nuxt-tailwind/node_modules/tailwindcss/plugin' imported from<EMAIL_ADDRESS>Did you mean to import tailwindcss/plugin.js?
    at NodeError.get (https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:286334)
    at __node_internal_ (https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:1492)
    at new NodeError (https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:2995)
    at https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:367454
    at https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:367501
    at Loader.defaultResolve [as _resolve] (https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:367507)
    at Loader.resolve (https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:1019940)
    at Loader.getModuleJob (https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:1021996)
    at https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:6:734578
    at _0x52ceac.link (https://formkit-nuxt-tailwind.w.staticblitz.com/blitz.5bca79c80956550a0ee18f24bf5b874e18bb8626.js:15:232691) {
  code: 'ERR_MODULE_NOT_FOUND'
}
[vite dev] Error loading external<EMAIL_ADDRESS>  at async eval (file://./.nuxt/nitro/index.mjs:160:24)
  at async renderMiddleware (file://./.nuxt/nitro/index.mjs:215:20)
  at async handle (file://./node_modules/h3/dist/index.mjs:299:19)

I also tried using it with @nuxtjs/tailwindcss but got the same error.
After quick research I found a similar issue at @tailwindcss/forms. But none of the proposed solution fixed the problem.
Can someone provide a working sandbox for with Nuxt and @formkit/tailwindcss?
Environment
• Tested on Stackblitz, macOS 12.2 and Windows 10
• @formkit/nuxt v1.0.0-beta.5

For now, try to update formkit to the @next of @formkit/tailwindcss version, I think it was fixed at #134.

Sorry I overlooked that this is a clear duplicate of #134


Support type-narrowing via discriminated unions

Type-narrowing via discriminated unions is a useful TypeScript feature. I believe it's not supported via Glint:
interface Circle {
  kind: "circle";
  radius: number;
}

interface Square {
  kind: "square";
  sideLength: number;
}

type Shape = Circle | Square;

export default class Foo extends Component<...> {
  public declare shape: Shape;

  public get foo(): number {
    return this.shape.kind === 'circle' ? this.shape.radius : this.shape.sideLength;
  }
}

{{#if (eq this.shape.kind "circle")}}
  {{log this.shape.radius}}
{{/if}}

The foo getter compiles just fine as the TypeScript compiler does it's job, however the log in the HBS gives an error:
error TS2339: Property 'radius' does not exist on type 'Shape'.
  Property 'radius' does not exist on type 'Square'.

6   {{log this.shape.radius}}
                     ~~~~~~

It would be nice to be able to do this. Not sure it's possible though. At the very least a "built-in" eq helper must be defined and Glint should be hard-coded to know about it I guess.

This is dependent the Equality Operators RFC actually landing. Until then we can't assume anything about what eq means in a template, so this kind of type narrowing isn't possible.

It's been more than a year since this feature request was opened and nearly 3(!) years since the equality operators RFC was first posted.
Is there some way we can get this as an opt-in, i.e. assert to glint that the eq helper is defined as === ?
Not having the ability to discriminate unions in templates leaves the choice of either (a) adding a ton of boilerplate in the component backing class or controller to deal with all the various cases, or (b) just telling glint to ignore many templates and hoping for the best.

It's been more than a year since this feature request was opened and nearly 3(!) years since the equality operators RFC was first posted.

And the RFC hasn't been implemented in that time, so my comment above still holds 🙂
I'd love to see built-in equality operators land in Ember, and I'm as impatient as I expect you are for that to happen!

Is there some way we can get this as an opt-in, i.e. assert to glint that the eq helper is defined as === ?

Glint's maintainers have limited capacity, and we need to carefully prioritize when considering what additions and improvements we spent that capacity on. Since the RFC hasn't been implemented, other issues have taken higher priority for us, and will likely continue to for some time given our constraints. If the equality operators were to land in an Ember release, though, that would certainly change the calculus.
In the meantime, I'd be happy to review a PR contributing the ability to opt in to native semantics for equality operators; it just isn't something we have the capacity to do ourselves at the expense of other work at present.

@dfreeman glad to hear that you're open to having an opt-in to the new semantics
I found it pretty easy to modify template-to-typescript.ts to add this functionality, but I'm unsure about the best way to implement a configuration option for adding eq and neq to INLINE_KEYWORDS.
Do you have any guidance or opinions on this? Thanks!

@bwbuchanan I'm currently overhauling how we handle special forms like hash and yield internally to address #374 and some of the points raised in #411, and I think that should make setting up the equality and comparison operators much easier! Stay tuned once that lands, hopefully in the next day or two 🙂

@bwbuchanan I'm currently overhauling how we handle special forms like hash and yield internally to address #374 and some of the points raised in #411, and I think that should make setting up the equality and comparison operators much easier! Stay tuned once that lands, hopefully in the next day or two 🙂

Nice, I see you just merged #453 . I will have a go at rebasing my changes and making up a PR.

@dfreeman What do you think is right for the option name? includeEqualityOperators? allowEqualityOperators?
Or would it be better to have something like
{
  includeOptionalHelpers: ['equalityOperators', 'logicalOperators', 'numericComparisonOperators']
}

Are {{eq}} and {{neq}} required to be imported from @ember/helper in strict mode or are they built-in globals?
RFC 560 is not clear about this (though it describes the helpers as "built-in") but RFC 496 would seem to suggest that anything not explicitly on its list of built-ins must be imported.
CC @chriskrycho @cibernox

I think what I'd suggest instead is directly accepting special forms config in a similar way to how the GlimmerX environment accepts an additionalGlobals option.
Then users could configure their environment to opt into the specific special forms they want to enable, e.g.:
"glint": {
  "environment": {
    "ember-loose" {
      "additionalSpecialForms": {
        "globals" {
          "eq": "===",
          "not-eq": "!==",
          "and": "&&",
          "or": "||",
          // ...
        }
      }
    },
    "ember-template-imports": {
      "additionalSpecialForms": {
        "imports": {
          "ember-truth-helpers/helpers/eq": { "default": "===" },
          "ember-truth-helpers/helpers/not-eq": { "default": "!==" },
          // ...
        }
      }
    }
  }
}

We can of course bikeshed on things like the appropriate names for these new special forms, and whether ember-loose needs that intermediary globals key since all its special forms are global, but overall this approach would give us similar flexibility to additionalGlobals to account for ways that users may customize their template environment either with polyfills or their own custom preprocessing.
It's a bit more boilerplate than a simple flag would be, but I think that's ok for opting into an unstable feature of the platform, particularly given that things like import paths for strict mode haven't been established yet.

Ah, I see you left a comment about import paths while I was writing that up—see above for how I think we might sidestep that particular issue within Glint 😄

PR filed! Once this is good enough to merge, I'll follow up with one to support logical and numeric comparison operators from RFCs 561 and 562.

Great, thank you! I'll aim to give it a look this weekend, or Monday at the latest.

I'm going to open a PR for logical operators (RFC 562). I believe that numeric comparison operators (RFC 561) do not require any glint special forms to implement and plain helper function typedefs should suffice.


documentation replace iroh-ctl to iroh

Add more clarity to the binaries that have been replaced and are no longer up to date
Example : iroh-ctl

[x] Update quickstart.md iroh-ctl replace to iroh
[x] Update DEVELOPERS.md iroh-ctl replace to iroh

closed by #445. Thanks @OnsagerHe!


Error in fetchDependency.ps1 while downloading CMake

After executing a .\vcpkg install <package> command, I get the error:

Could not run:
'C:/temp/vcpkg/scripts/fetchDependency.ps1'
An error description follows that points to an illegal method call on a null pointer in file C:\temp\vcpkg\scripts\VcpkgPowershellUtils.ps1, line 180.

I had a look at the vcpkgExtractFile function in fetchDependency.ps1
My machine runs Windows 7 and Pscx is not installed. So I have no Expand-Archive command available and the function will use the "shell.application" object which does not seem to accept forward slashes in folder paths.
In my configuration, the issue was fixed by replacing the forward slash with a backslash at line 155 of file fetchDependency.ps1 (in variable $destinationPartial)

Thanks for reporting!


Adding requirements file, updating README

Changes:

Removed textwrap, as it's in the standard library for Python 2.7+.
Ran Main.py multiple times, and noticed the missing module errors that were produced. Installed those modules and then created the requirements.txt file using pip freeze.
Added PyYAML that was missing from the README file and added instructions on how to easily install the module dependencies.

After installing the dependencies, the tool started successfully.

Thanks @gtseres for the PR


Missing H.264 and VC-1 capabilities on Tahiti chipset

The issue: when using AMDVLK instead of RADV, H.264 and VC-1 hardware decoding/encoding capabilities are not recognized.
System: Arch linux (5.0 kernel), Mesa 18.3, latest available AMDVLK build (r62...)
Chipset in question: Radeon R9 280
Notes: I had to use radeon.si_support=0 amdgpu.si_support=1 to force-load amdvlk. Don't know how that affects the decoding support.
Attached are the vainfo and vdpauinfo outputs for both drivers.
vainfo_amdvlk.txt
vainfo_radeon.txt
vdpauinfo_amdvlk.txt
vdpauinfo_radeon.txt

I realise I might have made a mistake. This issue lies with the amdgpu rather than with the amdvlk driver, doesn't it? I apologize, if it does. Hours of googling made my brain soft.

Hi @mflayer , Vulkan doesn't support video encoding/decoding. vainfo should report the video capability according to the video driver, such as radeonsi_drv_video.so.


Try out lyon 1.0

https://nical.github.io/posts/lyon-1-0.html  (Congrats on the release, if maintainers ever happen to see this)

The variable width strokes could be an interesting experiment for roads that change width in the middle. (The direct math in PolyLine::make_polygons probably wouldn't be too hard to extend to do this, but lyon also has bezier curves. CC @BudgieInWA as FYI, I know you've been interested in using those)

The path sampler sounds like it could possibly replace PolyLine::dist_along. I may want to try out the acceleration structure in bus_spotting particularly

Blocked on https://github.com/nical/lyon/issues/806

:fire:


[New API] : Chatbot API 🤖

Brief Description 🤓

The Chatbot API provides a conversational interface for interacting with users.
It uses natural language processing to understand and respond to user queries.
This API aims to enhance user engagement by providing intelligent responses and handling a variety of user inputs effectively.

How will you develop it?🤩
This Chatbot API uses a combination of basic web technologies HTML, CSS, Javascript to create a MVP chatbot.

Frontend Design: Developed by using HTML and styled using CSS. It features an input field for user queries and a message area where interactions are displayed.

JavaScript Functionality: The core of the chatbot is powered by JavaScript, which handles:

Input Processing: Simplifies user input by removing non-alphanumeric characters and unnecessary spaces.
Response Generation: Matches user inputs against predefined prompts and provides relevant replies. It includes specialized responses for topics like COVID-19 and fallback responses for unexpected inputs.
Chat Management: Dynamically updates the chat interface to display both user messages and bot responses, simulating real-time conversation.

Speech Synthesis: Utilizes the Web Speech API to convert text responses into spoken words, adding an auditory dimension to the interaction.

Deployment
Yes
Select the open source program you are contributing to
Other
Code of Conduct

[X] I follow CONTRIBUTING GUIDELINES of this project.

Greetings @SanskarSinghiit🎀 ! , We are excited to have you dive into another issue with us!🚀
Your involvement in our project has been invaluable, and we're confident that your skills and insights will help us conquer this challenge😇.  Use command /gssoc24 to self assign the issue.  This issue represents an exciting opportunity for us to improve and enhance our project, and we are thrilled to have you on board.
We request you to follow CONTRIBUTING GUIDELINES.
Looking for your PR soon!
In case of any issues, you can contact us on Discord.❣

/gssoc24


Fix arguments in value_transformation

Exchange origin and upstream arguments in value_transformation function

@syamashiro28,
To my mind, it is more reasonable to call BRCA_TPM as 'origin' when transforming TPM values.
I fixed arguments in this function and description in README.
Please do let me know if this change can influence other files.


Executing 'yarn build' command fails on Ubuntu

sys version: Ubuntu-22.04
When i execute 'yarn build' at root dir. it stopped here for a long time.

Maybe it's because the configuration of this machine is too low.


Replace unicode characters with ASCII

Unicode characters in source code screw up some build systems, like Chromium.

googlebot: oops<EMAIL_ADDRESS>is my chromium identity. this is also me.


Why not use the resenet API in keras

Isn't it easy  to load the keras inception net instead of writing it manually. I was just curious.

这是来自QQ邮箱的假期自动回复邮件。你好，我最近正在休假中，无法亲自回复你的邮件。我将在假期结束后，尽快给你回复。


erase option is missing in latest asciiflow diagrams

Hi,
earlier versions had erase option.
is it possible to include erase option in this latest version?
Select and Move option is not sufficient in some cases to edit the existing diagram.
Thanks and regards,
Adishesh

Hi Lewish,
i tried select and backspace/delete key, delete is not working.
for now i switched to https://asciiflow.com/legacy/
Thanks and regards,
Adishesh

Hi - Using the select tool and then pressing delete or backspace should do exactly the same as the old erase tool

This worked. But I've spent at least 2-3 minutes figuring this out and for finding this issue. Maybe the UX could be improved somehow.


fluxcd: 0.13.4 -> 0.14.0

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://github.com/fluxcd/flux2/releases.
meta.description for fluxcd is: "Open and extensible continuous delivery solution for Kubernetes"
meta.homepage for fluxcd is: "https://fluxcd.io"
meta.changelog for fluxcd is: ""
Updates performed

Golang update

To inspect upstream changes

Release on GitHub

Compare changes on GitHub

Impact

Checks done (click to expand)

built on NixOS

The tests defined in passthru.tests, if any, passed

/nix/store/gl96qv1sxn0v1aj91slv0w3b40plxb4a-fluxcd-0.14.0/bin/flux passed the binary check.

1 of 1 passed binary check by having a zero exit code.

1 of 1 passed binary check by having the new version present in output.

found 0.14.0 with grep in /nix/store/gl96qv1sxn0v1aj91slv0w3b40plxb4a-fluxcd-0.14.0

found 0.14.0 in filename of file in /nix/store/gl96qv1sxn0v1aj91slv0w3b40plxb4a-fluxcd-0.14.0

directory tree listing: https://gist.github.com/eddac6873d50e776a019fa65aa276b98

du listing: https://gist.github.com/5643e9f8ebc1b20427196cbca9b26a4e

Rebuild report (if merged into master) (click to expand)

4 total rebuild path(s)

1 package rebuild(s)

1 x86_64-linux rebuild(s)
1 i686-linux rebuild(s)
1 x86_64-darwin rebuild(s)
1 aarch64-linux rebuild(s)

First fifty rebuilds by attrpath
fluxcd

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/gl96qv1sxn0v1aj91slv0w3b40plxb4a-fluxcd-0.14.0 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A fluxcd https://github.com/r-ryantm/nixpkgs/archive/291dd7b8d5c4566f28e17f78cb922d15aa92126d.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/gl96qv1sxn0v1aj91slv0w3b40plxb4a-fluxcd-0.14.0
ls -la /nix/store/gl96qv1sxn0v1aj91slv0w3b40plxb4a-fluxcd-0.14.0/bin

Pre-merge build results
We have automatically built all packages that will get rebuilt due to
this change.
This gives evidence on whether the upgrade will break dependent packages.
Note sometimes packages show up as failed to build independent of the
change, simply because they are already broken on the target branch.
Result of nixpkgs-review run on x86_64-linux 1

1 package built:

fluxcd

Maintainer pings
cc @jlesquembre @kalbasit for testing.

Result of nixpkgs-review pr 124726 run on x86_64-darwin 1

1 package built:

fluxcd

Superseded https://github.com/NixOS/nixpkgs/pull/127819


Nadim 02 session storage

This Pr solves the following trello card: https://trello.com/c/sUDS7Hm2/60-store-user-choices-in-session

Its good practise to keep data-testid's unique, in the snapshot for helpPage because we render many cards they all have the same test id. This means when you press the button it flips every single card, not just one or two.


OSOD print(model) produces wrong output.

max_iterations = 1

model = tc.one_shot_object_detector.create(starter_images, 'label', background_images, max_iterations=max_iterations)
print(model)

produces
OneShotObjectDetector

which is supposed to be something like this:
Class                                    : OneShotObjectDetector

Model summary
-------------
Number of classes                        : 1
Input image shape                        : (3, 416, 416)

Synthetic data summary
----------------------
Number of synthetically generated examples : 5
Number of synthetically generated bounding boxes : 5

Training summary
----------------
Training time                            : 9s
Training iterations                      : 1
Training epochs                          : 6
Final loss (specific to model)           : 3.4134

@nickjong not sure this should be p1 or not.


Release: gulpfile.js not found

Environment

Server -VSTS
https://citylcdevelopment.visualstudio.com/jquery-accordion
build #20171027.6
release 11

Issue Description
cannot find gulpfile.js...following tutorial here:: SharePoint SpFX CI DEployment
[Include task name(s), screenshots and any other relevant details]
Failing on Upload to SharePoint
Error logs
see attached
ReleaseLogs_11.zip

so I got it to find the gulpfile, however still getting an error when hitting the upload to sharepoint task
2017-10-27T20:27:39.9898608Z ##[section]Starting: Upload to SharePoint Document Library
2017-10-27T20:27:39.9898608Z ==============================================================================
2017-10-27T20:27:39.9898608Z Task         : Gulp
2017-10-27T20:27:39.9898608Z Description  : Node.js streaming task based build system
2017-10-27T20:27:39.9898608Z Version      : 0.5.31
2017-10-27T20:27:39.9898608Z Author       : Microsoft Corporation
2017-10-27T20:27:39.9898608Z Help         : More Information
2017-10-27T20:27:39.9898608Z ==============================================================================
2017-10-27T20:27:40.7574856Z [command]C:\NPM\Modules\gulp.cmd upload-to-sharepoint --gulpfile d:\a\r1\a${System.DefaultWorkingDirectory}\build\release\gulpfile.js --ship --username ${username} --password ${password} --tenant ${tenant} --cdnSite ${cdnSite} --cdnLib ${cdnLib}
2017-10-27T20:27:48.6861031Z [20:27:48] Working directory changed to d:\a\r1\a${System.DefaultWorkingDirectory}\build\release
2017-10-27T20:27:51.2077273Z Build target: SHIP
2017-10-27T20:27:51.2737239Z [20:27:51] Using gulpfile d:\a\r1\a${System.DefaultWorkingDirectory}\build\release\gulpfile.js
2017-10-27T20:27:51.2737239Z [20:27:51] Starting gulp
2017-10-27T20:27:51.2767234Z [20:27:51] Starting 'upload-to-sharepoint'...
2017-10-27T20:27:51.3227212Z [20:27:51] 'upload-to-sharepoint' errored after 11 ms
2017-10-27T20:27:51.3227212Z [20:27:51]
2017-10-27T20:27:51.7598801Z [20:27:51] ==================[ Finished ]==================
2017-10-27T20:27:52.2626421Z [20:27:52] Project jqueryui-accordion version: 0.0.1
2017-10-27T20:27:52.2636417Z [20:27:52] Build tools version: 2.10.2
2017-10-27T20:27:52.2646419Z [20:27:52] Node version: v6.10.0
2017-10-27T20:27:52.2656419Z [20:27:52] Total duration: 3.23 s
2017-10-27T20:27:52.2956406Z ##[error]Gulp failed with error: C:\NPM\Modules\gulp.cmd failed with return code: 1

I know this issue is old, but I can't replicate it. Working fine with multiple SPFx projects for me.

Closing as this has gone stale. It looks like the issue has since been fixed anyways


Displaying time only when no initial data

Is there a way to display time only when no initial data is in the form?
The white example has a time field. If you remove the data, click outside to clear the time picker and click back it shows a calendar instead of a time picker.
I see on your main page demo it also has a time picker which has data-type="time" set, but that doesn't seem to be working for me to force the input to be time picker only.

I figured it out. Looked at the source on the main demo page. You used readValue function.
readValue: function(element) {
  if (!element.value && element.getAttribute('data-type') === 'time') { // initial time if empty
    return new Date().toTimeString().split(' ')[0]; // triggers default behavior
  }

  return element.value; // triggers default behavior
}


Add new default location for conmon

This will allow overriding the CRI-O version of conmon in our packages (and elsewhere, if we need to). No change on systems without a binary at that path, we'll just fall through to the next possible path (the old default)

LGTM

@baude @umohnani8 PTAL

does anything need to change in the test suite for conmon location?

@baude I don't think so since conmon can be  passed in via the command line.

@baude Good catch, I added a check for the new location to the E2E tests

LGTM

@rh-atomic-bot r+


WebSQL shim

for backwards compatibility with non indexeddb browsers (altho websql has now been deprecated)

No need to shim, PouchDB handles all this stuff.


[PowerToys Run]: Screen Reader only announce 'edit 1' for 'Maximum number of results' edit field.

Microsoft PowerToys version
"0.41.3"
Running as admin

[ ] Yes

Area(s) with issue?
PowerToys Run
Steps to reproduce
Test Environment:
OS: Windows 10 Version Dev
App version: 0.41.1
App name: PowerToys
Screen Reader: Narrator
Tool: Accessibility Insight for Windows
Repro Steps:

Launch 'PowerToys' application.
Turn on Narrator.
In PowerToys tab, Navigate to 'Maximum numbers of Result' button and observe the issue.
Then Navigate to edit field in Scan mode and Verify that Screen Reader read the label in scan mode or not.

User Impact: .-> Priority 1
Visual and Screen Reader user are impacted here as edit field name is not defined as result they will not able to know the Purpose of edit field.
Guidelines Reference:
https://www.w3.org/WAI/WCAG21/Understanding/name-role-value
Attachments:
Screen Reader only announce 'edit 1' for 'Maximum number of results' edit field..zip

✔ Expected Behavior
Screen Reader should announce 'Maximum number of results edit 1' for 'Maximum number of results' edit field and Screen Reader user also able to read it in Scan mode.
❌ Actual Behavior
Screen Reader only announce 'edit 1' for 'Maximum number of results' edit field.
Note Issue: In Scan mode, Screen Reader didn't read label of 'Maximum number of results' edit field when user navigate using 'up/down' arrow key.
Other Software
No response

Resolved with the release of v0.43.0.


default governor configuration with TLP is incorrect

The CPU scaling governor settings applied when TLP is enabled defaults to "performance" because relevant options are commented out.
Ideally, it should default to "powersave" as already reasoned in the configuration file (/etc/default/tlp) with the last two lines uncommented.
# Select a CPU frequency scaling governor.
# Intel Core i processor with intel_pstate driver:
#   powersave(*), performance.
# Older hardware with acpi-cpufreq driver:
#   ondemand(*), powersave, performance, conservative, schedutil.
# (*) is recommended.
# Hint: use tlp-stat -p to show the active driver and available governors.
# Important:
#   powersave for intel_pstate and ondemand for acpi-cpufreq are power
#   efficient for *almost all* workloads and therefore kernel and most
#   distributions have chosen them as defaults. If you still want to change,
#   you should know what you're doing! You *must* disable your distribution's
#   governor settings or conflicts will occur.
#CPU_SCALING_GOVERNOR_ON_AC=powersave
#CPU_SCALING_GOVERNOR_ON_BAT=powersave

Hmm, odd.  We use the  /etc/defaut/tlp file from the upstream package. So this seems
to be an upstream issue then.
https://github.com/NixOS/nixpkgs/blob/master/nixos/modules/services/hardware/tlp.nix#L16-L24

That did it.
Thank you.


Split componentize and transpile

A lot of work is currently going into the "componentize" logic of jco; however, this means it is taking on a ton of dependencies.
If users, such as arcjet, only want to transpile, they should not have to take on this supply chain risk.

We're in the process of discussing where ComponentizeJS best belongs, and currently it's an open question and has been considered on both sides for either moving ComponentizeJS into Jco or moving ComponentizeJS into StarlingMonkey.
This is a good datapoint to hear on the side of moving it into StarlingMonkey and I'll be sure to bring this argument up.


Plugin unable to detect streams on Afreecatv.com

The latest Afreecatv update on April 27th has caused the plugin to not be able to detect, any fix guys? Thanks heaps.

Works fine for me. But the add-on I'm using with Firefox isn't. Was wondering WTH was going on this morning...

I'm on firefox atm and can't detect any stream on Afreecatv.com, so your suggestion is to use other browsers with the livestreamer add-on?

I keep getting error: No plugin can handle URL: http://play.afreecatv.com/

Yeah, livestreamer isn't opening the afreecatv.com streams anymore.

error: No plugin can handle URL: http://play.afreecatv.com/galsa

I've noticed in the past few weeks that afreecatv.com was down for maintenance a few times, which leads me to think that afreecatv.com have changed their addresses.
 So I'm guessing we have to wait till someone finds that address and updates the plugin.

@RhysJB
Instead of
http://play.afreecatv.com/StreamerID
try
http://play.afreeca.com/StreamerID
and it should work.

@RhysJB This is the add-on for Firefox I'm talking about that's no longer working (not sure if you use this)...
https://addons.mozilla.org/en-US/firefox/addon/open-livestreamer/
But yes, like @BIZKIT551... it's probably due to the address change. I never actually noticed the change (or when it happened), but that must be it. That's probably why the add-on for Firefox isn't working. I copy and pasted some .txt files I have backed up and haven't had any issues with it.
Use the old address "afreeca.com" instead of with the "tv" as "afreecatv.com".


Create: 0701-insert-into-a-binary-search-tree.java

File(s) Modified: 0701-insert-into-a-binary-search-tree.java
Language(s) Used: Java
Submission URL: _https://leetcode.com/problems/insert-into-a-binary-search-tree/submissions/1002892385/_

Important
Please make sure the file name is lowercase and a duplicate file does not already exist before merging.

You should see my change. Now code looks more readable.

You should see my change. Now code looks more readable.

Thank you for your review and making the changes to improve the code readability...