multiprocessing on dask.dataframe becomes inefficent if a column is added at runtime

Let dummy be a large dataframe (about 100GB of data). I noticed, that adding a column to that dataframe slows down all further computations.
dummy['cell_type'] = dummy.apply(lambda x: x.synapse_type.split('_')[0], axis = 1)
result = dummy.map_partition(my_fun).compute(get=dask.multiprocessing.get)

my_fun does not use the added column in any way. The above code results in 30% CPU usage and a long running time. With line 1 commented out, I get 100% CPU usage.
Background information:

The dataframe is generated with the .from_delayed method.
The data is stored on a locally
The compute server has 40 cores and 512GB memory.
looking at top (linux command), there is usually one python process using slightly more than 100% CPU, while there are many python processes using about 20-30%. If line 1 is commented, all processes use ~95% CPU.

Does the additional column introduce heavy interprocess communication?  What bottlenecks are likely? Might this be connected to https://github.com/dask/dask/issues/1588?

Creating a new column shouldn't result in increased communication - the graph is still embarrassingly parallel along the partitions (you can see this using the visualize method).

For many cases, it's actually better to use a local instance of the distributed scheduler instead of the multiprocessing scheduler - if for nothing else than that it's easier to debug. This is easy to setup:

from distributed import client
c = Client()
# The distributed scheduler will now be set as the global default.
# If you don't want this, pass in set_as_default=False to Client,
# and specify the scheduler manually as `get=c.get`
# It should have as many worker processes as cores on your machine.
# If you'd like fewer processes, but a few threads in each process, you can
# specify that using `LocalCluster` (done automatically above):
from distributed.deploy import LocalCluster
cluster = LocalCluster(n_workers=10, threads_per_worker=4)
c = Client(cluster)

If using the distributed scheduler, profiling using the web interface should be useful in determining the cause of slowdowns. For the threaded/multiprocessing scheduler, the profiling capabilities can be used (specifically local at the Profiler and ResourceProfiler).

Just to clarify, even though my_fun doesn't use the added column in any way, dask has no way to know if this is true. map_partitions applies a function to each partition - it doesn't apply it to only the columns needed. The same goes for apply - even though you're only using one column, the whole frame will be needed here.

The psutil thing is unrelated. That's for determining the default chunk size when using read_csv.

Thanks for your reply. Is it somehow possible to access the documentation of dask 0.10.2 and distributed 1.12.2? Client  seems to be a new feature, which does not exist in versions of distributed, that are compatible with dask 0.10.2, so I'm not sure how to set up the distributed scheduler.
With dask from the new master branch, I get some strange errors (see below), and many many of my unittests are broken, so to focus on actual analysis, I tried to postpone the upgrade.
[xcb] Unknown sequence number while processing queue
[xcb] Most likely this is a multi-threaded client and XInitThreads has not been called
[xcb] Aborting, sorry about that.
python: ../../src/xcb_io.c:274: poll_for_event: Assertion `!xcb_xlib_threads_sequence_lost' failed.

Is it somehow possible to access the documentation of dask 0.10.2 and distributed 1.12.2?

No, unfortunately you'd have to checkout a tag on the git repo and look at them yourself, we only keep the latest documentation on readthedocs.

Client seems to be a new feature, which does not exist in versions of distributed, that are compatible with dask 0.10.2, so I'm not sure how to set up the distributed scheduler.

Client is the new name for Executor (renamed in the latest release). Just use Executor instead in the code above and everything should work fine.

With dask from the new master branch, I get some strange errors (see below), and many many of my unittests are broken, so to focus on actual analysis, I tried to postpone the upgrade.

There were some breaking changes in the latest release, but the errors you posted look completely unrelated to dask. I'd expect those are related to some other library you may be using.

Thanks again. Yes, I agree. However this error is 100% correlated to upgrading and downgrading dask, which I tried several times. Nevertheless, I hope to get some insights what the bottleneck might be using the distributed scheduler.

About the probably unrelated error: I was able to use matplotlib in processes launched by dask in 0.10.2. In the current dask release, the matplotlib backend specified before is not used in the spawned processes anymore, falling back to the default backend, which causes the error.
While the idea of using matplotlib within dask might seem strange, it gave me a huge speedup to plot data in parallel, and overlay them in the end.

About the strange error: Apparently, matplotlib does not work as in dask 0.10.2 in processes launched by the multiprocessing scheduler. Matplotlib uses the standard backend instead of the one specified before, which causes the error. While using matplotlib in this way might seem strange, it provided a huge speedup by allowing to plot parts of the dataset separately and overlaying them in the end.
edit: using Executor() fails with an OSError: [Errno 2] No such file or directory in some bokeh script, even after updating bokeh. Is there some special version required?

In the meantime some profiling results:
With line 1 commented out, no added column:

blue: my_fun(read_csv(*))

Comment: This is as I expected. The machine has 40 cores reflected by 39 worker IDs. The actual computation starts immediately and I see ~95% CPU usage in the task manager.
line 1 not commented out, column added at runtime, calling _, read_csv and head.

blue: applying the anonymous function
green: applying my_fun
yellow: read_csv

Comment: The actual computatation is delayed for ~20s. There are 3 more processes than cores. Those cores (ID 40, 41, 42) are active in the first milliseconds.

Readthedocs is now hosting some older versions of our documentation: http://distributed.readthedocs.io/en/1.12.2/

Moving all the csv files to tempfs didn't speed anything up, so apparently reading in the data is not the bottleneck. I am aware, that a minimal example is necessary. Should we close the issue until I can provide one?

Apologies for the lack of response.

Using Executor() fails with an OSError: [Errno 2] No such file or directory in some bokeh file, even after updating bokeh. Is there some special version required?

Shouldn't be. What's the full error message? You may also have a better experience debugging spinning up a cluster separately instead:
$ # In one terminal. This will print out a scheduler ip & port, use that below:
$ dask-scheduler
$ # In another terminal
$ dask-worker --nprocs=40 --nthreads=1 SCHEDULER_ADDRESS_FROM_ABOVE

In the meantime some profiling results:

From looking at your profiling plot, it appears to be an increase in serialization cost causing the issue. The local profiler lumps the cost of calling a function and serializing the data for it together, so I can't be sure. The distributed profiler will display the serialization cost in red, so that would be more beneficial for verifying.
I'd expect the multiprocessing scheduler to not move data between processes, as it's a simple map operation going on here. However, some heuristic may be failing. If you can, please try your problem with the distributed scheduler. I expect it to be more efficient across multiple processes, and also should make debugging and profiling easier.

Should we close the issue until I can provide one?

Only if you want to. I'm fine with keeping issues like this open as long as some activity is made to resolve them. I hope we can help you figure things out.

From looking at your profiling plot, it appears to be an increase in serialization cost causing the issue.

To verify this, try doing the following locally (assuming you're using IPython):
# let `df` be a dataframe chunk of appropriate size.
# You can use dask to compute one locally if you're not
# sure what this is:
In [1]: df = dummy.get_partition(0).compute()

In [2]: df2 = df.assign(cell_type=df.apply(lambda x: x.synapse_type.split('_')[0], axis = 1))

In [3]: import cloudpickle

In [4]: with_col = %timeit -o cloudpickle.dumps(df2)

In [5]: without_col = %timeit -o cloudpickle.dumps(df)

In [6]: with_col.best - without_col.best

If the serialization cost is the problem, I'd expect the output of cell 6 to be relatively large.

Thanks for your reply. After updating to dask 11.1, the delay before the actual computation begins is gone.
Given the following code, it appears, that the element-wise apply function is the bottleneck, so I close the issue.
abbr = lambda: np.random.randint(1000, size = 2000000)
pdf = pd.DataFrame(dict(A=abbr(), B=abbr(), c=abbr(), D=abbr()))
#untouched ddf
ddf = dd.from_pandas(pdf, npartitions = 400)
#assignment to column
ddf_assigned = dd.from_pandas(pdf, npartitions = 400)
ddf_assigned['Z'] = ddf_assigned.apply(lambda x: x.A, axis = 1)
#pandas --> dask --> assign --> pandas --> dask
ddf_assigned_from_pandas = dd.from_pandas(ddf_assigned.compute(get = dask.multiprocessing.get), npartitions = 400)

def fun(df):
    time.sleep(0.01)
    return pd.Series(dict(A=1))

%time silent = ddf.map_partitions(fun, meta = int).compute(get = dask.multiprocessing.get)
%time silent = ddf.apply(lambda x: x.A, axis = 1).compute(get = dask.multiprocessing.get)
%time silent = ddf_assigned.map_partitions(fun, meta = int).compute(get = dask.multiprocessing.get)
%time silent = ddf_assigned_from_pandas.map_partitions(fun, meta = int).compute(get = dask.multiprocessing.get)

This gives the following runtimes:
CPU times: user 560 ms, sys: 396 ms, total: 956 ms
Wall time: 1.43 s
CPU times: user 628 ms, sys: 236 ms, total: 864 ms
Wall time: 5.82 s
CPU times: user 1.63 s, sys: 420 ms, total: 2.05 s
Wall time: 7.73 s
CPU times: user 720 ms, sys: 316 ms, total: 1.04 s
Wall time: 1.45 s
I am not


Updates Gemfile and adds dependabot

Add dependabot, specify versions in Gemfile, and update ruby version in Travis configs.
Hannah notes:

Keeps Gemfile.lock in .gitignore because of Travis build errors explained in the Travis documentation. Travis uses Bundler 1 by default.
Removes gemspec and specifies all plugins in the Gemfile. Type Theme removed its own use of gemspec in 2019.
Specifies ruby version 2.7.4 because of a warning in the Jekyll Docs that using Ruby version 3.0.0 will currently cause local builds to fail.
Type Theme is not versioned and does not have releases, but a review of the repo commit history does not indicate changes to the theme that are relevant to our implementation.

It looks like Gemfile.lock is gitignored, which it probably shouldn't be (I say as the person who did it).
I also think understanding how to update the theme is probably a good idea, so I would encourage investing the time to figure that out now.

FYI in starting to look at dependency updates for the Project Electron repo (also uses Type Theme), I saw that the theme replaced gemspec with github-pages in the Gemfile. From my perusing of the commit history, that seems to be one of the bigger changes: https://github.com/rohanchandra/type-theme/commit/6b7ad26005ef08d361e03148f01fc03ab100c3dc.

I've revisited this. I reviewed the Type Theme commit history to see if there were any significant updates that were relevant to us (there are not). The main change I made was to remove the gemspec altogether and further update the Gemfile. I initially tried to add the github-pages gem (as recommended by the gh pages docs) to the Gemfile, but it did not play well with Travis.
cc: @p-galligan (since I can't request your review on your own PR)

Thanks so much for digging into this @HaSistrunk! I removed one config from .travis.yml, which you can read about here
I have a couple of questions, mostly for my own education:

it looks to me like the failure messages you got before and after you added (then removed) the github-pages gem are exactly the same. Is it possible the github-pages gem was a false positive/diagnosis of what was going on there?
Why did you end up removing Gemfile.lock from the repository again? (also PS you're gitignoring .Gemfile.lock not Gemfile.lock, which is the actual filename :)
What does adding the various things to the exclude array in _config.yml do?

Thanks for your questions, @helrond , they helped me clarify what is going on here:

I did falsely diagnose the github-pages gem as being a problem. I've added that back in.
I tried to ignore gemfile.lock because I thought that was causing issues with Travis. I just needed to align the version of bundler I was running to bundle with the ruby version specified in the Travis config.
I dug a little more into the exclude configs, and as explained in the Jekyll documentation, we don't need any of those because they are all excluded by default in Jekyll versions above v3.5 (we are using 3.9.0)

Looks good to me, thanks for taking care of this!


Delegation issues

Hi,  I initially logged into Tezbox with my Fundraiser details and my initial allocation appeared.  I then delegated this correctly and this appeared to work correctly.  For some reason I came back to the wallet this morning and instead of it just opening correctly my browser seems to have lost its setting, so I attempted to re-login with my fundraiser credentials and have found that I only have a small amount of XTZ that I didn't delegate left and there is no sign of my delegation KT account that I created.

I was able to re-import the KT Account.


[BUG]: Image frame not working

Describe the bug
when i select take picture with frame it automatically reboot the photobooth but the path of the frame is correct and im using the release 4.4.0
Steps to reproduce the behavior

click take pic with frame
take picture
photobooth error

Expected behavior
when i select take picture with frame it automatically reboot the photobooth but the path of the frame is correct and im using the release 4.4.0
Photobooth Version
4.4.0
Browser and browser version
chrome and firefox
Operating System
windows 11
Did it work before?
No
Latest working version
No response
Additional context
No response

More information about your setup needed.
OS Photobooth installed on?
PHP version?

More information about your setup needed. OS Photobooth installed on? PHP version?

Hello !
PHP Version 8.2.13
OS : Windows 11

Still need to look at. Busy in real life currently.

For me adding image frames doesn't work either. In the log i found the following:
Error ["Can't create GD resource.","Failed to create frame from image."]
This leads me to image.php and the function call imagcreatetofromstring(). Unfortunately i never did anything with php until now and don't know how to debug...
Thanks for helping

How does your config look like?
Until v4.4.1 frame needed to be a full path while on latest development version it must be placed inside the Webserver.
Example until v4.4.1
/var/www/html/resources/img/frames/frame.png

Example on latest development version:
/resources/img/frames/frame.png

And if it's failing with Can't create GD resource there might be something wrong with your image file.

At least on Linux I also can't confirm a bug on v4.4 0/v4.4.1

I am running on RPI5 with 8 Gb RAM. Installed using the install-photobooth script (version 4.99). PHP version is 8.3.10.
I tried it with the demo image and one of the provided frames in the webserver directory

PHP 8.2, frame with and without extension

Same with php 8.3.10

I did a clean reinstall and now it works perfectly. Unfortunately i cannot replicate what the problem was.
Thanks for your help! Appreciate it a lot!


Custom init process to replace agent hacks

Docker now supports custom init processes (see: https://github.com/docker/docker/pull/26061) so we could replace container entrypoint hacks with init process that reaps zombies and starts actual run command after agent has sent specific signal to init.

This needs to wait for Docker 1.13:
Related Docker PRs:

https://github.com/docker/docker/pull/26061
https://github.com/docker/docker/pull/28037
https://github.com/docker/docker/pull/26941


pass context around to control the calling chain timeout

Split from #409
Currently, the top context isn't passed around, which may cause dead goroutine in kubelet or controller-runtime.

Codecov Report

Merging #414 (bac99a4) into master (db87245) will decrease coverage by 0.13%.
The diff coverage is 37.88%.

@@            Coverage Diff             @@
##           master     #414      +/-   ##
==========================================
- Coverage   47.12%   46.99%   -0.14%
==========================================
  Files          27       27
  Lines        2801     2796       -5
==========================================
- Hits         1320     1314       -6
  Misses       1384     1384
- Partials       97       98       +1

Impacted Files
Coverage Δ

pkg/controller/mount_controller.go
0.00% <0.00%> (ø)

pkg/controller/reconciler.go
0.00% <0.00%> (ø)

pkg/driver/provisioner.go
6.45% <0.00%> (ø)

pkg/util/pod.go
67.30% <0.00%> (ø)

pkg/util/util.go
23.19% <0.00%> (ø)

tests/sanity/fake_juicefs_provider.go
66.66% <ø> (ø)

pkg/controller/pod_driver.go
47.01% <30.00%> (ø)

pkg/juicefs/k8sclient/client.go
27.34% <31.25%> (ø)

pkg/juicefs/mount/process_mount.go
40.83% <31.57%> (ø)

pkg/juicefs/mount/pod_mount.go
40.51% <32.65%> (+0.25%)
:arrow_up:

... and 4 more

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Setup Dana Point

https://en.wikipedia.org/wiki/Dana_Point,_California
https://www.rockybeaches.com/data/noaa_stations?_sort=stationId&geoGroupName__contains=san+clement
TWC0419

Can imitate this migration: https://github.com/natbat/pillarpointstewards/blob/6a984c73dadd4c42a6f335e5b1326a5abf52e2f0/pillarpointstewards/teams/migrations/0007_add_swamis.py#L4-L17

Going with 33.484639,-117.7349367 for the moment: https://www.google.com/maps/place/33°29'04.7"N+117°44'03.5"W/@33.484639,-117.7349367,247m/data=!3m2!1e3!4b1!4m13!1m8!3m7!1s0x80dcf08fba64fd89:0xe42eb4bc7001fa15!2sDana+Point,+CA!3b1!8m2!3d33.4672256!4d-117.6981014!16zL20vMHIyY3o!3m3!8m2!3d33.484639!4d-117.734293?entry=ttu

On running the migration:
ValueError: Field 'station_id' expected a number but got 'TWC0419'.

Need to switch station_id to being a string.

This:
curl "https://api.tidesandcurrents.noaa.gov/api/prod/datagetter?begin_date=20240701&end_date=20240801&product=predictions&station=TWC0419&datum=mllw&time_zone=lst_ldt&units=english&format=json"

Returned:
{"error": {"message":"No Predictions data was found. Please make sure the Datum input is valid."}}

Swapping that TWC0419 for 9410230 returned results:
curl "https://api.tidesandcurrents.noaa.gov/api/prod/datagetter?begin_date=20240701&end_date=20240801&product=predictions&station=9410230&datum=mllw&time_zone=lst_ldt&units=english&format=json"

{ "predictions" : [
{"t":"2024-07-01 00:00", "v":"0.531"},{"t":"2024-07-01 00:06", "v":"0.490"},{"t":"2024-07-01 00:12", "v":"0.453"},{"t":"2024-07-01 00:18", "v":"0.421"},{"t":"2024-07-01 00:24", "v":"0.393"},

Revisiting this:

Maybe the ID to use here is the refStationId of 9410170.
That's the one in San Diego: https://www.rockybeaches.com/data/noaa_stations?_sort=stationId&stationId__contains=9410170

For the moment I'll use that San Diego one:
9410170

Which does work with curl.

OK this is working. Need to do this:
TidePrediction.populate_for_station(9410170)

Onboarded them earlier this afternoon.


Counterclockwise spin

Improve formula when wheel is spinning counteclockwise

Hi @pmoralesp,
Thanks for the PR. Unfortunately this change didn't work in all scenarios.
I've moved this feature to the 4.0.0 release branch, and I've added unit tests.


Fix deprecationRulesInstalled not being set to true automatically

I tried to implement this for static PHPUnit dataProvider's from phpstan/phpstan-phpunit and couldn't get it to work without myself overriding the parameter value in our own phpstan.neon configuration.
I've dropped it from phpstan.neon as well as I believe that's redundant now.

Although you were faster, I like parameters at the top :) Sorry. I'm gonna merge https://github.com/phpstan/phpstan-deprecation-rules/pull/80.


Fix backwards compatibility for optional logging dependencies

Before submitting

[X ] Was this discussed/approved via a Github issue? (no need for typos, doc improvements)
[ X] Did you read the contributor guideline?
[X ] Did you make sure to update the docs?
[ X] Did you write any new necessary tests?
[ X] If you made a notable change (that affects users), did you update the CHANGELOG?

What does this PR do?
Fixes # (issue). #799
There's other ways to fix this, but I felt that adding these redirect files was the simplest and easiest to understand.

Hello @tullie! Thanks for opening this PR.

In the file pytorch_lightning/logging/comet.py:

Line 2:101: E501 line too long (103 > 100 characters)

In the file pytorch_lightning/logging/mlflow.py:

Line 2:101: E501 line too long (103 > 100 characters)

In the file pytorch_lightning/logging/neptune.py:

Line 2:101: E501 line too long (103 > 100 characters)

In the file pytorch_lightning/logging/test_tube.py:

Line 2:101: E501 line too long (103 > 100 characters)

In the file pytorch_lightning/logging/wandb.py:

Line 2:101: E501 line too long (103 > 100 characters)

Do see the Hitchhiker's guide to code style

Could you please merge it to #815?

@tullie thanks!


simplify useHandle for synchronous repo.find

i think it doesn't make sense for setHandle to be exposed here and this
should just be useMemo, but taking it one step at a time.

superseded but thanks :)


Add "Blazor" to project description and readme

I had a hard time finding this project when searching for it because I searched for things like "Blazor test framework", but "Blazor" doesn't appear in the project description or readme. I was recommend updating the project description and readme to mention "Blazor" somewhere, just so it's easier to find.

Hi @danroth27, that is a good point. I will do that right away.
I choose to call the library "Razor Component Testing Library" since it is my impression that the official name for the components we are building is "razor components", is that not the case anymore? If so, I should also rename the library to Blazor Component Testing Library.

I choose to call the library "Razor Component Testing Library" since it is my impression that the official name for the components we are building is "razor components", is that not the case anymore?

In the most formal sense we do refer to  a .razor file is a Razor component file, but for discoverability reasons we often refer to them as "Blazor components".

If so, I should also rename the library to Blazor Component Testing Library.

I think that would probably help more folks find this project.

I think that would probably help more folks find this project.

Noted. I will probably do that as soon as I am done with my (quite) major rewrite to use Steves prototype ideas and integrate AngleSharp and my own AngleSharp.Diffing library into this. That will add a bunch of breaking changes, so a new name will be the least of it :)
Thanks for the suggestion Dan.


Feature Request: Expose verification config in helm chart

Is your feature request related to a problem?
Configuring a PolicyServer to enable verification is already done, see https://github.com/kubewarden/kubewarden-controller/blob/6013ca6919c3711d4e1ebbc8afec0c2e5b38dc59/config/crd/bases/policies.kubewarden.io_policyservers.yaml#L181.
The ConfigMap gets already mounted by the controller. But, chart users need to expose that.
Solution you'd like
Come up with a good UX for helm chart users for enabling verification. We can't enable verification by default as we don't know the source of their policies/images.
Examples:

Accept a configmap name as chart value. The user creates the configmap (in kubewarden) on their own. Check RBAC.

Alternatives you've considered
Accept configmap content as chart value (this poses problems with ugprade. Who owns the ConfigMap?)
Anything else?
No response

Reopened, reverted for now: https://github.com/kubewarden/helm-charts/pull/74


update time macros to unquote time variables

Fixes https://github.com/grafana/google-bigquery-datasource/issues/153

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.


Avoid side effects during string intern processing

When e.g. pushing a string from the contents of a buffer object there's an outside chance that the mechanics of string pushing (allocation) causes a mark-and-sweep, which triggers a finalizer that resizes or reconfigures the buffer object we're trying to string coerce. When the string interning code has allocated space for the string and is ready to copy the data over, the original address and length might no longer be valid.
There's an explicit workaround for this in duk_push_buffer_object() but the workaround is awkward: the code first pushes a fixed buffer and copies the buffer object data there to stabilize it (fixed buffers can't be reallocated/relocated) and then proceeds to string intern the fixed buffer contents.
A better solution would be to ensure string interning cannot trigger finalizers or other side effects. This would then make all call sites safe against this potential (but a bit contrived) issue, and would allow duk_buffer_to_string() to be simplified.

I agree with this pull, string interning is somewhat of a mission-critical mechanism and should avoid side effects as much as possible.

By the way why are all the commits from #875 here?

This pull was a follow-up to the Duktape.Buffer removal branch; I rebased this now that the removal is in master. I quite often do that when a previous branch is finished except for some trivia, because it avoids an actual non-trivial rebase later.

I added this to the 1.5.1 fix list too. However, this issue would be very difficult to trigger in practice with the way typical finalizers work.

Added security tag because memory unsafe behavior would result if the issue is triggered in practice.

That being so, avoiding side effects is desirable anyway. :)

Well, not necessarily :) One of the benefits of GC side effects is that if we're truly low on memory, running the finalizers and freeing the related objects might allow the string push to succeed. With this change in place that won't be possible so we may run out of memory when there's technically collectable garbage in the heap. But because there's no easy and clean alternative that's an OK trade-off.

As a general goal the GC, especially emergency GC, tries to guarantee that:

An allocation won't fail if there's collectable garbage in the heap which, if collected, would allow the allocation to succeed.

There are a few exceptions to this now. One is property table resize which prevents finalizers and other side effects to avoid a finalizer operating on the object whose property table we're resizing. This string intern handling is another exception now.
The JSON fast path also does this, but alloc failures there cause a fallback into the slow path so while the behavior is not ideal, it's still correct for the caller, as the slow path will be able to collect the collectable garbage if it's enough to succeed.

Ok, managed to write a test case which illustrates the problem concretely in master (segfault; the same should happen in 1.x) and shows it was fixed in this pull.


prevent showing popup if disabled

hi do you think this is a reasonable change?
having a disabled input on the browser prevents the popup from showing, but doesn't seem to prevent it on android (crosswalk).

Coverage decreased (-2.02%) to 73.864% when pulling 5529e42c05bb00e68ccf20c3a68ab3e4ebca2749 on papaloizouc:master into 5f10460426637299960288e2109028a865eee7c6 on guylabs:master.

Hi @papaloizouc,
thanks for the contribution. But could you maybe create some tests for it and then also run the grunt build task such that everything is built properly?
Thanks and regards,
Guy

Hi @papaloizouc,
I just moved this to 0.4.0 as there was no update from your side. Is this still needed in the Ionic 1.3.x version?
Thanks and regards,
Guy

Hi @papaloizouc
could you maybe test this with the latest master if this is still needed? As there we now use the Ionic 1.3.2 version.
Thanks and regards,
Guy

hi sorry for the delay. i tested on 0.4 having an  still seems to allow the popup to open. Mostly from my side the values of the auto-complete depend on what you choose on a dropdown, so i have the auto-complete disabled until you select something. I'll try to find some time to write tests for this. Meanwhile it looks like i'm the only person who needed that feature so probably not a big deal.

HI @papaloizouc
ok thanks for the test. I think some tests would be nice, and then I can merge it to master.
Thanks and regards
Guy


fix: raise from exceptions rather than new exceptions to preserve stack trace

Suggestion In order to resolve issue #94
this PR uses the raise from idiom in order to wrap caught exceptions with additional context while preserving their original stack traces.
Notes
The original issue required the exception in semantic-router/semantic_router/llms/openai.py be re-raised, but this PR addresses similar occurrences of this pattern while preserving the additional context added by the new raised exceptions.

Looks good, thanks @alongadot — will run tests

I've corrected the linting issue regarding using Conventional Commits format in the commit message. The build also failed due to a failure in uploading the Codecov report, do you have any advice on that?

@alongadot conventional commits doesn't like the length of your commit message — could you shorten it? For Codecov that's on us, I'm looking into it

I've shortened the PR title to fix Lint PR. Please rerun, hopefully this is it :)

I see codecov/patch failed - should I add test coverage, given no new statements were actually added?

@alongadot codecov can be difficult 😅  — we have it as optional so I am merging and we'll add coverage for those statements in the future, thanks for the PR!


asyncio support?

add one tracer object when loop start and call  tracer.stop(),trace.save() when loop stopped
but the generated html don't show any traces but one loop.run_forever
is anything wrong ?

All those "lines" are traces. Use "AWSD" to navigate and zoom in.

@gaogaotiantian thanks~


Array constant does not work in where condition

Bug Report
Versions

Driver: io.r2dbc:r2dbc-h2:1.0.0.RELEASE
Database: H2 2.1.214
Java: 17
OS: osx, debian

Current Behavior
SQL SELECT my_col FROM codec_test WHERE my_col >= ALL (ARRAY [100,1000]) throws [42000] Syntax error in SQL statement error
I created a small test that reproduces the problem on the main branch:
public class CodecIntegrationTests extends IntegrationTestSupport {
    @Test
    void testAllArray() {
        createTable(connection, "INT");

        Integer value = 10000;

        Flux.from(connection.createStatement("INSERT INTO codec_test values($1)")
                        .bind("$1", value)
                        .execute())
                .flatMap(H2Result::getRowsUpdated)
                .as(StepVerifier::create)
                .expectNext(1L)
                .verifyComplete();

//        connection.createStatement("SELECT my_col FROM codec_test WHERE my_col >= 100 AND my_col >= 1000")
        connection.createStatement("SELECT my_col FROM codec_test WHERE my_col >= ALL (ARRAY [100,1000])")
                .execute()
                .flatMap(it -> it.map((row, rowMetadata) -> Optional.ofNullable(row.get(0))))
                .as(StepVerifier::create)
                .expectNext(Optional.of(10000))
                .verifyComplete();
    }
}

The variant SELECT my_col FROM codec_test WHERE my_col >= 100 AND my_col >= 1000 works well, the variant SELECT my_col FROM codec_test WHERE my_col >= ALL (ARRAY [100,1000]) throws the mentioned exception.
P.s. actually, I found that it fails when the method org.h2.engine.Session.prepareCommand() is called. The source of the issue is in the version of the H2, the mentioned error occurs in 2.1.214, but fixed in the version 2.2.220.
So looks like the question - do you have any plans on updating h2 version?

The driver is currently unmaintained as the previous maintainer was let go from his previous company. I'd be more than happy to welcome new maintainers that are interested in moving this effort forward. Ideally, this driver-add-on to H2 would be included in the H2 core project.


Updated lib_openshift to use communicate instead of wait.  This fixes deadlocking when buffers fill.

@mwoodson :+1:  in #1306


v1.13 backports 2023-05-12

[ ] #25112 -- bpf: Track reply packets of egress gateway and SNATed host-local connections (@gentoo-root)

Once this PR is merged, you can update the PR labels via:
$ for pr in 25112; do contrib/backporting/set-labels.py $pr done 1.13; done

/test-backport-1.13

/test-backport-1.13

/test-1.16-4.19

/test-1.19-4.19

/test-1.22-4.19

/test-1.23-4.19

/test-1.24-4.19

/test-1.25-4.19

/test-1.17-4.19

/ci-multicluster-1.13

/ci-aks-1.13

Thanks @thorn3r for linking the flake issues. Merging the PR based on your assessment.


Tensorflow crashed when using AdamOptimizer

I tried the cnn in the tutorial for MNIST data, but initialize the parameters with stddev=1 (instead of stddev=0.1).
Error message:
I tensorflow/core/common_runtime/local_device.cc:25] Local device intra op parallelism threads: 4
I tensorflow/core/common_runtime/local_session.cc:45] Local session inter op parallelism threads: 4
0 0.098
W tensorflow/core/common_runtime/executor.cc:1027] 0x4472710 Compute status: Invalid argument: ReluGrad input is not finite. : Tensor had NaN values
[[Node: gradients/Relu_grad/Relu/CheckNumerics = CheckNumericsT=DT_FLOAT, message="ReluGrad input is not finite.", _device="/job:localhost/replica:0/task:0/cpu:0"]]
W tensorflow/core/common_runtime/executor.cc:1027] 0x4472710 Compute status: Invalid argument: ReluGrad input is not finite. : Tensor had NaN values
[[Node: gradients/Relu_1_grad/Relu_1/CheckNumerics = CheckNumericsT=DT_FLOAT, message="ReluGrad input is not finite.", _device="/job:localhost/replica:0/task:0/cpu:0"]]
W tensorflow/core/common_runtime/executor.cc:1027] 0x4472710 Compute status: Invalid argument: ReluGrad input is not finite. : Tensor had NaN values
[[Node: gradients/Relu_2_grad/Relu_2/CheckNumerics = CheckNumericsT=DT_FLOAT, message="ReluGrad input is not finite.", _device="/job:localhost/replica:0/task:0/cpu:0"]]
Traceback (most recent call last):
File "2_cnn.py", line 67, in
session.run(train_step, feed_dict={X: x, Y: y, keep_prob: 0.5})
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 345, in run
results = self._do_run(target_list, unique_fetch_targets, feed_dict_string)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 419, in _do_run
e.code)
tensorflow.python.framework.errors.InvalidArgumentError: ReluGrad input is not finite. : Tensor had NaN values
[[Node: gradients/Relu_grad/Relu/CheckNumerics = CheckNumericsT=DT_FLOAT, message="ReluGrad input is not finite.", _device="/job:localhost/replica:0/task:0/cpu:0"]]
Caused by op u'gradients/Relu_grad/Relu/CheckNumerics', defined at:
File "2_cnn.py", line 55, in
train_step = tf.train.AdamOptimizer().minimize(loss)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.py", line 165, in minimize
gate_gradients=gate_gradients)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.py", line 205, in compute_gradients
loss, var_list, gate_gradients=(gate_gradients == Optimizer.GATE_OP))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gradients.py", line 414, in gradients
in_grads = _AsList(grad_fn(op_wrapper, *out_grads))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_grad.py", line 107, in _ReluGrad
t = _VerifyTensor(op.inputs[0], op.name, "ReluGrad input is not finite.")
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_grad.py", line 100, in _VerifyTensor
verify_input = array_ops.check_numerics(t, message=msg)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 48, in check_numerics
name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/op_def_library.py", line 633, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1710, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 988, in init
self._traceback = _extract_stack()
...which was originally created as op u'Relu', defined at:
File "2_cnn.py", line 32, in
h_conv1 = tf.nn.relu(conv2d(X1, w_conv1) + b_conv1)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 506, in relu
return _op_def_lib.apply_op("Relu", features=features, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/op_def_library.py", line 633, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1710, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 988, in init
self._traceback = _extract_stack()

Your weights are likely diverging. Try reducing the learning rate and/or revert your initialization change.

I do not think it's due to diverging, as it crashed when I did following:

same weight initialization as the tutorial
change full_connect to 512 units
change batch_size to 200
Training crashed say, at step 3500 (when accuracy is near 99.2%).

Consider increasing the epsilon value of the optimizer.

I am getting the same error on my Neural Network. I am logging the weights max and min and they are between -1 and 1 so they are not diverging. I get this error when using AdagradOptimizer, AdamOptimizer and the MomentumOptimizer the error happens after the first epoch so the algorithm was already trained with each minibatch at least once. I have now idea of why this is happening, how can I debug it?

One thing you can do is run with a tiny learning rate, or even zero learning rate. If you still have divergence then, you have a bug in your setup. If not, increase your rate slowly and see if there is a regime in which things train without diverging. It's completely possible to have weights that are in a good range, but activations or gradients going to infinity because of the shape of the loss, or too high a learning rate. It's obviously always a possibility that there is a bug in the optimizers, but in my experience, every single instance of this kind of problem could be traced back to a weirdly wired model, learning rate issues, bad randomization of the input examples, or - in the case of Adam or RMSProp - issues with the epsilon value.

OP: it might help if you can paste your entire code in a gist and report it
here.
On Tuesday, November 24, 2015, Vincent Vanhoucke<EMAIL_ADDRESS>wrote:

One thing you can do is run with a tiny learning rate, or even zero
learning rate. If you still have divergence then, you have a bug in your
setup. If not, increase your rate slowly and see if there is a regime in
which things train without diverging. It's completely possible to have
weights that are in a good range, but activations or gradients going to
infinity because of the shape of the loss, or too high a learning rate.
It's obviously always a possibility that there is a bug in the optimizers,
but in my experience, every single instance of this kind of problem could
be traced back to a weirdly wired model, learning rate issues, bad
randomization of the input examples, or - in the case of Adam or RMSProp -
issues with the epsilon value.
—
Reply to this email directly or view it on GitHub
https://github.com/tensorflow/tensorflow/issues/323#issuecomment-159294978
.

@vincentvanhoucke Thank you for your help. I tried to debug it following your advices:
I ran the algorithm with learning_rate = 0. Didn't raise any error.
I then tried to run the algorithm with different learning rates (lr) and obtained the following results:

All the learning rates, but the lr = 1E-8, raised the error. The learning rate 1E-8 didn't learn anything.
My code is here: gist .
If you want to run it you will also need the data that is [here](/home/joao/Dropbox/data analysis/rossman/results/results1/nn_train.dat
/home/joao/Dropbox/data analysis/rossman/results/results1/nn_val.dat) and here.

@jpiabrantes One thing that stands out here is that you use a square root in your loss. That's known to be very unstable numerically for very small values. Can you try 1) not taking the square root or 2) adding a small constant, e.g.: tf.sqrt(1e-4 + ...).
If that's indeed the problem, then one possible approach we can provide tooling around is to optionally cap the gradient of the sqrt function, because it's a common use case. Another possibility is to use gradient clipping in general (see: clip_by_norm(), which we should provide better examples for).
Let me know what happens.
The other avenue is to tune your learning rate decay. Gradients tend to paradoxically grow in magnitude as training progresses, and sometimes that introduces numerical issues late in training. It is still possible that we have issues with numerical precision somewhere, but my hunch is that these errors are legitimate divergence issues (for some twisted definition of 'legitimate').

@vincentvanhoucke You were right. My problem was due to the loss function being RMS. If I use the loss functions you proposed everything works fine. Thank you for the help.

@vincentvanhoucke: I copied the MNIST Conv Net. Since, I have just a handful of images, each Batch is applying some random changes to the images. Code snippet below. The first iteration is successful. 2nd one gives the above error.
def preprocessImages(x):
    retValue = numpy.empty_like(x)
    for i in range(len(data)):
    image = x[i]
    image = tf.reshape(image, [388,190,1])
    image = tf.image.random_brightness(image, max_delta=63)
    # Subtract off the mean and divide by the variance of the pixels.
    float_image = tf.image.per_image_whitening(image)
    float_image_Mat = sess.run(float_image)
    retValue[i] = float_image_Mat.reshape((388*190))
return retValue

for i in range(500):
    feed_dict={x: preprocessImages(data), y_: labelsAsOneHotVector, keep_prob: 0.5}
    train_step.run(feed_dict)
    if i%100 == 0:
        train_accuracy = accuracy.eval(feed_dict)
        print("step %d, training accuracy %g"%(i, train_accuracy))

First iteration works fine!
step 0, training accuracy 0.680851
W tensorflow/core/common_runtime/executor.cc:1027] 0x2a1a82e0 Compute status: Invalid     argument: ReluGrad input is not finite. : Tensor had NaN values

@navraj28 diverging when you use SGD can happen for many reasons:

your learning rate is too high. Note that the right learning rate can be data dependent.
your input data is not well randomized, or highly redundant, which could happen if you're just feeding the same data with few distortions.
This bug is about the AdamOptimizer. I am going to close it. Feel free to reopen if you have new evidence of a bug.

It is likely a 0 log(0) issue. See: http://quabr.com/33712178/tensorflow-nan-bug

@lightscalar that solved it for me. Thx.

Thanx lightscalar

cross_entropy = -tf.reduce_sum(y*tf.log(yconv+ 1e-9))
This works fine

Thanks @lightscalar, that fixed the issue for me too!!

I had exactly the same problem and you fixed the issue for me too! Thanks @lightscalar !!

Thank you @lightscalar , that solved my problem, too!!

thanks @lightscalar

@lightscalar big thanks

I think you can have a try with this solution  :
Use tf.nn.relu6() to replace tf.nn.relu()

@vincentvanhoucke Is there any improvement regarding numerical precisions for tf.sqrt() with last versions? Running v0.12 and still getting the mentioned issue.

@edgarriba that's not an issue with precision of tf.sqrt -- square root operation in general is unstable for small values. The bigger underlying issue is that SGD-like algorithms are fundamentally unstable and can produce NaN/Infinity during normal functioning.

@yanchen036 oh I see, thanks to clarify! I hope this feature comes some day since sometimes find such errors during the training is a bit painful.

We use an optimizer that does a line-search at each step, that makes things more predictable

Is it an internal code or is already part of TF?

Sorry, by "we" I meant OpenAI, not Google, and we'll be open-sourcing our optimization code soon. However, its tailored for RL problems rather than a generic optimizer. You can use l-BFGS optimizer through the scipy optimizer interface, that one is supposed to be stable, although you incur some extra overhead in transferring data between TF and scipy

My input image dimension is 3D i.e. (192256256) with one color channel image and i have used three Convolutional layers (with patches of 555) and 3 pooling layers (kernal size : 333 and stride : 222), one full-connection-layer with 128 nodes and output layer with two nodes. The number of samples are 120 for training. Batch size : 10
I am facing the below error on the cluster:
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Traceback (most recent call last):
File "./mri_cnn.py", line 362, in
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 44, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "./mri_cnn.py", line 332, in main
sess.run(optimizer, feed_dict={train_data_node: batch_data,train_labels_node: batch_labels})
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 767, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 965, in _run
feed_dict_string, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1015, in _do_run
target_list, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 1035, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: BiasGrad requires tensor size <= int32 max
[[Node: gradients/BiasAdd_grad/BiasAddGrad = BiasAddGradT=DT_FLOAT, data_format="NHWC", _device="/job:localhost/replica:0/task:0/cpu:0"]]
Caused by op u'gradients/BiasAdd_grad/BiasAddGrad', defined at:
File "./mri_cnn.py", line 362, in
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 44, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "./mri_cnn.py", line 290, in main
optimizer = tf.train.AdamOptimizer(learning_rate=0.0).minimize(train_loss) # Adam Optimizer
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.py", line 288, in minimize
grad_loss=grad_loss)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/optimizer.py", line 354, in compute_gradients
colocate_gradients_with_ops=colocate_gradients_with_ops)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gradients_impl.py", line 482, in gradients
in_grads = grad_fn(op, *out_grads)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_grad.py", line 204, in _BiasAddGrad
data_format=data_format))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 313, in bias_add_grad
data_format=data_format, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2395, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1264, in init
self._traceback = _extract_stack()
...which was originally created as op u'BiasAdd', defined at:
File "./mri_cnn.py", line 362, in
tf.app.run()
[elided 0 identical lines from previous traceback]
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 44, in run
_sys.exit(main(_sys.argv[:1] + flags_passthrough))
File "./mri_cnn.py", line 272, in main
train_prediction = model(train_data_node, True)
File "./mri_cnn.py", line 181, in model
relu = tf.nn.relu(tf.nn.bias_add(conv, conv1_biases))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/nn_ops.py", line 1316, in bias_add
return gen_nn_ops._bias_add(value, bias, data_format=data_format, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_nn_ops.py", line 281, in _bias_add
data_format=data_format, name=name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 2395, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 1264, in init
self._traceback = _extract_stack()
InvalidArgumentError (see above for traceback): BiasGrad requires tensor size <= int32 max
[[Node: gradients/BiasAdd_grad/BiasAddGrad = BiasAddGradT=DT_FLOAT, data_format="NHWC", _device="/job:localhost/replica:0/task:0/cpu:0"]]
Please suggest, how to fix it?

I've come across a similar bug during calculating the L2 norm along a certain dimension of a feature map. The gradients no longer explode after I added small values(1e-10) elementwise to that feature map. Hope this could help someone.


#94 지원 엔티티 추가

Resolved #94

Codecov Report

Merging #110 (1dc703c) into main (4124b36) will decrease coverage by 0.44%.
The diff coverage is 11.11%.

@@             Coverage Diff              @@
##               main     #110      +/-   ##
============================================
- Coverage     47.01%   46.57%   -0.45%
- Complexity       80       86       +6
============================================
  Files            36       38       +2
  Lines           419      438      +19
  Branches          3        3
============================================
+ Hits            197      204       +7
- Misses          222      234      +12

Impacted Files
Coverage Δ

...its/dsm/benecia/domain/student/domain/Student.java
0.00% <0.00%> (ø)

...benecia/domain/application/domain/Application.java
12.50% <12.50%> (ø)

...m/benecia/domain/enterprise/domain/Enterprise.java
19.04% <0.00%> (-4.49%)
:arrow_down:

.../benecia/domain/attatchment/domain/Attachment.java
83.33% <0.00%> (ø)

...necia/domain/application/code/ApplicationCode.java
6.66% <0.00%> (+6.66%)
:arrow_up:

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Custom theme development improvement

As far as my understanding goes, to develop a custom theme, you have to alter an existing one. Right now, the process can be a bit annoying because parent elements do not necessarily cascade their settings to all offspring. This is because there might some intermediate elements with different settings.
 Hence, I apply: line=element_line(color='black')
But then I realized that the grid lines where still grey.
After a while I realized that the default theme has: panel_grid=element_line(color='grey)

This creates a situation where, if you want to create a custom theme, you need to define every single element in full just to make sure that there are not intermediate elements messing with your settings. With this, inheritance becomes useless.
In my eyes, the implementation should be such that the default theme has all elements defined as None. That way, if an element is passed to the theme, all offspring will correctly inherit its properties. Only at rendering time, any leftover Nones should be substituted by suitable defaults.
If I am missing something and there is already a way to achieve what I am describing, please let me know.

Here you can try to start with theme_none() where only few top-level attributes are defined initially.


SlackedLime.TimeSpent version 1.2

[x] Have you signed the Contributor License Agreement?
[x] Have you checked that there aren't other open pull requests for the same manifest update/change?

[x] Does your manifest conform to the 1.2 schema?

Note: <path> is the name of the directory containing the manifest you're submitting.

Microsoft Reviewers: Open in CodeFlow

@microsoft-github-policy-service agree [company="SlackedLime"]

@microsoft-github-policy-service agree

Not sure why it didn't get validated. Maybe because the installer runs the program right after install?


feat: add associated address if doesn't exists, optimize send bonk an…

Description
Previously it wasn't possible to add bonk to a new wallet.
What are the steps to test that this code is working?
Create a new wallet and try to claim bonk. It should be succesfull.
Screen shots or recordings for UI changes
N/A

@marvinmarnold I have rebased this branch with main and squashed as well. If you think rebase is correct we can merge this work and close #798


Add support for Microsoft.OperationalInsights/Workspaces/DataSources

We use data sources to config Log Analytics workspace where to fetch the data from.

Can one of the admins verify this patch?

Can one of the admins verify this patch?

Hi @haidaocht, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!

It looks like you're working at Microsoft (haitch). If you're full-time, we DON'T require a contribution license agreement.

If you are a vendor, DO please sign the electronic contribution license agreement. It will take 2 minutes and there's no faxing! https://cla.azure.com.

TTYL, AZPRBOT;

@azuresdkci test this please

@azuresdkci test this please

@azuresdkci add to whitelist


Review UX/UI for the toast notifications

UX Description
We are introducing the toast notifications as an experimental capability in https://github.com/containers/podman-desktop/pull/9488
The goal of this ticket, would be to review the UX and the UI of the toast and provide a list of enhancements we could accomplish, in particular:

Behaviors for corner cases: length of the title, length of the description
Styling consistency: border for the toast? drop shadow? font styles, loader consistency
Toast Interaction: possibility to close the notification
Interactions with the Task Manager: Should clicking on the task manager release and remove the toast

Request type
UX analysis/suggestions for improvement
Primary Contact
@slemeur
Deadline for request
Sprint 265

z-index order (notification can be displayed on top of other elements or behind some of them)

appearance: always on, disappear on success, disappear after few seconds, reappear on success

duplication of information between status-bar, task manager and toasts

current:

Purpose:  I would suggest renaming the notification to "Task started" or "Job initiated" to avoid repeating "Building image." The toast should focus on notifying users of task initiation and provide three concise lines of task details.
Size: Limit the size to fit typical task descriptions & cap longer task descriptions to avoid clutter - anything longer than the example.
Style: Use the same font we usually use, with a bold title and regular body, and update the loader to match the status bar spinner.
Duration and Interactions: Display the toast for 3–5 seconds, allowing dismissal via a close button. Clicking it should navigate to the task source and close the toast.
proposed:

Thanks for the feedback @ekidneyrh.
I don't think the title of the task should be "Task started" or "Job initiated". While I agree with the repetition, it also creates another repetitive effect when the user will have multiple tasks started at the same time.
For the other item:

Size: Limiting the size to fit the toast notification might not always be possible. What is your suggestion when this case happen? Should we append ... at the end of the message, display a tooltip over the toast?

Style:  Shouldn't the description of the text be a lighter color? Also, is the position of the progress at the right place?

Duration and Interactions: ACK

for the duration, I'm still wondering if the toast should not stay until the task is completed or bring back the toast when complete (change of the status) else I don't see why I should have a toast at all.
Let say I'm building an image and it takes 10mn. If I see the toast only for 3s saying building image and then it disappears, what's the point ?  I will forget 10mn later that I have an image that is being built. I would probably expect to be notified when the image is ready

Thanks for the feedback @ekidneyrh.
I don't think the title of the task should be "Task started" or "Job initiated". While I agree with the repetition, it also creates another repetitive effect when the user will have multiple tasks started at the same time.

From my understanding the toast should be informational - telling the user what is happening, hence the ‘task started’.
What would be the use case for multiple tasks starting at the same time?

For the other item:

Size: Limiting the size to fit the toast notification might not always be possible. What is your suggestion when this case happen? Should we append ... at the end of the message, display a tooltip over the toast?

Yah i think the '...' and tooltip would be suitable here.

Style:  Shouldn't the description of the text be a lighter color? Also, is the position of the progress at the right place?

We can have the title by white and the description gray-300

I dont have the progress bar here as the toast would be disappearing after 3-5 seconds. Also that is accessible through the task manager and in the status bar so I wouldn't have it here again.

Duration and Interactions: ACK

for the duration, I'm still wondering if the toast should not stay until the task is completed or bring back the toast when complete (change of the status) else I don't see why I should have a toast at all.

The toast is to notify the user that a task is starting. We have a progress bar in the status bar and in the task manager. I don't think we need somewhere else displaying it.

Let say I'm building an image and it takes 10mn. If I see the toast only for 3s saying building image and then it disappears, what's the point ? I will forget 10mn later that I have an image that is being built. I would probably expect to be notified when the image is ready

There can be another toast when the task is complete - but would that get annoying if the task doesnt task that long? How long do the tasks usually take?
They should be non obstructive and not interrupt the users workflow.

@slemeur @benoitf
We could have a divider in the drop down that has the existing images at the top and then as you type the existing list filters down and relevant unpulled images appear like they do on the pull image page

If an image that needs to be pulled is selected the 'Select Image' button changes to a 'Pull Image' button

@ekidneyrh it looks like this last comment is more for the other https://github.com/podman-desktop/podman-desktop/issues/9977 issue ?

Let say I'm building an image and it takes 10mn. If I see the toast only for 3s saying building image and then it disappears, what's the point ? I will forget 10mn later that I have an image that is being built. I would probably expect to be notified when the image is ready

There can be another toast when the task is complete - but would that get annoying if the task doesnt task that long? How long do the tasks usually take?

it's hard to know as it really depends on the tasks. For example building an image can be like 1s if everything is in the cache to multiple hours (if for example it's using some arch emulation, etc)
We can have a value that says for example, if task ended after more than 'x' seconds (could be like 30s, 60s, I don't know) then send a notification when it's ending. (and iterate on this value to see what is the best value (to get the reminder of a task) or to get rid of it)

@ekidneyrh it looks like this last comment is more for the other #9977 issue ?

whoops 🙈 deleted and posted on appropriate ticket.

it's hard to know as it really depends on the tasks. For example building an image can be like 1s if everything is in the cache to multiple hours (if for example it's using some arch emulation, etc)

We can have a value that says for example, if task ended after more than 'x' seconds (could be like 30s, 60s, I don't know) then send a notification when it's ending. (and iterate on this value to see what is the best value (to get the reminder of a task) or to get rid of it)

Yah i think if the task is longer than 60s we can send another toast with 'Task complete'


Add Java 21 to CI build matrix

Checklist

[ ] Read the contributing guide
[ ] PR should be motivated, i.e. what does it fix, why, and if relevant how
[ ] If possible / relevant include an example in the description, that could help all readers
including project members to get a better picture of the change
[ ] Avoid other runtime dependencies
[ ] Meaningful commit history ; intention is important please rebase your commit history so that each
commit is meaningful and help the people that will explore a change in 2 years
[ ] The pull request follows coding style
[ ] Mention Fixes #<issue number> in the description if relevant
[ ] At least one commit should mention Fixes #<issue number> if relevant

Codecov Report

Merging #24 (0003e4c) into main (fd62884) will decrease coverage by 73.09%.
The diff coverage is n/a.

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
@@              Coverage Diff              @@
##               main      #24       +/-   ##
=============================================
- Coverage     85.52%   12.44%   -73.09%
+ Complexity     2912      424     -2488
=============================================
  Files           333      333
  Lines          8856     8856
  Branches       1095     1095
=============================================
- Hits           7574     1102     -6472
- Misses          994     7543     +6549
+ Partials        288      211       -77

see 304 files with indirect coverage changes
:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


[BACKPORT] drivers/pipes: poll: fix off-by-one error

From Jussi Kivilinna<EMAIL_ADDRESS>c73dd8973accd312ca7675fde044df80e9cc62d5
fix off-by-one error in calculation of
bytes in the buffer
Buffer calculation in pipe poll setup is off-by-one when read index
is larger than write index. This causes poll() not getting POLLIN
when buffer has one byte as calculation gives zero bytes in buffer.
Reproducible with:
 {
   char buf[8] = { 0, };
   int fds[2];
   struct pollfd in_pfd;

   pipe2(fds, 8);

   write(fds[1], buf, 7);
   read(fds[0], buf, 7);
   write(fds[1], buf, 1);

   in_pfd.fd = fds[0];
   in_pfd.events = POLLIN;
   ret = poll(&in_pfd, 1, -1); // pipe bug => stuck waiting
   assert(ret == 1);
 }

Flashed on px4fmu-v3_default and did a basic bench test. Couldn't find any actual usage.

Group post
https://groups.yahoo.com/neo/groups/nuttx/conversations/topics/16910;_ylc=X3oDMTM3b3I3YmxwBF9TAzk3MzU5NzE0BGdycElkAzIzMzg5MDcwBGdycHNwSWQDMTcwNTAwNjU1OQRtc2dJZAMxNjkxMQRzZWMDZnRyBHNsawN2dHBjBHN0aW1lAzE1MTI2NTI2MzkEdHBjSWQDMTY5MTA-
NuttX upstream commit
https://bitbucket.org/nuttx/nuttx/commits/ce88bc212d0a3b7eec4e31d53bdc6dab3960b0c1


[Sema] Avoid misleading diagnostics for incomplete enum computed properties

Just avoid a misleading diagnostic for incomplete enum computed properties. We had already a solution applied for extensions so this patch was simply apply to enum as well.

Resolves SR-15657.

@swift-ci Please smoke test

@swift-ci Please smoke test

@swift-ci Please smoke test

@swift-ci Please smoke test

@LucianoPAlmeida This is in my queue, going to take a look on Monday.

@LucianoPAlmeida This is in my queue, going to take a look on Monday.

Thank you @xedin =]

@swift-ci please test

Thank you @xwu @xedin!


[Journey] fix builds

Ticket:

23329

Description

Fix build errors for journey and journey-api
Type

[ ] Dependency upgrade
[x] Bug fix
[ ] New feature
[ ] Dev change
[ ] Additional tests
[ ] Documentation
[ ] Other

Checklist:

[ ] I have added tests that prove my fix is effective or that my feature works
[ ] This change might impact the developer experience of others and should be communicated

Screenshots:
N/A

@bozzelliandrea @andreacappadona17 @alewin I made a few changes to the analytics integration, can you please validate them? Thanks


Migrate to use v0.14 API

I've tried to migrate to use v0.14 Input Plugin API.
This PR contains major update change.
Could you bump up minor/major version not patch level if releasing new version of gem?
And please refer http://docs.fluentd.org/v0.14/articles/plugin-update-from-v12 before release new version.
Thanks,

Changes Unknown when pulling 53abda8beb66501e97ab487f9f03f752c82cfdc3 on cosmo0920:migrate-v0.14 into ** on marcy-terui:master**.

Changes Unknown when pulling 53abda8beb66501e97ab487f9f03f752c82cfdc3 on cosmo0920:migrate-v0.14 into ** on marcy-terui:master**.

Changes Unknown when pulling 53abda8beb66501e97ab487f9f03f752c82cfdc3 on cosmo0920:migrate-v0.14 into ** on marcy-terui:master**.

Changes Unknown when pulling 53abda8beb66501e97ab487f9f03f752c82cfdc3 on cosmo0920:migrate-v0.14 into ** on marcy-terui:master**.

Thanks a lot 😄  Please give me some time.

Sure.
If you have any questions, please feel free to let me know.

An overview of v0.14 plugin helper article would be helpful for you: http://www.clear-code.com/blog/2016/8/30.html
And overview of v0.14 plugin API would be also helpful for you: http://www.clear-code.com/blog/2016/10/20.html


[Feature] Add project checksum to manifest.json and run_results.json metadata

Is there an existing feature request for this?

[X] I have searched the existing issues

Describe the Feature
Prompted by https://github.com/tailsdotcom/dbt_artifacts/issues/53
Currently, it's only possible to match a run_results.json with a manifest.json if they have the same invocation_id, a custom environment variable is set, or the data:metadata:env:dbt_cloud_run_id is present. It should be possible to link a run_results.json with a manifest.json based on the state of the project at the time of their generation.
An initial version of this could simply be a hash of all the concatenated node checksums.
Describe alternatives you've considered
No response
Who will this benefit?
No response
Are you interested in contributing this feature?
No response
Anything else?
No response

I can see how useful this would be. The idea of concatenated node checksums is interesting, but there are some complications -- the contents may change based on environment variables, or vars, or things that change in the dbt_project.yml file. Perhaps an arbitrary uuid that's common to both the manifest and the run_results? Similar to the cloud run_id, I suppose.

Perhaps an arbitrary uuid that's common to both the manifest and the run_results? Similar to the cloud run_id, I suppose.

Is this not just the existing invocation_id? The motivation really is being able to match run_results.json with a manifest.json produced by an identical version of the project. Identical version of the project needs clearly defining, but like you said could include the state of the models, env vars, vars etc.

Oh, I see. We have something like that for the partial parsing check, which is called ManifestStateCheck. We also check for file changes and env var changes. I suppose a combination of the ManifestStateCheck, the file checksums, and env_var changes might work.


Also complete #tags and ^links

Thanks for the great plugin!

it looks exceptions happened to me.

My bad, I made last minute changes and didn't test properly. Just fixed it.

My bad, I made last minute changes and didn't test properly. Just fixed it.

Looks good, would you mind providing me some use cases to test?

Sure! I tested the following on my beancount ledger:

Account completion should now work regardless of the line prefix, so you can test 2024-03-11 open Assets:xyz ..., balance, and close.
Completion for tags should trigger as soon as hitting the # keyboard (make sure you have a few transaction with tags)
Similarly for links, it should trigger by hitting ^.

Also, the plugin doesn't "live reload" accounts/tags/links on a modified document (this was an existing behaviour).
If you want to force reload and use vim-plug you can use the following ugly hack:
function M.reload_beancount_completions()
    for _, s in pairs(cmp.core.sources) do
        if s.name == "beancount" then
            s.source.items = nil
            print("Beacnount completions will reload...")
        end
    end
end

Hi! Did you have a chance to test this?

I have issues with loading tags. The Python codes seemed work, but vim.b.beancount_tags is empty.

Can you provide the test case you are using?

Can you provide the test case you are using?

I use my daily beancount setup and added some tags. I think I may merge directly. But one more thing to be confirmed, I noticed that your completion item of account is now cmp.lsp.CompletionItemKind.Interface. Maybe we should keep all them as cmp.lsp.CompletionItemKind.Property?

Just pushed the change, thank you!

@aldur Thanks!


docs: some improvement after the docs migration

Signed-off-by: Daniel Hu<EMAIL_ADDRESS>Summary

Index page
Links fixed
Format improvement

I'd like to merge it first to record the demo.


App doesn't update risk status (in foreground)

Avoid duplicates

[x] Bug is not mentioned in the FAQ
[x] Bug is not already reported in another issue

Technical details

Device name: iPhone XR

iOS Version: 14.4

App Version: 1.11.0

Case 2 @cricketsamya:  iPhone 12 Pro Max /CWA 1.11.0 (9)/iOS 14.4

Describe the bug
I opened CWA at 15:40, more than 4 hours have passed since the last check (11:27).
The app did NOT automatically carry out a risk check.
Restarting the app did not help, but deactivating background updates did.
Seems like a problem with automatic updates.
Steps to reproduce the issue

Open App after 4 hours have passed since the last check
See that no check happens
Deactivate background updates in iOS Settings
See that the check instantly happens when you reopen the app

Expected behaviour
A risk check should, if the phone is connected to WiFi, happen after 4 hours.
Additional context
No ENA entries in settings.
EN-Log:
ExposureChecks-2021-01-29.txt

Screenrecordings:
https://user-images.githubusercontent.com/67682506/106321370-74308f80-6274-11eb-841b-d9352d9187da.MOV
https://user-images.githubusercontent.com/67682506/106356004-6888ab80-62fc-11eb-81b0-0ae5ddcea2d1.mp4

Could not reproduce this on an iPhone 6s. Will continue monitoring.
The check often happens shortly after the app was closed, in the background.
This issue persists after restarting the device.

Internal tracking ID: EXPOSUREAPP-4953

App is not updating Risk status since yesterday 01.02.2021

@cricketsamya Are you using iOS 14.4?
Interesting is that your app is also not updating in the background, mine is only not updating in the foreground.
Did you restart your device?

iPhone6s / iOS 14.4 / CWA 1.11 - cannot reporduce - I will continue observing issue.
@Ein-Tim FYI
@cricketsamya iPhone modell ? / CWA 1.11 / ios 14.4 ? Thanks for feedback.

@Ein-Tim

You reported 4 days ago this issue. Any pattern you can report.
Can you reproduce the issue on the iPhone XR? If so, what steps?
Can you reproduce the issue on the iPhone 6s? If so, what steps?
Thanks for reporting and the feedback. We are checking also for reports on the AppStore.

@cricketsamya Are you using iOS 14.4?
Interesting is that your app is also not updating in the background, mine is only not updating in the foreground.
Did you restart your device?

I am using iOS 14.4. After restart, the app synced. May be it was stuck during last sync?

iPhone6s / iOS 14.4 / CWA 1.11 - cannot reproduce - I will continue observing issue.
@Ein-Tim FYI
@cricketsamya iPhone modell ? / CWA 1.11 / ios 14.4 ? Thanks for feedback.

@dsarkar
iPhone 12 Pro Max /CWA 1.11.0 (9)/iOS 14.4

@cricketsamya

I am using iOS 14.4. After restart, the app synced. May be it was stuck during last sync?

Could you provide your EN-Log here?

How to export Exposure Notificaiton Logs under iOS 13.7 or newer
German:
Einstellungen ➡ Begegnungsmitteilungen ➡ Status von Begegnungsaufzeichnungen ➡ Begegnungsüberprüfungen ➡ Überprüfungen exportieren
English:
Settings ➡ Exposure Notifications ➡ Exosure Logging Status ➡ Exposure Checks ➡ Export Exposure Checks
To upload the file here, rename it from .json to .txt

@dsarkar

You reported this issue 4 days ago. Any pattern you can report?

Not really, no... The only pattern is that the check always works if I open the app with deactivated background updates.

Can you reproduce the issue on the iPhone XR? If so, what steps?
Can you reproduce the issue on the iPhone 6s? If so, what steps?

There are no special steps I do to reproduce this bug. Sometimes it works on the iPhone XR, sometimes not. I did not yet see this on the iPhone 6s.

@cricketsamya

I am using iOS 14.4. After restart, the app synced. May be it was stuck during last sync?

Could you provide your EN-Log here?
How to export Exposure Notificaiton Logs under iOS 13.7 or newer

@Ein-Tim
Done! Have a look!
ExposureChecks-2021-02-02.txt

Thank you @cricketsamya
When looking at your EN-Log it seems like that the last check (yesterday, 15:53) was not interrupted, but the risk check just stopped working until today at 09:49.
Update from my side:
Currently I don't see this behaviour anymore, neither on the iPhone XR nor on the iPhone 6s.
I will continue to monitor and try to reproduce it.

@Ein-Tim @cricketsamya Internal tracking ID: EXPOSUREAPP-4953

I was again able to reproduce this today, @dsarkar is there anything I should do the next time this happens? Sadly there are no ENA files in the analytics files in the settings...

@Ein-Tim Thanks for the info. I asked the dev he needs more info from your side. Stand by. Fix is planned for 1.12 or 1.13.

@dsarkar
What information should I provide?

@Ein-Tim Right now no further information needed from the developer's side, many thanks! There are fixed introduced in 1.12 and 1.13, so monitoring this issue then would be appreciated.

I will continue to monitor with 1.12.
If I don't see this behaviour anymore, I will close this issue.

@Ein-Tim OK, let´s do that. Thanks.

@dsarkar
iPhone 12 Pro Max
CWA 1.12.1
iOS 14.4
Looks like it appeared after update to CWA 1.12.1
Check exposure logs timestamps..

@cricketsamya ok, thanks for the screenshot. At first sight, it looks ok to me.

If you are on wifi, 4- max 6 downloads per day are typical.
On mobile data max one download per day
If you use mobile data for some hours and then wifi you might have 1 - max 6 downloads per day.

So it looks fine at first sight.
You might try the following: Do not open the app for 24 h and show us then a screenshot. If there us day missing, then it would not look right.
Thanks.

@dsarkar I was on mobile data today for few hours. Then wifi all time.. may be that explains the missing syncs.

Oh, I see, you are saying that in the morning the first check is only triggered when you open the app?
I guess you are using at night wifi, correct?
In the morning, when the first check happens, wifi or mobile data?

@dsarkar first check always happens with wifi for sure 💪🏼

@cricketsamya ok, maybe try this. Don't open the app for a day and report back. Feedback very much appreciated! Thanks

@dsarkar I am talking about yesterdays last check! That happens after I opened the app! And todays last check as well..

@cricketsamya the last check and the check before the last check have a time difference of 4-6 hours in your case, so that looks ok so far. What called my attention, is that during the night there is a larger gap. However, as long you get 4-6 checks per day on wifi, or 1 check on data, or 1-6 check data/wifi mixed, it looks ok so far.

I think it is normal that @cricketsamya does not have any checks at night since he deactivates Bluetooth during the night.

@dsarkar @Ein-Tim yes I deactivate bluetooth. I will try the test! And report! Thanks!

@cricketsamya
@Ein-Tim ok, thanks for pointing that out! I was not aware of BT off during the night. So, all good. Thanks, and good night.

I, personally, can't reproduce this anymore. I will still leave this open to further investigate @cricketsamya's case.
@dsarkar What you could maybe ask the devs if it's intended that the App does not update in the foreground if the App is opened in the foreground and 4 hours pass (I hope you understand what you mean).

@Ein-Tim

(I hope you understand what you mean).

Usually I do ;-)

For sure @dsarkar (:
I will try to explain with an example:
Your last check was today at 14:00h, now you open the App at 17:59 and leave it open. You will see that there is no check carried out at exactly 18:00h (what I would expect). The next check happens as soon as you close the app. Now I wonder whether this is intended or not.
I hope now it's clear what I'm talking about 😁

@Ein-Tim @dsarkar

I did not open the app for 24 hours! Looks like it worked! Except risk status still says 12/14.
All good!

@cricketsamya
Nice to hear that everything is working as it should 👍
I will close this after my question above has been answered.
Have a nice evening!

Your last check was today at 14:00h, now you open the App at 17:59h and leave it open. You will see that there is no check carried out at exactly 18:00h (what I would expect). The next check happens as soon as you close the app.

@Ein-Tim interesting. How long did you leave the app open? Because also from background I do never have exact 4 hours.
Besides that, my expectation as a user would be that it should not matter whether I just switch off the display while cwa is still open, or whether I press the home button before. Of course I expect the check to be triggered after (roughly) every 4 hours in both cases.

@ndegendogo

How long did you leave the app open?

For at least 3-4 Minutes. But I expect a check to be triggered after exactly 4 hours if the app is opened.

Because also from background I do never have exact 4 hours

I never have exactly 4 hours in the background, but if I (in the example above) put the app in foreground at 18:00h, a check will happen.

Besides that, my expectation as a user would be that it should not matter whether I just switch off the display while cwa is still open, or whether I press the home button before. Of course I expect the check to be triggered after (roughly) every 4 hours in both cases.

I think, and I will test this, the check will be triggered after
a) pressing the home button
b) switch of the display
c) killing CWA (unsure about that).

@Ein-Tim ok, I think I understand now the question you made earlier. In any case, the updates are not exactly every 4 hours. Can't find it now, but it was discussed somewhere already.

@dsarkar But I have the stong feeling that the check will not be triggered at all in the foreground in the case I've described above. I will try it and keep you up to date.

@dsarkar Interesting, I will try it ... need to wait for about 3 h now.

@dsarkar in parallel you could try to ask the developers what is the intended behaviour.
If I remember correctly, I have seen risk check triggered from start of application and from transition to the home screen; and the timer started from closing the app. This seems inline with @Ein-Tim 's observations.
But I may well err, have misunderstood something, overseen something or din't remember well ...

Tested the following:
(Last check 08:08h)

Open App at 12:07h
No check happens at 12:08h
No check happens between 12:08h - 12:30h if the app is left in foreground
Either close the app, open a new view and go back to the home screen or switch off the display -> check happens

Screen recordings and screenshots
12:07h -> 12:08h:
https://user-images.githubusercontent.com/67682506/108064625-3ea1e980-705d-11eb-9d93-908f56d477e0.mp4
Still no risk-check at 12:12h:

Still no risk-check at 12:30h:

Open another view to trigger the check:
https://user-images.githubusercontent.com/67682506/108064790-7446d280-705d-11eb-9a2d-336f4418cbe8.MP4

@Ein-Tim Thanks for the feedback. I will also check this over a longer period of time.

@Ein-Tim Last week Tuesday 1600 - Wednesday 1200 we run a check: CWA in the foreground, screen on. See screenshots above, checks are done regularly in the foreground.

@dsarkar Okay, thanks, I consider this as solved now and will close it.

@Ein-Tim ok! Thanks.

@Ein-Tim did you continue to watch this? Any observations?
With 1.12 I had the feeling (although no hard data) that the background risk check was more reliable when I returned to the home screen before I pressed the home button to close the app.
When I forgot this the background check seemed unreliable ...

@ndegendogo
Thanks for the hint, I closed this issue since I didn't experience it anymore.
I will try it again now on 1.13, if I see this behavior again, I'll reopen the issue.
Did you experience it on 1.13?

I don't have loaded 1.13 yet.
And it is a bit hard to test here - during the week I go to the office and have phases without WLAN. Also I am using the contact diary very much, so when I open the app it triggers the check again.


Initial Commit for Ketch in Civo Marketplace

Thank you for wanting to submit a Pull Request to the Civo Kubernetes Marketplace repository!
If your pull request is to submit a new application to the marketplace, please answer the following questions:

[y] Have you followed the guidelines in our Contributing document in setting up the application?
[y] Have you checked that the application your submission is proposing to add does not yet exist on the Marketplace, or as a pull request to be processed?
[y] Have you tested your application on the Civo managed Kubernetes service? Please include a screenshot.
[y] Can you confirm that the software you are submitting licensed for use in a publicly-available Kubernetes marketplace?

If your pull request concerns an existing Marketplace application, please make sure you have:

[ ] Notified the Maintainer of the application in this pull request so that they are aware of your proposal.
[ ] Outlined the changes you are proposing, and the reasons these are required (e.g. stability, compatibility with new versions of Kubernetes implementations, etc).
[ ] Tested that the application works with the proposed updates applied (including a screenshot)

Deployed by Ketch Running in Civo:

Civo Cluster [No Traefik installed by Civo]:

kubectl validation:

Cheers!

Blah! The .DS_Store got picked up by GIT... Will kill this PR and remove it.


Delete resolveConfigOptions from prettier configuration.

Currently, if passing resolveConfigOptions to loader, the option is also passed down to prettier itself, resulting in:

Ignored unknown option { "resolveConfigOptions": <message> }.

This fixes it.

Thanks, merged and published in version 2.1.1


[fix] fix readme error

add an arrow

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and also the chinese readme？

<EMAIL_ADDRESS>


COU should halt when the model it's not active idle

Currently COU doesn't check if the model is blocked or on error state. We should check it first before analyzing or generating the upgrade plan

We do not need to check only relevant (data and control plane) applications and not whole model.


Added scriptcs support

All boxes checked.
Thank you @jchannon!

No probs! Thank you :)
On 11 May 2015 at 17:28, Kyle Kelley<EMAIL_ADDRESS>wrote:

All boxes checked.
Thank you @jchannon https://github.com/jchannon!
--
Reply to this email directly or view it on GitHub
https://github.com/rgbkrk/atom-script/pull/443#issuecomment-100971675.

Nice!

:shipit:
$ apm publish minor
Preparing and tagging a new version ✓
Pushing v2.23.0 tag ✓
Publishing<EMAIL_ADDRESS>✓

I cannot run scriptcs and yes, scriptcs.exe is in my path under C:\ProgramData\chocolatey\bin;


data: arifaisal123

Check List (Check all the applicable boxes)

[x] My code follows the code style of this project.
[ ] My change requires changes to the documentation.
[ ] I have updated the documentation accordingly.
[ ] All new and existing tests passed.
[x] This PR does not contain plagiarized content.
[x] The title of my pull request is a short description of the requested changes.

Hello! You have conflicts in your file. Please resolve and if you have any issues, feel free to ask here or in discord

Thank you. Conflicts resolved for PR.

The conflict is resolved, but there is one small error in your json.


LEGO: Pull request from lego/hb_935_20170901150050378 to master

LEGO: Pull request from lego/hb_935_20170901150050378 to master with localized lcls

@csigs,
Thanks for your contribution as a Microsoft full-time employee or intern. You do not need to sign a CLA.
Thanks,
Microsoft Pull Request Bot


Feat: PromptText and PromptIcon should not attempt to display a prompt icon if one is not found.

In my use case i want a prompt icon to be display normally if one is found for both the PromptIcon and PromptText and one to not attempt to be displayed if one is not found.
I figured the best way to do this might be another setting in the settings SO. There's a few ways I have devised doing this. I will list them below.

A single setting for both PromptIcon and PromptText that defines what to do if a sprite is not found.

public enum SpriteNotFoundBehavior
{
    ///
    /// Let each component handle what happens individually if a sprite is not found.
    ///
    Default,
    ///
    /// In the case of PromptText wherever [Example/Prompt] comes up short display nothing.
    /// In the case of PromptIcon wherever [Example/Prompt] comes up short disable Gameobject or Image component.
    ///
    SuppressDisplay
}

A settings for both PromptIcon and PromptText that defines how we should handle sprite not found scenarios.

PromptIconSpriteNotFoundBehavior
{
    ///
    /// Do nothing (current behavior)
    ///
    Default,
    ///
    /// Disable the gameobject that the PromptIcon is attached to when sprite is not found.
    ///
    DisableGameobject,
    ///
    /// Disable the Image component that the PromptIcon is attached to when sprite is not found.
    ///
    DisableImage
}

PromptTextSpriteNotFoundBehavior
{
    ///
    /// Display error message that's the reason for no sprite showing (current behavior)
    ///
    Default,
    ///
    /// Skips over any [Example/Prompt] that can't be found, preserving the text as it was.
    ///
    PreserveOriginalText
}

A debug mode variable in the settings bool debugMode. When enabled it will display why icons for devices aren't showing as they potentially should be. Sort of how PromptText works. In the case of PromptIcon perhaps there is a debug sprite that shows when no sprite can be found in order to visually see that this is the case.

Let me know what you think :). I will likely roll one of these solutions on my own project immediately, as I need this functionality, but I'm curious if anyone has any input on what might be the best behavior.

Yeah this is a great idea - I got caught out on this making a trailer recently! I'd maybe add two boolean settings:

Display missing tag errors on Development Builds (default true)
Display missing tag errors on non-development builds (Default false)

then do something like this in InputDevicePromptSystem:
static bool DisplayTagErrors {

get {

#if DEVELOPMENT_BUILD || UNITY_EDITOR
return s_Settings.DisplayTagErrorsDevelopmentBuild;
#else
 return s_Settings.DisplayTagErrorsNonDevelopmentBuild;
#endif

}
}

And use in functions like GetActionPathBindingTextSpriteTags


Using ISM7MQTT without the Addon

Hello there, I've come access this HA addon as I'm getting a Wolf Home Link gateway in a couple weeks.
But I have one issue: I'm using HA core, so I am not able to install addons.
What does this addon do on top of the ISM7MQTT program to be able to have the entities in Home Assistant? Or ist ist purely there to make installation easier for hassio users?
Thanks in advance for your answer!

Nothing. It just starts ism7mqtt with the correct command line args.


would be nice if this video player strected on landscape mode

Another thing is, the text description flows into the video

Fixed in https://github.com/lbryio/lbry-android/pull/132.


feature req: color prompt red when folder not writable

feature req: color prompt red when folder not writable
My 2c. ;-0

That's a nice idea (and something I might add in to my own prompt config) but it's not particularly git related. Plus I would have thought colouring the folder name red would be more specific, since its the folder that can't be written. Maybe render the UTF8 lock symbol beside the folder name as well. Ok, I like this idea quite a bit.
But... it's not git related. This plugin is all about providing at a glance info about a git repo. For that reason I won't be adding it to git-radar. Though I will add it to my dotfiles (I'll paste a link here once implemented).
Closing.


Add Rails/FilePath auto-correct

test/integration/cleanliness_test.rb:9:46: C: Rails/FilePath: Please use Rails.root.join('path/to') instead.
    files -= [File.expand_path(__FILE__).sub("#{Rails.root}/", '')]
                                             ^^^^^^^^^^^^^^^^

Expected behavior
autocorrect
Actual behavior
no autocorrect
Steps to reproduce the problem
see code above
RuboCop version
1.9.1 (using Parser <IP_ADDRESS>, rubocop-ast 1.4.1, running on ruby 2.6.5 x86_64-darwin19)
  - rubocop-rails 2.9.1

C is an abbreviation for Convension, not an abbreviation for Correctable. So, C does not mention auto-correction. Also, W is an abbreviation for Warning. So, I think this is the expected behavior.
https://docs.rubocop.org/rubocop/1.9/formatters.html#progress-formatter-default
Currently RuboCop Rails (2.9) doesn't support auto-correct for Rails/FilePath.
https://docs.rubocop.org/rubocop-rails/2.9/cops_rails.html#railsfilepath
OTOH, I think it can be safely auto-corrected (rubocop -a), so it should be possible to enhance Rails/FilePath.

ah thx, I always thought it's correction because they usually had an auto-correct 👍

I updated the title/descriotion

Autocorrection for this appears to have been added in https://github.com/rubocop/rubocop-rails/pull/991
The exact example given here now autocorrects from:
File.expand_path(__FILE__).sub("#{Rails.root}/", '')

to
File.expand_path(__FILE__).sub("#{Rails.root.join('')}", '')

@grosser sorry I forgot to say that the autocorrect actually breaks the original intention of the code (it's getting rid of the trailing slash, meaning that slash doesn't get deleted by the .sub call), so it's a bug: see #1177 =)

ah thx, I was like "looks sus but at least it will shut up" :D


upgrade @shopify/cli-kit

WHY are these changes introduced?
Fixes https://github.com/Shopify/hydrogen/issues/1734
User encounter TypeError: config.plugins.map is not a function error which is fix upstream in https://github.com/Shopify/cli/pull/2975, found in https://github.com/Shopify/cli/issues/3004

WHAT is this pull request doing?

Bumping @shopify/cli-kit to the latest @ ^3.55.4

Hey, so unfortunately upgrading cli-kit is a bit more involved than just changing the version. We need to bump all the templates @shopify/cli version to be in sync. Also, this cli-kit version upgrades to Oclif v3, which means we should also bump our @oclif/core dependency accordingly (to be the same as cli-kit). With all of that, I'm not sure if we'll have to change something in our code to adapt to the new Oclif so we also need to test it well.
I would say this is probably not high priority, given that the linked issue only happens in Hydrogen if you bump @shopify/cli locally without updating our CLI, but we now have h2 upgrade that should take care of this. That said, feel free to try to do the full upgrade with these guidelines if you want 👍

agree not high priority, close for now


Adjust 'Release Guidelines Checks' dashboard for TRG 4.02

Is your support request related to a problem? Please describe.
on the 'Release Guidelines Checks' dashboard, portal(backend) is shown as apparently not compliant with TRG 4.02 but portal-backend is actually compliant with that TRG, see:
https://github.com/eclipse-tractusx/portal-backend/tree/main/docker
https://eclipse-tractusx.github.io/docs/release/trg-4/trg-4-02#description
also for cx-iam the dashboard shows non compliance with TRG 4.02.: I opened https://github.com/eclipse-tractusx/eclipse-tractusx.github.io/pull/383 for that
Describe the solution you'd like
Adjust dashboard to show portal and cx-iam compliant with TRG 4.02.

Hi @evegufy, your PR was approved by @SebastianBezold, think your waiting for feedback from @AngelikaWittek .
For the Release Guidelines Checks we have to check if the result for desired systems.

Nightly Run worked:
https://github.com/eclipse-tractusx/sig-release/actions/runs/6307042100

@carslen I'm reopening the issue because the portal(backend) and cx iam shown are still shown as not compliant with TRG 4.02 on the 'Release Guidelines Checks' dashboard,

little update for cx-iam

but portal-backend seems working differently

@FaGru3n, @evegufy  yes, that's known issue at the moment we don't support image aliases in Dockerfiles at our check. I've just created an issue to fix that in nearest future - https://github.com/eclipse-tractusx/tractusx-quality-checks/issues/53
cc: @SebastianBezold

moved to our backlog to plan it properly


Strip build ID from Nitro binaries

Fix for https://github.com/veracruz-project/veracruz/issues/518

Here's an alternative approach: #520


Added configurable cache

Added files to be able to manually configure the cache time for the dependent packages in the package details page. Time can be configured using a json file.
Progress on: https://github.com/NuGet/NuGetGallery/issues/8038

Please place your base branch from "master" to "dev" branch.
Unless it's a hotfix, we normally require that the change is firstly merged to "dev" branch.


I would like to deploy my blog on a subfolder

Hello,
This template works fine locally but when I try to upload the content of the dist folder to a server, it does not look good because all the paths are wrong. I realized it is because I uploaded the files to a subfolder (not the root server). Is there a way to put relative paths in the built site instead of root paths?

You can add url filter to all urls in the template files, then use the pathPrefix configuration.
I'm working on making this easier right now, so hold on a second.
Do you use Github Pages or something simillar?

Ok done!
All you need to do is uncomment this line inside eleventy.config.js and change subfolder with your subfolder name.
return {
  dir: {
    input: "src",
    output: "dist"
  },
  // pathPrefix: "/subfolder/",
  templateFormats: ["md", "njk", "html"],
  dataTemplateEngine: "njk",
  markdownTemplateEngine: "njk"
}

Also, don't forget to include the subfolder name after domain in site.url data here. For example: https://your-website.com/subfolder.

Thank you very much!

It is much better with the fixes you applied. My only issue is for images inside posts. The image url is the same whether on the posts list on on the post page itself, which means that the image does not load inside the post. You can see the result here: http://styles-bijoux.com/blog/
On the list of posts, the images are fine but when I click on one of them and get inside the post, the image is not visible because the path is wrong.
I think I am missing something regarding the url filter but I do not know what...
Thank you very much for your help!

Please create a new issue so others facing the same problem can be helped 😃