Throwing error on invalid JSON string…

This seems too big to be an oversight, so apologies in advance if this is a design choice and it's been covered before (I looked in the issues and didn't see anything):
When sending an invalid JSON string, eg (note the stray comma):
curl -X PUT "http://localhost:5000/bar/0001" -H "accept: application/json" -H "Content-Type: application/json" -d "{ \"foo\": \"bar\" , }"

… it seems that parsers are expected to simply return an empty dict {}, while silencing any error. Eg flask_parser:
        # Fail silently so that the webargs parser can handle the error
        if hasattr(req, "get_json"):
            # Flask >= 0.10.x
            json_data = req.get_json(force=force, silent=True)
        else:
            # Flask <= 0.9.x
            json_data = req.json
        if json_data is None:
            return core.missing

Despite what the comment implies, I don't think there is any way later on to distinguish between a real missing value, and one resulting from an invalid JSON string…
As expected, assuming an empty dict is compatible with Schema validation options, no error is thrown (and adding an error handler does not seem like it would help).
Am I missing something? Shouldn't JSON parsing errors be caught and trigger a 400 or 422 automatically?

Thanks for the report, @zedrdave . I think you're right about not handling JSON correctly. I would also expect an error response to be returned.
I won't have time to look at this in the immediate future. Would you like to send a PR for this?

This issue is resolved by #334, which allows JSONDecodeError to be raised when the client passes an invalid JSON payload.
Your code will still need to handle the error appropriately.
For example, with flask:
import json
from flask import jsonify

@app.errorhandler(json.JSONDecodeError)
def handle_invalid_json(err):
    return jsonify(["Invalid JSON."]), 400


Update Camel to 4.0.4

Unfortunately this now has a conflict, can you please rebase?
Thanks

@geoand: Branch is rebased

Thanks!


Don't create a new ISwaggerProvider on every resolution (address #541)

The existing behavior has AddSwaggerGen() register the SwaggerGenerator
as a transient; every resolution of ISwaggerProvider generates a new
instance. Each creation causes all Document, Operation, and Schema
filters to be registered again.
This is slow, and requires that filters check before adding an extension
to avoid generating exceptions.
This may address a problem I encountered and reported in #541

When using DI frameworks, I generally tend to avoid using "Singleton" lifetimes, particularly in web applications where the likelihood of concurrent requests is much more likely. By sticking with "Transient" lifetimes, I can avoid the complexity of writing and maintaining thread-safe code for the SwaggerGenerator and it's dependencies.
There's very little happening in the constructors of these services and therefore I'd be astonished if they have any tangible impact on overall response latency. I'd be far more concerned about the service sitting there taking up permanent space in the consuming applications memory, which would be the case if I merged this PR.
I'm aware of the problem you encountered and reported in #541 and have tracked down the real root cause -  the Clone method on SwaggerGeneratorSettings and SchemaRegistrySettings is only performing a shallow copy, causing some state to be incorrectly kept around between invocations. I'm working on a fix as we speak.

Just ran into the Clone issue in my netcoreapp2.0 project when attempting to integrate the swashbuckle cli.  Strangely enough it does not appear to be an issue with projects that target netcoreapp2.1.
@domaindrivendev is this as simple as modifying the Clone method to copy the lists?
I'm using the following as a workaround for now:
var descriptor = services.First(sd => sd.ServiceType == typeof(ISwaggerProvider));
services.Replace(new ServiceDescriptor(
  descriptor.ServiceType,
  descriptor.ImplementationFactory,
  ServiceLifetime.Singleton));

Yeh I think that’s the probably the simplest thing for now and should solve the immediate issue. I’m not particularly happy with the way the settings are currently plumbed through and would love to simplify but that’s prob best left for another day.


[XMLHttpRequest] How to use Fetch API to get excel file data from a link

I can use fetch to get csv file data (text) from a link like:
           fetch(this.state.fileUrl)
                .then((response) => {
                    console.log("response", response);
                    return response.text();
                })

But if the fileUrl was a link to an excel file, the response.body was null and response.text was empty.
I tried use XmlHttpRequest directly, like:
           var request = new XMLHttpRequest();

            request.responseType = "blob";
            request.onreadystatechange = (e) => {
                if (request.readyState !== 4) {
                    return;
                }
                if (request.status === 200) {
                    console.log('success', request);
                } else {
                    console.warn('error');
                }
            };

            request.onload = function(oEvent) {
                var blob = request.response;
                console.log("blob", blob);
                // ...
            };

            request.open('GET', this.state.fileUrl);
            request.send();

It was the same. I also tried use superagent library, still the same:
           agent.get(this.state.fileUrl)
                .accept('application/vnd.ms-excel')
                .end(function(err, response) {

                console.log("agent response", response);
            });

Is fetch (and XmlHttpRequest) support in react native only can fetch text data, no binary data. Or I am doing something wrong at here?

@bright-sea - if you do the exact same request in the browser with superagent or fetch, does that work?

@brentvatne
Just tried use fetch API in chrome, it doesn't work for cross domain resources (Same origin policy), but it works well for same origin resources. I can get response both for text data (for example, a link to a csv file) and binary data (for example, a link to an excel file).
In react native, it works for any resources link, but only text data populated in response.text.  For binary data, we can get response as well, but response.body is null and response.text is empty.

cc @nicklockwood

Hi there! This issue is being closed because it has been inactive for a while.
But don't worry, it will live on with ProductPains! Check out it's new home: https://productpains.com/post/react-native/xmlhttprequest-how-to-use-fetch-api-to-get-excel-file-data-from-a-link


[SPARK-4127] [MLlib] [PySpark] Python bindings for StreamingLinearRegressionWithSGD

Python bindings for StreamingLinearRegressionWithSGD

cc: @freeman-lab Will remove the LinearDataGenerator stuff (or rebase over master) as soon as https://github.com/apache/spark/pull/6715 is merged.

Merged build triggered.

Merged build started.

Test build #34596 has started for   PR 6744 at commit fdaa8b0.

Test build #34596 has finished for   PR 6744 at commit fdaa8b0.

This patch fails Python style tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(LinearRegressionModel):
class LinearDataGenerator(object):

Merged build finished. Test FAILed.

Merged build triggered.

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Test build #34602 has started for   PR 6744 at commit 8a0e560.

Test build #34602 has finished for   PR 6744 at commit 8a0e560.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(LinearRegressionModel):
class LinearDataGenerator(object):

Merged build finished. Test FAILed.

Merged build triggered.

Merged build started.

Test build #34672 has started for   PR 6744 at commit e6c5299.

Test build #34672 has finished for   PR 6744 at commit e6c5299.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(LinearRegressionModel):
class LinearDataGenerator(object):

Merged build finished. Test PASSed.

Merged build triggered.

Merged build started.

Test build #34979 has started for   PR 6744 at commit 30bac18.

Test build #34979 has finished for   PR 6744 at commit 30bac18.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(LinearRegressionModel):
class LinearDataGenerator(object):

Merged build finished. Test FAILed.

Merged build triggered.

Merged build started.

Test build #35004 has started for   PR 6744 at commit c9aaf7e.

Test build #35004 has finished for   PR 6744 at commit c9aaf7e.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(LinearRegressionModel):
class LinearDataGenerator(object):

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Merged build triggered.

Merged build started.

Test build #35692 has started for   PR 6744 at commit cdad794.

Test build #35692 has finished for   PR 6744 at commit cdad794.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(LinearRegressionModel):

Merged build finished. Test FAILed.

Merged build triggered.

Merged build started.

Test build #35697 has started for   PR 6744 at commit 5675a16.

Test build #35697 has finished for   PR 6744 at commit 5675a16.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(LinearRegressionModel):

Merged build finished. Test FAILed.

Merged build triggered.

NAVER - http://www.naver.com/
<EMAIL_ADDRESS>님께 보내신 메일 <Re: [spark] [SPARK-4127] [MLlib] [PySpark] Python bindings for StreamingLinearRegressionWithSGD (#6744)> 이 다음과 같은 이유로 전송 실패했습니다.

받는 사람이 회원님의 메일을 수신차단 하였습니다.

Merged build triggered.

@freeman-lab @mengxr I rebased over master and inherited from StreamingLinearAlgorithm to avoid code duplication. Please give another pass.

Merged build triggered.

Merged build started.

Merged build started.

Merged build started.

Test build #35782 has started for   PR 6744 at commit d47cc24.

Test build #35779 has started for   PR 6744 at commit 1b4ddd6.

Test build #35780 has started for   PR 6744 at commit 618a93b.

Test build #35780 has finished for   PR 6744 at commit 618a93b.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test FAILed.

Test build #35782 has finished for   PR 6744 at commit d47cc24.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(StreamingLinearAlgorithm):

Merged build finished. Test FAILed.

Test build #35779 has finished for   PR 6744 at commit 1b4ddd6.

This patch fails PySpark unit tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearRegressionWithSGD(LinearRegressionModel):

Merged build finished. Test FAILed.

Merged build triggered.

Merged build started.

Test build #35784 has started for   PR 6744 at commit d8f6457.

Test build #35784 has finished for   PR 6744 at commit d8f6457.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearAlgorithm(object):
class StreamingLinearRegressionWithSGD(StreamingLinearAlgorithm):

Merged build finished. Test FAILed.

I moved StreamingLinearAlgorithm to regression.py so that it complies with LabeledPoint and (there were circular imports)

jenkins retest this please

Merged build triggered.

Merged build started.

Test build #36161 has started for   PR 6744 at commit d8f6457.

LGTM. Merged into master. Thanks! (The last Jenkins build was successful.)

Test build #36161 has finished for   PR 6744 at commit d8f6457.

This patch passes all tests.
This patch merges cleanly.
This patch adds the following public classes (experimental):
class StreamingLinearAlgorithm(object):
class StreamingLinearRegressionWithSGD(StreamingLinearAlgorithm):

Merged build finished. Test PASSed.


Implemented setDocumentation in OpenApi Plugin

See #722
@TobiasWalle I don't know whether I added the code on the intended places,
I'm a bit confused about how the OpenApi generation works

@maxemann96 This looks quite good to me. If you have any specific questions let me know.

@maxemann96 Do you think you will have this ready in the next ~24 hours? Considering a Sunday release.

@tipsy Yes :)

@maxemann96 Looks good to me. Ready for merge?

Ready for merge. @TobiasWalle some thoughts?

Going to merge this and release in two hours if there aren't any comments.


Mongo tracker store causing interactive learning to crash

Rasa Core version:
0.13.0a1
Python version:
2.7.15
Operating system (windows, osx, ...):
Ubuntu (Docker)
Issue:
When adding a MongoDB tracker store through the endpoints.yml, when running:
python -m rasa_core.train interactive -d domain.yml -o models/dialogue/current --endpoints endpoints.yml -u current/nlu -c policies.yml  --core models/dialogue/current
I receive the following error:
Traceback (most recent call last):
  File "/opt/conda/envs/env/lib/python2.7/runpy.py", line 174, in _run_module_as_main
    "__main__", fname, loader, pkg_name)
  File "/opt/conda/envs/env/lib/python2.7/runpy.py", line 72, in _run_code
    exec code in run_globals
  File "/opt/conda/envs/env/lib/python2.7/site-packages/rasa_core/train.py", line 366, in <module>
    additional_args)
  File "/opt/conda/envs/env/lib/python2.7/site-packages/rasa_core/train.py", line 313, in do_interactive_learning
    _broker)
  File "/opt/conda/envs/env/lib/python2.7/site-packages/rasa_core/tracker_store.py", line 48, in find_tracker_store
    **store.kwargs)
TypeError: __init__() got an unexpected keyword argument 'user'

Content of endpoints.yml file:
action_endpoint:
  url: http://rasa-actions:5055/webhook
nlu:
  url: http://rasa-nlu:5000
tracker_store:
  store_type: mongod
  url: mongodb://mongo:27017
  user: rasa
  password: password

I think I might have found the issue. In the docs it says user instead of username.

would you mind submitting a PR to fix this?

your own fork of the repo ideally

But submit a PR into master? Saw the same issue exists in 0.12 already.

no please base the PR off of 0.12.x :)

Done.


WSL2 ubuntu in Win 10, imports crash

Godot version
4.0.RC3
System information
WSL2, ubuntu 20.04.5 LTS, under Windows 10 Pro 22H2, os build 19045.2604 AMD Ryzen 7 5700X 8-Core Processor 3.40 GHz RAM: 32.0 GB (31.9 GB usable) NVIDIA GeForce RTX 3060 driver 526.98
Issue description
I have not been able to successfully import anything created under win 10 into WSL2 ubuntu (including 3rd party demos, etc).  Import and edit crashes.  The project then appears in the project list.  Loading crashes.  There is a delay as the editor window appears and a load attempt is made, but before you can use the editor it crashes.
Note that 3.5 has no crashing issues and apart from sound works okay on stuff I have tried.
If you need an example, try this one: https://gdquest-demos.github.io/godot-4-3d-third-person-controller/  from gdquest.
Screenshot of terminal attached.
I am a long way away from being a technical person so I hope this is valid and that this helps. :)

PS and probably not related:  How can you fix an editor options issue (say like blender path not available) if you have to enter the editor to do so and that issue is the reason for the crash?  Maybe another option button on the project manager: "Edit", "Run", "Rename", "Remove", and also Editor "Preferences".
Steps to reproduce
Minimal reproduction project
https://gdquest-demos.github.io/godot-4-3d-third-person-controller

Please don't paste the same link and screenshot 3 times.
Out of curiosity, why not use native Windows builds?

PS and probably not related: How can you fix an editor options issue (say like blender path not available) if you have to enter the editor to do so and that issue is the reason for the crash? Maybe another option button on the project manager: "Edit", "Run", "Rename", "Remove", and also Editor "Preferences".

See https://github.com/godotengine/godot-proposals/issues/1602.

Hi,
It's Ubuntu "under" Windows...
How are you running Ubuntu? in a Virtual Machine?
If yes then which VM software are you using in Windows?
Jesse

Nevermind, just reread.

Calinou
Re screenshots, ok I understand.
Re curiosity: I do use windows however I wanted to try the linux version (out of my curiosity).
re proposal:  Good to see  :)
Jesse:
ok :)

The demo you're trying to import is not importable because not all the files are included in the repository yet: https://github.com/gdquest-demos/godot-4-3d-third-person-controller/issues/15

Shall I try others and post screenshots of each if they fail?

No, this is enough for now.

See the message:

WARNING: lavapipe is not a conformant vulkan implementation, testing use only.

As it says, it's using lavapipe, which is a software renderer for Vulkan. If it works, it's going to be very slow. But it seems not to work and to crash.
Windows WSL2 probably ships with an old version of Mesa/lavapipe, or it's simply not compatible with WSL2 yet, at least to run complex Vulkan applications.
You should likely use the GL Compatibility renderer on WSL2 for now.

Hi Calinou, ok.
Akien-mga
I am not sure how to do that on an import.  I will see if I can.

You might need to force it from the command line:
cd /to/project/folder
/path/to/godot --rendering-driver opengl --editor

Then if it opens fine, go the project settings and change the renderer to GL Compatibility.

Hi Akien-mga
I did that (replace 'opengl' with 'opengl3) and it loaded with one dependency error as per the screenshot below.  Haven't tried more.


Update to index.md at documentation

Fixes https://github.com/rh-ecosystem-edge/kernel-module-management/issues/392

/lgtm


Mismatched Index Converting Pandas Dataframe to Xarray Dataset

I notice this behavior happening in version 0.15.0 afterwards, but no in version 0.10.7.
When converting a Pandas Dataframe to Xaray Dataset using from_dataframe, there is a chance that the index will get mismatched.
import xarray as xr
import pandas as pd
import numpy as np
df = pd.DataFrame(np.arange(12), index=pd.MultiIndex.from_product([[0, 1], ['bar', 'foo'],
                                                                   list('HGD')]))
new_df = df.copy()
new_index = df.index.set_levels(['A', 'D', 'E', 'G', 'H'], level=2)
new_index = new_index.set_codes([4, 3, 1, 4, 3, 1, 4, 3, 1, 4, 3, 1], level=2)
new_df.index = new_index
xr.Dataset.from_dataframe(new_df).to_dataframe()
xr.Dataset.from_dataframe(df).to_dataframe()

df and new_df are intrinsically the same Dataframe, with new_df has some unused levels for the multi-index. However, xr.Dataset.from_dataframe(new_df).to_dataframe() and xr.Dataset.from_dataframe(df).to_dataframe() give different results, with the former has a misaligned index.
It seems the versions of numpy and pandas package do not matter, although I tried both the latest version, and numpy=1.16.2 and pandas=0.23.0

Thanks for the report @falcon8241 . I think this is fixed on master by https://github.com/pydata/xarray/commit/1eedc5c146d9e6ebd46ab2cc8b271e51b3a25959


Overwrite fprintf, fputc, fputs

Also overwrite fprintf_unlocked, fputc_unlocked, fputs_unlocked, as well as error functions perror, error and error_at_line. This just about covers most GNU utilities such as ls, ln, cat, find, touch, etc.
Provided asprintf function (for when it's not available), also vasprintf (as a macro), and although it works for me, ymmv.

Looks like a lot of stuff covered. I'll give it a try, thx.


Update Python version in poetry to accomodate 3.10

I have updated the Python versions accommodated by the project. The versions accommodated now include the default Python version in Ubuntu 22.04, version 3.10. README is updated to reflect the change.

config.py updated server-side to include TomTom API key.


[WIP] Migrate to v0.14 API

Remaining tasks

[ ] Use timer to execute periodically task
[ ] Use storage plugin to store values

Coverage decreased (-0.9%) to 92.07% when pulling c12618f2cbf45b724b154cd352caf63374ade138 on cosmo0920:migrate-v0.14 into 50195a97014619a05757a6ec61900fc83bd9fea7 on sonots:master.

Coverage decreased (-0.9%) to 92.07% when pulling c12618f2cbf45b724b154cd352caf63374ade138 on cosmo0920:migrate-v0.14 into 50195a97014619a05757a6ec61900fc83bd9fea7 on sonots:master.


🚀 | Switch between playlists by button

Feature Description
What functionality would you like to see in your phoniebox?
Child #1 is growing older and would be able to handle the box better. I'd like to enable switching between playlists by button. But not like in https://github.com/MiczFlor/RPi-Jukebox-RFID/wiki/Hack-Playlist-triggered-by-GPIO-Button. That hack triggers a hardcoded playlist.
I'd rather have two additional buttons that execute NextPlaylist and PrevPlaylist.
How do you envision the feature to work from a users perspective?
This feature would enable navigation through playlists without the RFID cards (especially if supported by a display), suitable for an older child that is able to read.
Further information that might help
Anybody did such a thing before?

Is there a way to find out the current playlist without checking the logs?

Note to self: RPi-Jukebox-RFID/shared/latestID.txt

Duplicate of #574


Proposal: A way to control idle connection timeouts

This is an AWESOME tool to provide devs an easy and secure way of using our development environment on our k8s cluster.
The issue
Idle connection timeout is very short, and we can't change streaming-connection-idle-timeout setting in our managed kubernetes cluster.
Proposal
Some kind of flag to either control the port-forwarding tunnel idle timeout (not sure how feasible this would be tho), or one that tells the tool to reconnect the service upon disconnecting.
I'm not a fan of either of those two options but perhaps this is a good conversation starter to find a solution.

kubefwd port-forwards to Pods. I have not done any type of exhaustive research on this, but in my initial work, I did not find a reliable way to know what constitutes a complete failure or temporary disruption and what to do next. Since kubefwd was designed as a development utility one of the main use cases involves the ability to observe the behavior of the pods you are connected to, something difficult to do when communicating with a server that has dozens or hundreds of pods backing it (unless you have a well oiled, distributed tracing implementation). Automatically disconnecting from on Pod and connecting to another may break that use cast, leaving the developer observing a Pod they are no longer connected to.
I like the feature and would love to have a flag that enables it. There are times that I don't care what Pod I am connected to and only concerned for the connection at the service level.
At this point, kubefwd only knows a connection is down when an attempt to connect is made; this may be some time after a Pod has crashed. Would kubefwd need to watch for changes on connected Pods.

Yeah I didn't think this would be an easy task by any stretch, just thought it was necessary to voice what could be a very VERY cool feature, I can't promise I can do anything about it, but I'll surf through the code trying to get how kubefwd works and perhaps offer my brain to bounce ideas around and see if there's any feasible way of doing this.
At least for the use case I'm handling right now, my team of developers don't really care to which pod they're connecting to, as long as they get an endpoint to the deployed service they can reference in their local development (having all of our setup running locally, really upsets our laptops hehe)
What I've noticed is that the timeout is precisely 5 minutes and has to do with the --streaming-connection-timeout-idle perhaps a child process can be spawned to check every X amount of minutes to check connectivity to a service, and if it's down try to make the connection again? I might be talking complete trash tho haha, haven't looked at the code long enough yet to know if this even makes any sense at all.

I'll have to explore the timeout issue you are having. I typically run kubefwd aginst custom cluster I build and at times I have had kubefwd attached for days with no problem.

That's interesting, I think this "bug" is only true for managed k8s instances (GKE, AKS or EKS), where one doesn't have control of how that's setup. I haven't tried in GKE or EKS yet but I'd imagine they would behave similarly.
I'm jealous of your k8s instance running kubewd for days 😛

I'm also experiencing the disconnection after 5 minutes of idle time in Azure AKS. I use kubefwd extensively, but it does become a bit annoying having to restart kubefwd and enter my password each time (so it can update the hosts file). I haven't looked in any depth whether I can configure the kubelet timeout setting yet.

The 5-minute timeout looks to be a kubelet setting (feature). I use kubeadm to build custom clusters which must set this timeout to infinity.
https://stackoverflow.com/questions/47484312/kubectl-port-forwarding-timeout-issue
I plan to explore some options for re-connecting soon.

Release 1.11.0 should resolve this. I have not extensive testing and will re-open the issue if needed.

I'm afraid it doesn't reconnect automatically on timeout. Using Azure AKS which has the 5 minute window. I have seen it automatically reconnect when a pod is deployed though.

I can confirm that not reconnecting on the 5 minute timeout. Works only on pod refresh only.

I can actually see it reconnecting now, after updating to 1.17.0, however it does take some time.
INFO[07:38:04] Port-Forward: <IP_ADDRESS> pdfs:80 to pod pdfs-7d79bb499f-7vtlg:80
ERRO[07:46:29] Runtime error: lost connection to pod
WARN[07:46:29] Stopped forwarding pod pdfs-7d79bb499f-7vtlg for pdfs.namespace.cluster
INFO[07:58:04] Port-Forward: <IP_ADDRESS> pdfs:80 to pod pdfs-7d79bb499f-7vtlg:80

I think this is probably what #153 is trying to solve.

@cjimti Hi. Is this fixed? I still find port forwarding timing out in my GKE cluster every few minutes.

If I stop it and then start it again, it works. But the annoying thing is that I have to do this every 5 minutes or so 😢

I run version 1.17.3 and forward ~30 services (pods) ~6-8 hours a day. I only drop connections If I suspend my computer or lose my internet connection completely, which is rare.
There was some work to check connections and re-connect a few versions ago that caused more problems than it solved. I'm not an expert on socat and the networking around you and GKE and why you would lose connection so often.
Let me know if you have tried version 1.17.3. It does not make attempts to check the connections and re-connect, yet in my experience has been more stable.

@cjimti Hi. Thanks a lot for your response. I am using 1.17.3 as mentioned above already and while it works and is stable, the issue of timeout is not with Kubefwd directly but due to --streaming-connection-idle-timeout as mentioned here https://stackoverflow.com/questions/47484312/kubectl-port-forwarding-timeout-issue which I guess is around 4-5 minutes in GKE and I am guessing that is the reason due to which the connect breaks.
Actually, I had similar problems when forwarding manually like this (without Kubefwd):
#!/bin/sh
kubectl --context <mycontext> --namespace <mynamespace> port-forward $(kubectl get pods --context <mycontext> --namespace <mynamespace> --selector "statefulset.kubernetes.io/pod-name=dgraph-dgraph-alpha-0,release=dgraph" --output jsonpath="{.items[0].metadata.name}") 9999:8080

But to get over this problem and reconnect, I wrapped it within a while like this and it reconnects without issues:
#!/bin/sh
while true; do kubectl --context <mycontext> --namespace <mynamespace> port-forward $(kubectl get pods --context <mycontext> --namespace <mynamespace> --selector "statefulset.kubernetes.io/pod-name=dgraph-dgraph-alpha-0,release=dgraph" --output jsonpath="{.items[0].metadata.name}") 9999:8080; done

I was wondering how to do the same with Kubefwd since I cant wrap it in a while (it does not exit on forwarding failures) or was wondering if there was an inbuilt way to do this so that Kubefwd can reconnect periodically rather than me having to modify the flag in the kubelet to increase the timeout which is not recommended.
Really love kubefwd. Btw, while not related to this issue, is there any way to use kubefwd over remote ssh?
I have my setup like this where I use a remote VM to do all my development:
My PC->Remote SSH to VM in GCP->Kubefwd->GKE Cluster
Now, while kubefwd works well in remote VM, I was wondering if there was a way to forward the same to my local PC as well so that I need not open an RDP to access the browser remotely when needed.
Thanks.

@cjimti re-opening an old thread as we're also constantly affected by this. Would it be possible to have kubefwd fail (and terminate the process) on a forwarding failure?
What we see is:
ERR: Runtime: lost connection to pod
WARN: Stopped forwarding pod ...

and then kubefwd just hangs forever.


F#2298 generate metadata when datasource enabled

Description
Changes metadata creation time since creation of datasource
Related Issue : #2298
How Has This Been Tested?

create DataSource normally.

The "Go to Metadata" button should not be present immediately after creation.

The "Go to Metadata" button should appear after the completion message.

create DataSource again (for error)

To create a DataSource ingestion error, add the column using the wrong longitude, latitude column.

The "Go to Metadata" button should not be present immediately after creation.

DataSource should not appear in metadata list after error occurs.

Need additional checks?
Types of changes

[ ] Bug fix (non-breaking change which fixes an issue)
[ ] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to change)

Checklist:

[ ] I have read the CONTRIBUTING document.
[ ] My code follows the code style of this project.
[ ] My change requires a change to the documentation.
[ ] I have added tests to cover my changes.

Additional Context

run build
deploy to 4

run build
deploy to 4

@brandon-wonjune @ufoscw
Even though ingestion success, the "Go to Metadata" button does not appear after ingestion in the detail view that appears after creating the data source.
데이터 소스 생성 후 나타나는 상세화면 내에서 적재 작업이 끝난 후 "Go to Metadata" 버튼이 나오지 않습니다.

@kyungtaak
Changed metadata generation time before topic sending.

run build
deploy to 4


[FEATURE] Birthday Mode

Description
We can have a birthday field for the person (optional)
there will be a list of birthdays on discover page (in the side)
AND CONFETTTTIIIIIII ON THEIR PROFILES [TOP CLASS IMPORTANCE]
Screenshots
No response
Additional information
No response

Whilst it would be great to celebrate the birthdays of the LinkFree users, this does begin to fall into the realm of personal information that we are not looking to store (and could potentially present a security risk) so I will close this issue for now.

@SaraJaoude I was hoping it would be a "optional" information to disclose to us, so it shouldn't be a big issue, since they willingly give us that information


Please don't suggest using sudo pip install

This project is awesome, but please don't teach people to use pip with sudo.
Tell them to use virtualenv instead !
sudo pip is potentially dangerous, just like curl | bash
cheers

I don't disagree. However this is- for better or worse- Python aimed at the lowest-common-denominator. The aim is to always get people doing something so they can worry about the implications later, rather than deflect beginners with things like virtualenv.

I disagree :-)
Security primes over convenience.
Besides, it's just 4 additional steps.
If we want people to copy-paste commands, they might as well copy-paste safe commands.

Sorry, but I fail to understand how this is "completed".
Of course it's your choice to refuse it.

The simple answer: it's not. I have been bulk closing a lot of issues to stir up the dust as we start to add some management and oversight into how we deal with them.
Genuinely, thank you for still putting up this fight.
I think I'd now recommend python3 -m pip install and any mention of python2 is quite thoroughly redundant. Need to check and fix that across all of our repositories though.
And uh... we rely upon a lot of curl | bash installers... :grimacing:

So for virtualenv and py3 it's :
bash> python3 -m ~/pimoroni
bash> . ~/pimoroni/bin/activate
bash> pip install ...

The next day...
bash> python3 some-example.py
bash>
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ModuleNotFoundError: No module named 'unicornhatmini'

"Hello, support, yes, I installed your library as per your instructions, started up my Pi today and it's not working?!?!?"

pip install --user unicornhatmini

I decided to dig out an old Pi & resurrect my office door sign, which uses the Unicorn Hat Mini. I know minimal Python, so I also tried the sudo pip3 install... route. Nowadays it immediately errors:
pi@pi-office-door:~ $ sudo pip3 install unicornhatmini
error: externally-managed-environment

× This environment is externally managed
╰─> To install Python packages system-wide, try apt install
    python3-xyz, where xyz is the package you are trying to
    install.

    If you wish to install a non-Debian-packaged Python package,
    create a virtual environment using python3 -m venv path/to/venv.
    Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make
    sure you have python3-full installed.

    For more information visit http://rptl.io/venv

note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.
hint: See PEP 668 for the detailed specification.

Consdering the error also mentions venv, I think @faxm0dem's solution is the most suitable. Will do a pull request if I get time later.

We have a new boilerplate that deals with this and other issues relating to Bookworm and also Pi 5, which I’m gradually migrating things to - https://github.com/pimoroni/boilerplate-python
Life comes at you fast!
A PR would be most welcome, but this is on my (long) todo list if you don’t get ‘round to it.


Slow output on using different model

i tried it on faster_rcnn_resnet101_coco_2018_01_28 and faster_rcnn_inception_v2_coco_2018_01_28 but both of them results in slow output and not able to detect speed but the already present model in this project works fine.Please help me @ahmetozlu

"results in slow output" depends:

Speed of  the models you chose.
Hardware capabilities: the machine that the model runs on it should have enough powerful GPU.

Also, tensorflow should be installed wih the GPU support so detection models can work faster.


Causing Out-of-Memory crash for users in USA.

It's causing this error for users in USA, in all browsers on any machine/OS. It works fine for non-US users in any browser on any machine/OS. I am using v2.24.0 in a Reactjs/Nextjs app.

There's not enough information to reproduce or investigate this.
It looks like your application is bundled with webpack, and the problem occurs in a call made from application code in journal-entry.
Do you know what moment-related calls are being made by journal-entry?  Is it one specific call / loop that leads to the out of memory error?

@ashsearle It turned out, it wasn't moment.js after all. So no worries. I will close this. Thanks anyway.


[prim, rom_ctrl] Remove S&P layer from data scrambling

As elaborated on #20788, the S&P layer is removed from data scrambling in order to improve error detection guarantees, interactions with ECC and timing.

For Ibex, this has to be disabled separately in a second PR, since we'll have to vendor the updated memory backdoor utils and the scrambling primitive into the ibex repository first.

I am going ahead with this and merge it so that I can do the Ibex re-vendoring.


Standardize formatting of manifests/x/XSplit/Broadcaster/PTR/4.4.2205.2602

Microsoft Reviewers: Open in CodeFlow

@wingetbot run

URL: https://cdn2.xsplit.com/download/bc/m47/4.4.2205.2602/XSplit_Broadcaster_Beta_4.4.2205.2602.exe
Status Code: 200
(Automated message - build 931)


Upgrade to ocamlformat 0.26.1 and set exp-grouping=preserve

This PR upgrades ocamlformat to the latest version 0.26.1 and adds exp-grouping=preserve to the configuration.
Here is what the man page says on exp-grouping:
--exp-grouping={parens|preserve}
    Style of expression grouping. parens groups expressions using parentheses. preserve preserves
    the original grouping syntax (parentheses or begin/end). The default value is parens. Cannot
    be set in attributes.

In other words, exp-grouping=preserve allows one to explicitly use begin ... end instead of ( ... ).  The default is to always use ( ... ).
I've been using exp-grouping=preserve in several projects, because I find that using begin ... ; ... end for grouping statements/blocks is visually clearer (easier and faster to read).  I don't think that it should be controversial that begin ... ; ... end is easier to spot visually than ( ... ; ... ).  What could be controversial is that exp-grouping=preserve is not the default of ocamlformat, some people might find begin ... ; ... end "uglier", and having the option could lead to formatting wars (i.e. people changing formatting back and forth). I personally don't believe those are significant enough reasons to force code to be visually subtler in a library like this, with very high requirements for correctness.  Ultimately this is not a purely technical matter.

Thanks for the PR .
I agree that begin ... end is clearer than parenthesis !


update KubeletPluginsWatcher feature gate

KubeletPluginsWatcher feature is beta in 1.12 release
xref: kubernetes/kubernetes#68200

/lgtm

/assign @steveperry-53
PTAL

/lgtm
/assign @zparnold

This should go to release-1.12 branch.

@tengqm I saw the commits before were merged to master branch, should i change it to release1.12 ?

/approve


is this repo support training on multiple nodes?

Did you find a solution for multi-nodes? @forever208


Codeception Yii2 Module 'cleanup' of multiple DB connections and multiple requests in Functional Tests

This issue is a request for an enhancement of the Codeception Yii2 Module for Functional Testing. The module includes a 'cleanup' option to use a DB Transaction for the main 'db' connection, but is missing some functionality that I am expecting.  The module needs to handle DB Transactions for multiple DB connections, as well as persist the DB connections and their open transactions across multiple Application Requests within one functional test.
I have come up with a solution and provide code examples below for anyone else who needs this, but I would also like to have a discussion on best practices, @DavertMik, and request that the concept be integrated into the Codeception Yii2 Module.
I found this Blog post on the Codeception site for Unit Testing with Database:
http://codeception.com/06-28-2014/unit-testing-with-database.html
The post indicates to use DB Transactions around Unit and Functional Tests for automatic rollback of DB changes for repeatable tests, rather than re-initializing the database (slow).  There are some examples, but the documentation, configuration, and best practices for Functional Tests are lacking.  Also, the Codeception Yii2 Module page is missing documentation on the 'cleanup' config option that is available in code.
I am using Yii2 Advanced app template and Codeception to write Functional Tests for an application.  Our project has multiple DB connections (db, db_log, etc) and has a large database, so re-initializing during testing with dump.sql scripts is not a good solution.  I like the idea of DB Transactions to speed up testing and keep the database data clean.  I was hoping the Yii2 Module would support multiple connections out of the box, but found this wasn't the case.
Additionally, I am writing Functional Tests using Cest classes such that one test function makes several calls to amOnPage and submitForm in sequence to simulate and fully test a business process. These pages/forms will insert DB data that a subsequent page/form requires, so there are dynamic data prerequisites between pages within one test.  To use the DB Transaction concept for automatic rollback of data, I understand this must be done at the test level, requiring that all parts of the test (multiple page calls) are done together.  This functionality is not currently available in the Codeception Yii2 Module.
While investigating the Codeception Yii2 Module and Yii2 Client code, I found that the Yii2 module _before function creates $this->app in the module using $this->client->startApp(), and begins a transaction on $this->app->db.  The _after function rolls back this transaction.  However, when doRequest is called many times in a test, $this->client->startApp() is called many times, creating multiple $app objects, and thus many separate db connections that do not have the original transaction enabled.  Thus, the DB records added by functional tests with multiple requests are not rolled back.  If every request did its own DB transaction, then the DB records added/updated by one page request could not be seen by another page request in the same test.
The solution found was to begin a DB Transaction on each of the application's DB Components, save the references to those $dbs in the module to rollback later, pass $dbs into the Yii2 $client, have the $this->client->startApp() function create a new $app and replace all of the DB components with the original ones that have active transactions.  I chose to leave the transactions at the Test level, instead of moving it up to the Suite, so that rollbacks occur sooner.  Then uncommitted DB changes won't carry over across tests when there are a large number of tests to run that have no dependencies.  This may cause a problem for multiple tests with DB data dependencies, but is not a requirement at this time.
Here are some links to public Github Gist files with working code:

Extended Codeception Yii2 Module:
https://gist.github.com/jkovacs618/50f171b709ab13f36437
Extended Codeception Yii2 Client:
https://gist.github.com/jkovacs618/31041c41a455374cddc8

Please look these over, see if there is a better solution to achieve this functionality, and let me know if I am missing something about functional testing.  Consider integrating this concept into the base Yii2 Module and Yii2 Client classes so that the extended classes are not needed.  Thank you.

It was discussed long time ago with me and @qiangxue if we should start and rollback transactions for Yii testing , we agreed that it should be developer issue, since note this cases:

developer can commit transactions due to application runtime;
it becomes very hard to check what actually rolled back since see p1, and it can leave database or other persistence in inconsistent state.

Dont think that it should be implemented in Yii2 module for Codeception, note that you always can implement your own helper and catch _before / _after events to make your own transaction or other cleanup

thanks for your comment, @Ragazzo, closing this then.

@Ragazzo: The Codeception Yii2 Module already supports a config 'cleanup' flag (optional), and when set to true will start a Transaction.  This configuration flag is undocumented though.  I suppose this is only meant for Test function uses of $I->haveRecord() to create DB data and roll back that data, not the data produced in project code being tested.
I see how this feature should be up to the developer according to your points above, and not default functionality.  However, there is little information on best practices in testing with Yii2 and Codeception.  The Dbh module doesn't integrate well with Yii2, or is not well documented how to do so.  It doesn't seem too far fetched that the Yii2 Module could support this with optional configuration settings.

The Codeception Yii2 Module already supports a config 'cleanup' flag (optional), and when set to true will start a Transaction.

Yeah, i know, it was added long time ago by @DavertMik when he was using Yii2, yet i was against that change. Later it was ported ot other fw modules.

However, there is little information on best practices in testing with Yii2 and Codeception.

yes , my fault , i am currnetly a little bit busy , but i will try to add more docs before end of January.

The Dbh module doesn't integrate well with Yii2, or is not well documented how to do so

The point here is that you should use fixtures that are Yii2 feature, see how they are used in FixtureHelper in yii2-avanced. With fixtures and cests if neeed it becomes very easy to manipulate for cleanup, since each fixture actually knows what it should cleanup and you dont need to worry about inconsistencies.


[luigi.six.iteritems] usage removed

Description

py27 tests removed from .travis.yml
luigi.six.iteritems eliminated
luigi.six.iteritems now raises exception on invocation to be sure it's not called

Motivation and Context
#2830
Have you tested this? If so, how?
tests are okay

@honnix
@dlstadther
it seems that travis can't be ran on branches differing from master
could you pls add py2-deprecation into /branches/only in travis.yml ?

@drowoseque added

LGTM. PTAL as well @dlstadther @Tarrasch . We need some extra eyes. Not so sure of test coverage of those contrib code, so never know.

@honnix
@dlstadther
ptal

Sorry I merged the snakebite PR first.

@honnix did it

@honnix
i've resolved conflicts
could you, please review this pr
as well as @dlstadther or @Tarrasch

@drowoseque Please resolve the conflict. Thanks.

@honnix
done


Remove deprecated state restoration

Follow up to #7, as state restoration was only half implemented and no longer actively supported. Better for user of the library to instead restore manually based on NSUserActivity.

@pnuts2 FYI. I'm preparing follow-up PRs for TripKitUI, too. When that's tested and working well, we can bump TGCardVC to 2.0.0.


Support for functions

Why are we doing this work?
To make it simpler to use the plugin
Acceptance

Commonly used functions are available
Docs are updated with the supported functions

What functions should we really support? Who can we ask about it?

We chatted during planning and we were a bit unsure on what are the functions we really want to support. The legacy plugin ships the following functions:

$rate(cols...): converts query results as "change rate per interval"
$columns(key, value): query values as array of [key, value], where key will be used as label
$rateColumns(key, value): a combination of $columns and $rate
$perSecond(cols...): converts query results as "change rate per interval" for Counter-like(growing only) metrics
$perSecondColumns(key, value): a combination of $columns and $perSecond for Counter-like metrics

It's unclear wether those are common use cases on Clickhouse or just a choice made by the developer of the plugin.
@josiahg, do you have insights on this one?

Long-time ClickHouse-Grafana user here. The functions are pretty essential in use cases that go beyond just visualizing a single column.
For me, the $perSecondColumns and $columns are the commonly used ones. Also the $conditionalPredicate is very useful.

@kirederik i'm not sure we need these. Philosophically i think we agreed to move away from creating a sub language and simplifying this through either a query builder and/or query templates and/or improvements in ClickHouse.

@gingerwizard good point
I'll close this one and we can keep an eye for community requests beyond the macros we currently support


Someone I don't follow showed up in my "Following" timeline (without being retweeted)

I think because two people I follow replied to the tweet this showed up in the Following timeline. It didn't have any special header or anything, it just looked like a tweet from someone I follow. Would be nice if this could get filtered out.

Did you refreshed the timeline and checked again?
It happened to me twice already, that sometime "{user} retweeted" isn't shown on the whole timeline till I refreshed it again. It's most probably that, I guess.
I was just looking for such issue before I open one.


feat(java): Implement classId related logic

What does this PR do?

Implementing xlang_spec typeId.
Related issues

https://github.com/apache/incubator-fury/pull/1413
Does this PR introduce any user-facing change?

[ ] Does this PR introduce any public API change?
[ ] Does this PR introduce any binary protocol compatibility change?

Benchmark

Hi @chaokunyang , could you help me check if there is any problem with the implementation logic? If there is no problem, I will handle CI related errors.


Fix typo in train_udpos.sh

Thanks Jannis for the fix. I've marked the PR as ready for Google. It will be merged soon.


Bad scaling due to flooding and overhead of copying packets in limactl

Throughput decreases and cpu usage increases significantly when adding more vms connected to the same socket_vmnet daemon.
Tested using:

host: running iperf3 -c ...
server vm: running iper3 -s
1-4 additional idle vms

vms
bitrate (Gbits/sec)
cpu (%)

1
3.52
51.23

2
2.42
58.17

3
1.22
81.28

4
0.81
93.07

Expected behavior

Performance and cpu usage should remain the same when adding more idle vms
Packets sent to one vm should not be forwarded to other vms
Packets should be copied directly to vz datagram socket in socket_vmnet, bypassing limactl

Why it happens
When we have multiple vms connected to socket_vmnet:

every packet sent from the vmnet interface is forwarded to every vm, instead of the vm with the right mac address.
every packet sent from any vm is forwarded to all other vms, and vmnet inteterface, instead of one of the vm or only vmnet interface
when a packet is forwarded to a vm, it is copied to the vz datagram socket via a socket pair in limactl
packets forwarded from limactl to the vz are copied and processed in the guest, where they are dropped (since the packets are not related to the guest).

 I don't understand why there are so many copies.


Added border around scanning rectangle for scan view

I added your changes but I didn't see anything. How to use new changes?

Hi @halilozel1903 . Please take a pull. Really sorry, Some issue happened from my side and latest changes were not pushed. I just got to know today by your comment only. Please check and let me know if you can see the changes.:-)

How you doin’ ❓ Thanks. 😊 Why don't they accept what you do?

May be Project Maintainers are not active. I hope they can provide feedbacks or suggestions on it. If this can be merged.

Maybe the maintainer @rkistner should have a second maintainer to avoid a no-progress-state like sadly a lot of other projects have ?


luajit -l cltorch -e 'cltorch.test()'   passes but    th -l cltorch -e 'cltorch.test()' fails

Hi, I'm trying to set up cltorch on OSX el capitan on a macbook pro with AMD GPU.
The tests run and pass using luajit -l cltorch -e 'cltorch.test()' but th -l cltorch -e 'cltorch.test()'  fails with the output:
could not load cltorch, skipping
/Users/chris/torch/install/share/lua/5.1/cltorch/init.lua:19: cannot load '/Users/chris/torch/install/lib/lua/5.1/libcltorch.so'
stack traceback:
	[C]: in function 'require'
	/Users/chris/torch/install/share/lua/5.1/cltorch/init.lua:19: in main chunk
	[C]: in function 'require'
	...hris/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:48: in function <...hris/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:48>
	[C]: in function 'xpcall'
	...hris/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:48: in main chunk
	[C]: at 0x010ba9cbd0
[string "cltorch.test()"]:1: attempt to index global 'cltorch' (a nil value)

/Users/chris/torch/install/lib/lua/5.1/libcltorch.so definitely exists.
and the output of clinfo is:
Number of platforms                               1
  Platform Name                                   Apple
  Platform Vendor                                 Apple
  Platform Version                                OpenCL 1.2 (Nov 18 2015 20:45:47)
  Platform Profile                                FULL_PROFILE
  Platform Extensions                             cl_APPLE_SetMemObjectDestructor cl_APPLE_ContextLoggingFunctions cl_APPLE_clut cl_APPLE_query_kernel_names cl_APPLE_gl_sharing cl_khr_gl_event

  Platform Name                                   Apple
Number of devices                                 3
  Device Name                                     Intel(R) Core(TM) i7-4980HQ CPU @ 2.80GHz
  Device Vendor                                   Intel
  Device Vendor ID                                0xffffffff
  Device Version                                  OpenCL 1.2
  Driver Version                                  1.1
  Device OpenCL C Version                         OpenCL C 1.2
  Device Type                                     CPU
  Device Profile                                  FULL_PROFILE
  Max compute units                               8
  Max clock frequency                             2800MHz
  Device Partition                                (core)
    Max number of sub-devices                     0
    Supported partition types                     None
  Max work item dimensions                        3
  Max work item sizes                             1024x1x1
  Max work group size                             1024
  Preferred work group size multiple              1
  Preferred / native vector sizes
    char                                                16 / 16
    short                                                8 / 8
    int                                                  4 / 4
    long                                                 2 / 2
    half                                                 0 / 0        (n/a)
    float                                                4 / 4
    double                                               2 / 2        (cl_khr_fp64)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     Yes
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  Yes
  Double-precision Floating-point support         (cl_khr_fp64)
    Denormals                                     Yes
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  No
  Address bits                                    64, Little-Endian
  Global memory size<PHONE_NUMBER>4 (16GiB)
  Error Correction support                        No
  Max memory allocation<PHONE_NUMBER> (4GiB)
  Unified memory for Host and Device              Yes
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       1024 bits (128 bytes)
  Global Memory cache type                        Read/Write
  Global Memory cache size                        64
  Global Memory cache line                        6291456 bytes
  Image support                                   Yes
    Max number of samplers per kernel             16
    Max size for 1D images from buffer            65536 pixels
    Max 1D or 2D image array size                 2048 images
    Base address alignment for 2D image buffers   1 bytes
    Pitch alignment for 2D image buffers          1 bytes
    Max 2D image size                             8192x8192 pixels
    Max 3D image size                             2048x2048x2048 pixels
    Max number of read image args                 128
    Max number of write image args                8
  Local memory type                               Global
  Local memory size                               32768 (32KiB)
  Max constant buffer size                        65536 (64KiB)
  Max number of constant args                     8
  Max size of kernel argument                     4096 (4KiB)
  Queue properties
    Out-of-order execution                        No
    Profiling                                     Yes
  Profiling timer resolution                      1ns
  Execution capabilities
    Run OpenCL kernels                            Yes
    Run native kernels                            Yes
  Prefer user sync for interop                    Yes
  printf() buffer size                            1048576 (1024KiB)
  Built-in kernels
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  Device Extensions                               cl_APPLE_SetMemObjectDestructor cl_APPLE_ContextLoggingFunctions cl_APPLE_clut cl_APPLE_query_kernel_names cl_APPLE_gl_sharing cl_khr_gl_event cl_khr_fp64 cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_int64_base_atomics cl_khr_int64_extended_atomics cl_khr_3d_image_writes cl_khr_image2d_from_buffer cl_APPLE_fp64_basic_ops cl_APPLE_fixed_alpha_channel_orders cl_APPLE_biased_fixed_point_image_formats cl_APPLE_command_queue_priority

  Device Name                                     Iris Pro
  Device Vendor                                   Intel
  Device Vendor ID                                0x1024500
  Device Version                                  OpenCL 1.2
  Driver Version                                  1.2(Nov 18 2015 20:57:43)
  Device OpenCL C Version                         OpenCL C 1.2
  Device Type                                     GPU
  Device Profile                                  FULL_PROFILE
  Max compute units                               40
  Max clock frequency                             1300MHz
  Device Partition                                (core)
    Max number of sub-devices                     0
    Supported partition types                     None
  Max work item dimensions                        3
  Max work item sizes                             512x512x512
  Max work group size                             512
  Preferred work group size multiple              32
  Preferred / native vector sizes
    char                                                 1 / 1
    short                                                1 / 1
    int                                                  1 / 1
    long                                                 1 / 1
    half                                                 0 / 0        (n/a)
    float                                                1 / 1
    double                                               0 / 0        (n/a)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     No
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  Yes
  Double-precision Floating-point support         (n/a)
  Address bits                                    64, Little-Endian
  Global memory size<PHONE_NUMBER> (1.5GiB)
  Error Correction support                        No
  Max memory allocation                           402653184 (384MiB)
  Unified memory for Host and Device              Yes
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       1024 bits (128 bytes)
  Global Memory cache type                        None
  Image support                                   Yes
    Max number of samplers per kernel             16
    Max size for 1D images from buffer            25165824 pixels
    Max 1D or 2D image array size                 2048 images
    Base address alignment for 2D image buffers   4 bytes
    Pitch alignment for 2D image buffers          32 bytes
    Max 2D image size                             16384x16384 pixels
    Max 3D image size                             2048x2048x2048 pixels
    Max number of read image args                 128
    Max number of write image args                8
  Local memory type                               Local
  Local memory size                               65536 (64KiB)
  Max constant buffer size                        65536 (64KiB)
  Max number of constant args                     8
  Max size of kernel argument                     1024
  Queue properties
    Out-of-order execution                        No
    Profiling                                     Yes
  Profiling timer resolution                      80ns
  Execution capabilities
    Run OpenCL kernels                            Yes
    Run native kernels                            No
  Prefer user sync for interop                    Yes
  printf() buffer size                            1048576 (1024KiB)
  Built-in kernels
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  Device Extensions                               cl_APPLE_SetMemObjectDestructor cl_APPLE_ContextLoggingFunctions cl_APPLE_clut cl_APPLE_query_kernel_names cl_APPLE_gl_sharing cl_khr_gl_event cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_image2d_from_buffer cl_khr_gl_depth_images cl_khr_depth_images cl_khr_3d_image_writes

  Device Name                                     AMD Radeon R9 M370X Compute Engine
  Device Vendor                                   AMD
  Device Vendor ID                                0x1021c00
  Device Version                                  OpenCL 1.2
  Driver Version                                  1.2 (Nov 18 2015 20:53:16)
  Device OpenCL C Version                         OpenCL C 1.2
  Device Type                                     GPU
  Device Profile                                  FULL_PROFILE
  Max compute units                               10
  Max clock frequency                             800MHz
  Device Partition                                (core)
    Max number of sub-devices                     0
    Supported partition types                     None
  Max work item dimensions                        3
  Max work item sizes                             256x256x256
  Max work group size                             256
  Preferred work group size multiple              64
  Preferred / native vector sizes
    char                                                 4 / 4
    short                                                2 / 2
    int                                                  1 / 1
    long                                                 1 / 1
    half                                                 0 / 0        (n/a)
    float                                                1 / 1
    double                                               1 / 1        (cl_khr_fp64)
  Half-precision Floating-point support           (n/a)
  Single-precision Floating-point support         (core)
    Denormals                                     No
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               No
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  Yes
  Double-precision Floating-point support         (cl_khr_fp64)
    Denormals                                     Yes
    Infinity and NANs                             Yes
    Round to nearest                              Yes
    Round to zero                                 Yes
    Round to infinity                             Yes
    IEEE754-2008 fused multiply-add               Yes
    Support is emulated in software               No
    Correctly-rounded divide and sqrt operations  No
  Address bits                                    32, Little-Endian
  Global memory size<PHONE_NUMBER> (2GiB)
  Error Correction support                        No
  Max memory allocation                           536870912 (512MiB)
  Unified memory for Host and Device              No
  Minimum alignment for any data type             128 bytes
  Alignment of base address                       32768 bits (4096 bytes)
  Global Memory cache type                        None
  Image support                                   Yes
    Max number of samplers per kernel             16
    Max size for 1D images from buffer            65536 pixels
    Max 1D or 2D image array size                 2048 images
    Base address alignment for 2D image buffers   256 bytes
    Pitch alignment for 2D image buffers          256 bytes
    Max 2D image size                             16384x16384 pixels
    Max 3D image size                             2048x2048x2048 pixels
    Max number of read image args                 128
    Max number of write image args                8
  Local memory type                               Local
  Local memory size                               32768 (32KiB)
  Max constant buffer size                        65536 (64KiB)
  Max number of constant args                     8
  Max size of kernel argument                     1024
  Queue properties
    Out-of-order execution                        No
    Profiling                                     Yes
  Profiling timer resolution                      37ns
  Execution capabilities
    Run OpenCL kernels                            Yes
    Run native kernels                            No
  Prefer user sync for interop                    Yes
  printf() buffer size                            134217728 (128MiB)
  Built-in kernels
  Device Available                                Yes
  Compiler Available                              Yes
  Linker Available                                Yes
  Device Extensions                               cl_APPLE_SetMemObjectDestructor cl_APPLE_ContextLoggingFunctions cl_APPLE_clut cl_APPLE_query_kernel_names cl_APPLE_gl_sharing cl_khr_gl_event cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics cl_khr_byte_addressable_store cl_khr_image2d_from_buffer cl_khr_depth_images cl_APPLE_command_queue_priority cl_APPLE_command_queue_select_compute_units cl_khr_fp64

NULL platform behavior
  clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...)  Apple
  clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...)   Success [P0]
  clCreateContext(NULL, ...) [default]            Success [P0]
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU)  Success (1)
    Platform Name                                 Apple
    Device Name                                   Intel(R) Core(TM) i7-4980HQ CPU @ 2.80GHz
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU)  Success (2)
    Platform Name                                 Apple
    Device Name                                   Iris Pro
    Device Name                                   AMD Radeon R9 M370X Compute Engine
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR)  No devices found in platform
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM)  <checkNullCtxFromType:2073: create context from type CL_DEVICE_TYPE_CUSTOM : error -30>
  clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL)  Success (3)
    Platform Name                                 Apple
    Device Name                                   Iris Pro
    Device Name                                   AMD Radeon R9 M370X Compute Engine
    Device Name                                   Intel(R) Core(TM) i7-4980HQ CPU @ 2.80GHz

Hi allthetime, yes, I think it's an rpath issue, which I'm currently trying to fix, but not really succeeding yet.
What is rpath?
cltorch has a module called libcltorch.so, which is installed at ~/torch/install/lib/lua/5.1/libcltorch.so.  When it loads, it needs to pull in some other libraries, like libTHCl.dylib, and libclblas.dylib, and a few others.  To do this, on other systems it can read the paths from LD_LIBRARY_PATH variable, but this seems not to work very well on Mac OS X, for various reasons, and is considered generally a Bad Idea, apparently.
The other way it can find them is, at build time, the linker stores the locations of the dependencies.  It can do this using relative or absolute paths.  On MAC OS X, I think it always uses absolute paths (?), but the first bit of such absolute paths can be a special varaible @rpath, which will be replaced at runtime by the current value of @rpath, which is also somehow set by the linker.
Now, I've set up a travis build, and run a few builds, eg https://travis-ci.org/hughperkins/cltorch/builds/113309396 , which all run from .travis.yml file.  And in that build, I'm using otool to examine the various paths stored in libcltorch.so, at build time, by the linker.  Here's how it looks:
https://travis-ci.org/hughperkins/cltorch/builds/113309396#L1024
0.48s$ otool -L ~/torch/install/lib/lua/5.1/libcltorch.so

/Users/travis/torch/install/lib/lua/5.1/libcltorch.so:
	@rpath/libluaT.dylib (compatibility version 0.0.0, current version 0.0.0)
	@rpath/libTHCl.dylib (compatibility version 0.0.0, current version 0.0.0)
	libclBLAS.2.dylib (compatibility version 2.0.0, current version 2.4.0)
	@rpath/libTH.dylib (compatibility version 0.0.0, current version 0.0.0)
	/System/Library/Frameworks/Accelerate.framework/Versions/A/Accelerate (compatibility version 1.0.0, current version 4.0.0)
	/usr/lib/libSystem.B.dylib (compatibility version 1.0.0, current version 1225.1.1)
	libEasyCL.dylib (compatibility version 0.0.0, current version 0.0.0)
	libclew.1.0.0.dylib (compatibility version 1.0.0, current version 0.0.0)
	/usr/lib/libc++.1.dylib (compatibility version 1.0.0, current version 120.1.0)

Do you see? libTHCl.dylib uses @rpath, but libclBLAS.2.dylib does not, and it wont be found at runtime, because it's not in ~/torch/install/lib/lua/5.1, it's actually in the parent of the parent, at ~/torch/install/lib. What is @rpath?  It can be obatined by using otool too:
https://travis-ci.org/hughperkins/cltorch/builds/113309396#L1037
The command "otool -L ~/torch/install/lib/lua/5.1/libcltorch.so" exited with 0.

0.02s$ otool -l ~/torch/install/lib/lua/5.1/libcltorch.so | grep RPATH -A2

          cmd LC_RPATH

      cmdsize 40

         path @executable_path/../lib (offset 12)

--

          cmd LC_RPATH

      cmdsize 48

         path /Users/travis/torch/install/lib (offset 12)

=> it is ~/torch/install/lib, which is what we want.
So, all the libraries which have @rpath in their location are located.  The others are not.  If any of them fail to be located, cltorch fails to load.
As far as why it works with luajit -l cltorch, and not with luajit -e 'require 'cltorch' (or the other way around), that's interesting, that's new information, I'm not quite sure yet ;-)

Oh yes, wiki page on cmake and rpath:

https://cmake.org/Wiki/CMake_RPATH_handling

some other links I've found:

http://cmake.3232098.n2.nabble.com/RPATH-RUNPATH-td6696135.html
http://cmake.blogspot.jp/2012/10/cmake-target-properties.html
https://cmake.org/cmake/help/v3.0/command/add_library.html
https://github.com/agra-uni-bremen/metaSMT/commit/be176cc632777a4a353b6cef2ec30709978d5194

@hughperkins thanks for the quick & informative reply, I'll let you know if I find anything.

(By the way, one option that apparently might work is, create direcotry ~/lib, and copy all these dylibs from ~/torch/install/lib into that directory, or simply symlink it, ie:
ln -s ~/torch/install/lib ~/lib

@hughperkins thanks for the quick & informative reply, I'll let you know if I find anything.

k :-)

@hughperkins nice, that symlink worked! thanks again.

Ok, cool :-)


Support and test Python 3.11 (#122)

Related issue: #122

[ ] Tests written and passed
[x] Documentation and changelog entry written, docs build passed
[ ] All tox checks passed

Just for additional info: the bug was missing lexers in packaging: https://github.com/ipython/ipython/issues/13845


Support + for NdLayouts

If I start with two NdLayouts that each display separately:

I would expect + to adjoin the two NdLayouts into a Layout just as it would any other two collections of four plots, but currently that's an error:
>>> l.HoloMap.Sine_Grating[1::2].layout() + l.HoloMap.I[1::2].layout()
TypeError: initialize_plot() got an unexpected keyword argument 'ranges'

:Layout
   .NdLayout.Sine_Grating :NdLayout   [y]
      :Overlay
         .Image.Sine_Grating :Image   [x,y]   (z)
         .HLine.I            :HLine   [x,y]
   .NdLayout.I            :NdLayout   [y]
      :Curve   [x]   (z)

Can we relax this restriction and make it possible to use NdLayouts in a larger figure?

It might also be useful to have a way to put them into a GridSpace, when two NdLayouts share the same dimension as they do in this case, but I don't know how to express that.

I'm open to relaxing this restriction.
On one hand, new users may get confused if they build certain structures that can be tricky to parse mentally from the visual presentation alone (labeling is the only thing that differentiates an NdLayout from a Layout) but experienced users can also get confused when operations such as + are disallowed when there is no immediately obvious reason why it shouldn't be possible.
The main thing to worry about here is the cols method as each NdLayout is treated as a single element of the overall Layout and you would need to be able to call cols on the NdLayouts themselves (i.e nested calls to cols). I'm not sure how well the layout code can handle this.

My other concern is that the difference in labelling is the only thing that can distinguish a layout from an ndlayout and this isn't a particularly strong visual cue. If we allow a global cols wrapping, then the boundaries between the ndlayouts can get pretty blurred.
For instance, in the screenshot above there could be..
ndlayout + ndlayout
(images + curves)
ndlayout + ndlayout + ndlayout
( image with y:1.075 and 3.025 ) + ( image with y:4.975 and 6.925 ) + curves
...and dozens more datastructures that could look exactly the same.
Some visual cue to differentiate different ndlayouts in the same layout would help a lot e.g a separator to mark the boundaries of the ndlayouts.
Generally ambiguity leads to confusion and I just want some better way of resolving the ambiguity visually, other than relying on the labels being sufficiently different.

I think there are several distinct concerns involved here:

Yes, it would be nice to be able to group a set of related visualizations, such as the NdLayouts here, into a group that is formatted separately from the main layout.  But that's a separate issue that I already proposed in #91, and does not depend on whether what's grouped is an NdLayout or not.  People will want groups of all sorts of things, and there's no reason I can see to limit grouping to NdLayouts (though indeed NdLayouts are probably the most common things one might want to group).

A GridSpace already provides the ability to organize plots into a fixed arrangement, which is not the goal of an NdLayout.  Requiring that a GridSpace be a single coherent unit is very reasonable, because the layout of items in a GridSpace directly indicates a value, in both the X and Y directions, and breaking that organization loses information.  And so I'd personally also vote (beyond the topic of this particular issue) for a GridSpace to be ok to lay out with other items, being treated as a single item with its own internal formatting (though that's an aside). The layout of items in an NdLayout, in contrast, matters only in one dimension, and thus .cols() is in no way breaking such an ordering, no more than having newlines on a page of (linear) text is.

Conceptually, I don't think we need to think of the items generated by an NdLayout as being any different from those constructed by hand using Layout.  One can always make an NdLayout by constructing each frame of it, titling them properly, and concatenating them.  There need not be any difference between doing it that way or by calling .layout() -- the result is an ordered list of visualizable data, in either case, and either way what it is needs to be clearly labeled for it to be useful. So I don't think there's any issue with .cols(), and I'd even argue that if the result of a method called .layout() doesn't behave like any other Layout, including supporting +, it's a bug.

I'd love to have support for grouping, but meanwhile, I don't see why we should be treating the result of making an NdLayout as being anything less than or more restricted than any other Layout; it's just a list of displayable things.

I think in the end we decided that we should allow + between NdLayouts although there are several important issues to address after that (e.g grouping). The cols method then works across elements across containers and will be part of a future API that we anticipate will help solve the issue of grouping elements together in different ways within layouts.

I thought we had decided that it would be safer to require a helper method that constructs a Layout out of the NdLayout's Elements, breaking them up so that they can then be flowed into a Layout at will, to preserve the ability to treat NdLayouts as unbreakable groups in the future.  But I don't know how that would be implemented, so maybe that wasn't the real conclusion.


Show notification when something is copied into clipboard

Why
It is currently impossible to tell if anything has happened at all when copying some path.
There are times that for some reason path is not copied, but the user wound't notice until they try to paste somewhere else.
What
Just simply show a notification (that disappears in 2 sec).

Looks good! Thanks.


Hello

Hello, can this pass the cloudflare test?

It can only bypass CF(default)

How many connections can he attack

How many connections can he attack

About this Pummel can only send about 1.3k ops
I have another Pummel version that can send over 2k pps

How can I contact you?Telegram？

How can I contact you?Telegram？

I will not make my Tg known to public
But you can contact me by Discord HC#3341
If you need my Tg I will pm you in discord

OK


feat(rewrite-with-pipe): add regex action

I am sorry, but I may simplify the unit tests. I don't think it's necessary to test the native regex functionality since it's not controlled by our source code. I prefer to just test that the passed regex is used to validate the input.


not include credential options for fileshare namespace

As title.
solves issue:
https://github.com/microsoft/spring-cloud-azure/issues/937

Hi @jialigit, will the property spring.cloud.azure.storage.fileshare.credential.* be in the file _configuration-properties-all.adoc?
This PR should contain the file _configuration-properties-azure-storage-file-share. adoc that was changed after executing the command mvn clean install -Pdoc. If the property spring.cloud.azure.storage.fileshare.credential.* will not be in the file _configuration-properties-all.adoc then it should also be included after the update.

OK, Let's use only one PR to update them all at once.

Hi @jialigit, the pr to update spring-cloud-azure-appendix in MS Docs has been merged, please create PR update spring-cloud-azure-appendix.

Yes. This properties(AzureStorageFileShareProperties) inherit from the parent properties, but some of them are not available for this service. As for now, we can't modify the structure of the class which will bring breaking changes to the API, so here we just only need to suppress the properties file generation rule.

This is the PR update the options in MS doc: https://github.com/MicrosoftDocs/azure-dev-docs-pr/pull/3279
We will merge the update into MS doc first mannualy, and then merge this PR into spring-cloud-azure repo. But the azure-dev-docs-pr repo may not merge it very quickly, so this PR is likely be blocking here for a few days.

As PR : #3279 is merged, we merge this to sync the changes.


[Plugin] Jeager/Zipkin

Summary
Once developers find out that their application has an issue, it is very beneficial to see the application's traces. This can help identify the source of the issue.
Motivation
I am using Istio service mesh (on top of k8s) along with Jeager tracing.
I often depend on the tracing information to find the source of a particular issue or latency.
I believe that ability for developers to see traces of their application will be beneficial in diagnosing their application.

Re-opening since plugin suggestion issues are now exempt from stalebot.

Would be nice if there would be a complete istio plugin, which would show data from jaeger, kiali and the functionality a certain application is using from istio. Think about circuit breaking, fault injection and stuff.

Yeah, those types of view when you get collected / correlated data from related systems gathered into one place, can be where the most value can be had for users.

We are actually builing an observability plugin which correlates traces with logs, and metrics. However, we did not set out to build a [dynnatrace,jaeger,...] clone as these tools do a perfectly good job of exploring traces. What we did is start from bottom up and watch for logged error or anomalies and then display these traces only. IF you need to do further exploring then you can follow a link to the source tool (i.e. hypertrace). We basically source logs, traces and metrics from different tools via kafka and normalize it into OpenTelemetetry models (Log,Trace,Metric) Then we display it in backstage.
Backstage has knowledge about your applications and can automatically filter for you. A simple example is shown here where the Resource name is added to the filter.
I am working on open sourcing this as soon as possible.
https://user-images.githubusercontent.com/152763/151332262-f7e88a49-e61c-4e96-920b-8f3244563a84.mp4

What do you think about integrating SigNoz?

cc. @tacigar

Are there something new? Do we have jaeger backstage plugin?