HDFS-16934. org.apache.hadoop.hdfs.tools.TestDFSAdmin#testAllDatanodesReconfig regression

JIRA: HDFS-16934. org.apache.hadoop.hdfs.tools.TestDFSAdmin#testAllDatanodesReconfig regression

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_ Other Tests _

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/patch-unit-hadoop-hdfs-project_hadoop-hdfs.txt
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317m 40s

Reason
Tests

Failed junit tests
hadoop.hdfs.TestDFSStripedInputStream

Subsystem
Report/Notes

Docker
ClientAPI=1.42 ServerAPI=1.42 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/2/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/5434

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uname
Linux 8d5495247d8f 4.15.0-200-generic #211-Ubuntu SMP Thu Nov 24 18:16:04 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux

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Personality
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git revision
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Default Java
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Multi-JDK versions
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Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/2/testReport/

Max. process+thread count
3241 (vs. ulimit of 5500)

modules
C: hadoop-hdfs-project/hadoop-hdfs U: hadoop-hdfs-project/hadoop-hdfs

Console output
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/2/console

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ClientAPI=1.42 ServerAPI=1.42 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/1/artifact/out/Dockerfile

GITHUB PR
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uname
Linux a48dbd54d303 4.15.0-200-generic #211-Ubuntu SMP Thu Nov 24 18:16:04 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux

Build tool
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dev-support/bin/hadoop.sh

git revision
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Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/1/testReport/

Max. process+thread count
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modules
C: hadoop-hdfs-project/hadoop-hdfs U: hadoop-hdfs-project/hadoop-hdfs

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https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/1/console

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205m 32s
/patch-unit-hadoop-hdfs-project_hadoop-hdfs.txt
hadoop-hdfs in the patch passed.

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0m 51s

The patch does not generate ASF License warnings.

312m 25s

Reason
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Failed junit tests
hadoop.hdfs.server.datanode.TestDirectoryScanner

Subsystem
Report/Notes

Docker
ClientAPI=1.42 ServerAPI=1.42 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/3/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/5434

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dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux b482bad4c369 4.15.0-200-generic #211-Ubuntu SMP Thu Nov 24 18:16:04 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / d2846c2703df45db725d704bbe864b9d9b86966d

Default Java
Private Build-1.8.0_352-8u352-ga-1~20.04-b08

Multi-JDK versions
/usr/lib/jvm/java-11-openjdk-amd64:Ubuntu-11.0.17+8-post-Ubuntu-1ubuntu220.04 /usr/lib/jvm/java-8-openjdk-amd64:Private Build-1.8.0_352-8u352-ga-1~20.04-b08

Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/3/testReport/

Max. process+thread count
2989 (vs. ulimit of 5500)

modules
C: hadoop-hdfs-project/hadoop-hdfs U: hadoop-hdfs-project/hadoop-hdfs

Console output
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/3/console

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@steveloughran Can you help review this pr? Thank you very much!

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3m 22s

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22m 34s

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the patch passed

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1m 20s

the patch passed with JDK Ubuntu-11.0.17+8-post-Ubuntu-1ubuntu220.04

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1m 20s

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1m 13s

the patch passed with JDK Private Build-1.8.0_352-8u352-ga-1~20.04-b08

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1m 13s

the patch passed

+1 :green_heart:
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0m  0s

The patch has no blanks issues.

+1 :green_heart:
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0m 51s

the patch passed

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1m 22s

the patch passed

+1 :green_heart:
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0m 50s

the patch passed with JDK Ubuntu-11.0.17+8-post-Ubuntu-1ubuntu220.04

+1 :green_heart:
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1m 25s

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202m 36s
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hadoop-hdfs in the patch passed.

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0m 50s

The patch does not generate ASF License warnings.

310m 19s

Reason
Tests

Failed junit tests
hadoop.hdfs.server.namenode.TestFsck

Subsystem
Report/Notes

Docker
ClientAPI=1.42 ServerAPI=1.42 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/4/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/5434

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux 565d7392aa5e 4.15.0-200-generic #211-Ubuntu SMP Thu Nov 24 18:16:04 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / b5292e830b010bc2cff220b916544ce49bd5b2f9

Default Java
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Multi-JDK versions
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Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/4/testReport/

Max. process+thread count
2900 (vs. ulimit of 5500)

modules
C: hadoop-hdfs-project/hadoop-hdfs U: hadoop-hdfs-project/hadoop-hdfs

Console output
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/4/console

versions
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trunk passed with JDK Ubuntu-11.0.17+8-post-Ubuntu-1ubuntu220.04

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3m 29s

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22m 53s

branch has no errors when building and testing our client artifacts.

_ Patch Compile Tests _

+1 :green_heart:
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1m 21s

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1m 17s

the patch passed with JDK Ubuntu-11.0.17+8-post-Ubuntu-1ubuntu220.04

+1 :green_heart:
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1m 17s

the patch passed

+1 :green_heart:
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1m 13s

the patch passed with JDK Private Build-1.8.0_352-8u352-ga-1~20.04-b08

+1 :green_heart:
javac
1m 13s

the patch passed

+1 :green_heart:
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0m  0s

The patch has no blanks issues.

-0 :warning:
checkstyle
0m 51s
/results-checkstyle-hadoop-hdfs-project_hadoop-hdfs.txt
hadoop-hdfs-project/hadoop-hdfs: The patch generated 1 new + 0 unchanged - 0 fixed = 1 total (was 0)

+1 :green_heart:
mvnsite
1m 18s

the patch passed

+1 :green_heart:
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0m 50s

the patch passed with JDK Ubuntu-11.0.17+8-post-Ubuntu-1ubuntu220.04

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1m 26s

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+1 :green_heart:
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3m 17s

the patch passed

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shadedclient
22m 33s

patch has no errors when building and testing our client artifacts.

_ Other Tests _

-1 :x:
unit
212m 14s
/patch-unit-hadoop-hdfs-project_hadoop-hdfs.txt
hadoop-hdfs in the patch passed.

+1 :green_heart:
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0m 49s

The patch does not generate ASF License warnings.

318m 19s

Reason
Tests

Failed junit tests
hadoop.hdfs.server.datanode.TestDirectoryScanner

hadoop.hdfs.server.namenode.ha.TestObserverNode

Subsystem
Report/Notes

Docker
ClientAPI=1.42 ServerAPI=1.42 base: https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/5/artifact/out/Dockerfile

GITHUB PR
https://github.com/apache/hadoop/pull/5434

Optional Tests
dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

uname
Linux 17457753e6f3 4.15.0-200-generic #211-Ubuntu SMP Thu Nov 24 18:16:04 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/bin/hadoop.sh

git revision
trunk / 45c2a08193920c45906836f965b1f37491ed7fdb

Default Java
Private Build-1.8.0_352-8u352-ga-1~20.04-b08

Multi-JDK versions
/usr/lib/jvm/java-11-openjdk-amd64:Ubuntu-11.0.17+8-post-Ubuntu-1ubuntu220.04 /usr/lib/jvm/java-8-openjdk-amd64:Private Build-1.8.0_352-8u352-ga-1~20.04-b08

Test Results
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/5/testReport/

Max. process+thread count
3281 (vs. ulimit of 5500)

modules
C: hadoop-hdfs-project/hadoop-hdfs U: hadoop-hdfs-project/hadoop-hdfs

Console output
https://ci-hadoop.apache.org/job/hadoop-multibranch/job/PR-5434/5/console

versions
git=2.25.1 maven=3.6.3 spotbugs=4.2.2

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checkstyle failing on an unused import; other than that I'm happy -the assertj collection asserts are so much better for asserting on collections and debugging their failures.
+1 pending the checkstyle fix

Thank you very much for your help to review pr! I will continue to use assertj to complete the unit test.

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dupname asflicense compile javac javadoc mvninstall mvnsite unit shadedclient spotbugs checkstyle codespell detsecrets

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[BUG?] Stuck mining “air”/“nothing”

I am developing a bot, that is supposed to find some diamond ore and mine it for me, however the bot often gets stuck swinging its pickaxe, but breaking no block (somewhat similar to what the bot does in #54).
The code I used is basically as close as possible to what the example in the README.MD is. Is there a fix for this issue, or is there a workaround of some sort?
Thanks in advance.

facing the same issue.

I am developing a bot, that is supposed to find some diamond ore and mine it for me, however the bot often gets stuck swinging its pickaxe, but breaking no block (somewhat similar to what the bot does in #54).
The code I used is basically as close as possible to what the example in the README.MD is. Is there a fix for this issue, or is there a workaround of some sort?
Thanks in advance.

facing the same issue, only for diamond tho, not for any other ore or block

#137


Mina Metrics: Peers is always zero.

Environment

Version : Testnet 5.0 (mina-testnet-postake-medium-curves=0.2.2-b7eff8e)
OS : Ubuntu 18.04
10 nodes were operated in the same environment, but occurred in two.

Issue

Mina Metrics : 0 peers
Mina GraphQL(3085 port) : 43 peers
coda client status : 43 peers

Only this node has a Mina Metrics value always zero.

Duplicate of https://github.com/MinaProtocol/mina/issues/6022

Duplicate of https://github.com/MinaProtocol/mina/issues/6022

Closing this issue as it is stale for a long time.


[Windows] Implement support for native notifications.

Ask permissions to the user (previously it was not granted). Android
will not grant permissions because it works differently.
Hook up the notification support in content to the Windows C++ API. It
comes with some limitation such as not being able to have URL based
icons part of the notification. Workaround is to copy it in a temporary
file before firing the notification.
Windows 7 is not supported as there is no notification center.

Known limitations which I plan to fix in a following patch : persistent
support (aka it says in the notification center), activation even when
Crosswalk is closed.
BUG=XWALK-4990

@pozdnyakov PTAL

lgtm with nits


ERROR: unable to download video data: HTTP Error 404: (when downloading Twitch clips)

Checklist

[x] I'm reporting a broken site support
[x] I've verified that I'm running youtube-dl version 2021.05.16
[x] I've checked that all provided URLs are alive and playable in a browser
[x] I've checked that all URLs and arguments with special characters are properly quoted or escaped
[x] I've searched the bugtracker for similar issues including closed ones

Verbose log

[debug] System config: []
[debug] User config: []
[debug] Custom config: []
[debug] Command-line args: ['-v', 'https://www.twitch.tv/loltyler1/clip/BlightedDrabLasagnaOptimizePrime']
[debug] Encodings: locale cp1252, fs mbcs, out cp437, pref cp1252
[debug] youtube-dl version 2021.05.16
[debug] Python version 3.4.4 (CPython) - Windows-10-10.0.19041
[debug] exe versions: none
[debug] Proxy map: {}
[twitch:clips] BlightedDrabLasagnaOptimizePrime: Downloading clip GraphQL
[debug] Default format spec: best/bestvideo+bestaudio
[debug] Invoking downloader on 'https://production.assets.clips.twitchcdn.net/AT-cm%7C956442975.mp4'
ERROR: unable to download video data: HTTP Error 404:
Traceback (most recent call last):
  File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\ytdl-org\tmp8rlhijs0\build\youtube_dl\YoutubeDL.py", line 1976, in process_info
  File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\ytdl-org\tmp8rlhijs0\build\youtube_dl\YoutubeDL.py", line 1915, in dl
  File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\ytdl-org\tmp8rlhijs0\build\youtube_dl\downloader\common.py", line 366, in download
  File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\ytdl-org\tmp8rlhijs0\build\youtube_dl\downloader\http.py", line 351, in real_download
  File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\ytdl-org\tmp8rlhijs0\build\youtube_dl\downloader\http.py", line 116, in establish_connection
  File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\ytdl-org\tmp8rlhijs0\build\youtube_dl\downloader\http.py", line 110, in establish_connection
  File "C:\Users\dst\AppData\Roaming\Build archive\youtube-dl\ytdl-org\tmp8rlhijs0\build\youtube_dl\YoutubeDL.py", line 2288, in urlopen
  File "C:\Python\Python34\lib\urllib\request.py", line 470, in open
  File "C:\Python\Python34\lib\urllib\request.py", line 580, in http_response
  File "C:\Python\Python34\lib\urllib\request.py", line 508, in error
  File "C:\Python\Python34\lib\urllib\request.py", line 442, in _call_chain
  File "C:\Python\Python34\lib\urllib\request.py", line 588, in http_error_default
urllib.error.HTTPError: HTTP Error 404:

Description

I have been using youtube-dl in my python project daily for the past few months to download clips from the Twitch website, and it has been working perfectly ever since I started with it. I did not change anything in my code at all, nor any other systems, but a few days ago, youtube-dl just randomly became unable to download clips from Twitch, it just keeps giving me this error message. I assumed it was just an update issue, so I updated youtube-dl, but it still does not work. I tried downloading a video by giving it a Youtube link instead of a Twitch link and it works, so it seems like the problem is only related to Twitch (and maybe other sites I did not test). I tried the same code on two different systems and they both did not work, so I do not think it is a system issue either. I attached the basic code that I am trying to get working below. This code is standard, and worked in the past, but I don't know if there is something that I should change in my options, or it that even is the issue. I also attached the output of the code into the console to see the error message easier. Any help would be greatly appreciated. Thank you.

import youtube_dl
url = "https://www.twitch.tv/loltyler1/clip/BlightedDrabLasagnaOptimizePrime"
try:
ydl_opts = {  # options for downloading clip
'format': 'best',  # best quality
'outtmpl': "twitch_clip.mp4",  # downloaded clip file name
}
with youtube_dl.YoutubeDL(ydl_opts) as ydl:
ydl.download([url])
except Exception:
print("Error downloading twitch clip")
print()

Link to original issue? Tried to search with 'is:issue is:open twitch' and did not find anything related to this.

From what I saw on the discussion posts, it seems like the fix was created, but has it been "updated" yet because I still get the same error message when I try to download the clip. I also tried updating youtube-dl in python, but it says it is already up to date.

ytdl doesn't auto-release even the "secret" compilations by GitHub Actions cuz the project's 100% Open Source Python project, so if you wanna use the fix before an official release you can go to the respective commit and click the 'Browse Files' button in the top right to bring yourself to the file tree, then you need to download the 'youtube_dl' folder and execute the ZIP (assuming the '__main__.py' is in the root) or the 'youtube_dl' folder or the '__main__.py' with Python.
Or, download the one from the 'master' branch instead of the specific commit.
Obviously the version reported that way is a lie until an official release.
All of these are valid:
REM The folder:
# python I:\_DOWNLOADS_\youtube_dl --version
2021.05.16

REM The main file:
# python I:\_DOWNLOADS_\youtube_dl\__main__.py --version
2021.05.16

REM The folder with the main file in the root:
# python I:\_DOWNLOADS_\youtube_dl.zip --version
2021.05.16


Please add Ray framework integration for sentry/apm.

Problem Statement
https://www.ray.io/
I want to annotate that kind of code with spans:
import ray
import os
import time
import sentry_sdk
import random
import asyncio
from sentry_sdk.integrations.asyncio import AsyncioIntegration

logging.basicConfig(level=logging.DEBUG)

def step1():
    with sentry_sdk.start_span(description="step1"):
        time.sleep(random.randint(200,500)/1000.)
def step2():
    with sentry_sdk.start_span(description="step2"):
        time.sleep(random.randint(200,500)/1000.)
def step3():
    with sentry_sdk.start_span(description="step3"):
        time.sleep(random.randint(200,500)/1000.)

@ray.remote
def retrieve_task(item):
    step1()
    step2()
    step3()
    return 1

async def main():
    sentry_sdk.init(
        dsn=os.getenv('SENTRY_DSN'),
        traces_sample_rate=1.0,
        integrations=[
            AsyncioIntegration(),
        ],
    )
    #---
    ray.init()
    with sentry_sdk.start_transaction(op="task", name="example ray task transaction"):
        object_references = [
            retrieve_task.remote(item) for item in range(8)
        ]
        data = ray.get(object_references)
        print(data)

if __name__ ==  '__main__':
    asyncio.run(main())

But I only see one big transaction trace without those 3 spans.
Solution Brainstorm
I think new integration needs to be done.

https://www.ray.io/

Hey @dPeS !
Thanks for bringing this up!
I guess the problem is that the step*() functions are run in another process or something like this (don't know how Ray works) And that the tracing data are not propagated to the other process thus the spans can not be attached to the transaction you create...

Lets test how much demand there is:
If you want to see us support Ray, please "Thumb up" this issue!

I guess the problem is that the step*() functions are run in another process or something like this (don't know how Ray works) And that the tracing data are not propagated to the other process thus the spans can not be attached to the transaction you create...
@antonpirker not the only problem - in those "remote" ray workers sentry isn't initialized - that's for starter.

@szokeasaurusrex Hey I made PR with Ray integration, it handles tracing propagation to ray cluster, feedback is more than welcome!

Thanks @glowskir for the integration! We will have a look sometime soon. Can not promise any ETA yet.

@antonpirker is it planned to merge this PR? ray is becoming more and more popular, would be great to use sentry with it.

@leokster Thanks for reaching out, I will try to look into this later today

@dPeS the Ray integration has been released in Sentry SDK version 2.13.0:
https://github.com/getsentry/sentry-python/releases/tag/2.13.0
Thanks again for the great work! 🥇


glx: Unbind the context if it's the current one

Sorry if the comment was for a reason I'm not aware of.

Thanks!
The other problem is that a context can be binded in a thread different from the thread where the window is being destroyed, but we have no way to know that.
Anyway, I'm merging this as it can't hurt.


The application leaves *.parts files in downloads directory

It happens if you exclude some files from the torrent and even if they are completely downloaded, *.parts are still persists. I think it would be better to store these files in the %temp% folder.

This is still an issue. @nxrighthere, why did you close this?


commonsDaemon: 1.3.1 -> 1.3.3

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/metapackage/commons-daemon/versions.
meta.description for commonsDaemon is: "Apache Commons Daemon software is a set of utilities and Java support classes for running Java applications as server processes."
meta.homepage for commonsDaemon is: "https://commons.apache.org/proper/commons-daemon"
meta.changelog for commonsDaemon is: ""
Updates performed

Version update

To inspect upstream changes
Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 1.3.2 in filename of file in /nix/store/cgawrzwr2p73lw9aw5q85k21082a5plh-commons-daemon-1.3.2

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

3 total rebuild path(s)

3 package rebuild(s)

First fifty rebuilds by attrpath
commonsDaemon
jsvc
unifi-video

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/cgawrzwr2p73lw9aw5q85k21082a5plh-commons-daemon-1.3.2 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A commonsDaemon https://github.com/r-ryantm/nixpkgs/archive/0cb2b03f0cca20b78a167b61b31b7183f11a3632.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/cgawrzwr2p73lw9aw5q85k21082a5plh-commons-daemon-1.3.2
ls -la /nix/store/cgawrzwr2p73lw9aw5q85k21082a5plh-commons-daemon-1.3.2/bin

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

2 packages built:

commonsDaemon
jsvc

Maintainer pings
cc @rsynnest for testing.

Automatic update generated by nixpkgs-update tools. This update was made based on information from https://repology.org/metapackage/commons-daemon/versions.
meta.description for commonsDaemon is: "Apache Commons Daemon software is a set of utilities and Java support classes for running Java applications as server processes."
meta.homepage for commonsDaemon is: "https://commons.apache.org/proper/commons-daemon"
meta.changelog for commonsDaemon is: ""
Updates performed

Version update

To inspect upstream changes
Impact

Checks done (click to expand)

built on NixOS
The tests defined in passthru.tests, if any, passed
found 1.3.3 in filename of file in /nix/store/ck4y9n6hsq2ch7bfq8hmg52h45pvq4c3-commons-daemon-1.3.3

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

3 total rebuild path(s)

3 package rebuild(s)

First fifty rebuilds by attrpath
commonsDaemon
jsvc
unifi-video

Instructions to test this update (click to expand)

Either download from Cachix:
nix-store -r /nix/store/ck4y9n6hsq2ch7bfq8hmg52h45pvq4c3-commons-daemon-1.3.3 \
  --option binary-caches 'https://cache.nixos.org/ https://nix-community.cachix.org/' \
  --option trusted-public-keys '
  nix-community.cachix.org-1:mB9FSh9qf2dCimDSUo8Zy7bkq5CX+/rkCWyvRCYg3Fs=
  cache.nixos.org-1:6NCHdD59X431o0gWypbMrAURkbJ16ZPMQFGspcDShjY=
  '

(The Cachix cache is only trusted for this store-path realization.)
For the Cachix download to work, your user must be in the trusted-users list or you can use sudo since root is effectively trusted.
Or, build yourself:
nix-build -A commonsDaemon https://github.com/r-ryantm/nixpkgs/archive/f4170e0ab28461d9884b27b9aef648edf498fc8a.tar.gz

After you've downloaded or built it, look at the files and if there are any, run the binaries:
ls -la /nix/store/ck4y9n6hsq2ch7bfq8hmg52h45pvq4c3-commons-daemon-1.3.3
ls -la /nix/store/ck4y9n6hsq2ch7bfq8hmg52h45pvq4c3-commons-daemon-1.3.3/bin

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

2 packages built:

commonsDaemon
jsvc

Maintainer pings
cc @rsynnest for testing.

@ofborg build commonsDaemon jsvc


test: DONT-MERGE try build convert.bats inline

What type of PR is this?

Which issue does this PR fix:
What does this PR do / Why do we need it:
If an issue # is not available please add repro steps and logs showing the issue:
Testing done on this change:

Automation added to e2e:

Will this break upgrades or downgrades?
Does this PR introduce any user-facing change?:

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

https://github.com/project-stacker/stacker/actions/runs/6193833107/job/16815934794?pr=503
^ leaving this as evidence of a successful run.
Stripping the commit on top so we can merge.

https://github.com/project-stacker/stacker/actions/workflows/nightly.yaml
^ has been passing now. Stashing this PR for now.


Help with issue

Hi, just wondering what this errors are about.  Just installed via homebrew and tested with random YouTube Url.
% youtube-dl -F https://youtu.be/RY9O_kvU-JY
[youtube] RY9O_kvU-JY: Downloading webpage
ERROR: Unable to extract uploader id; please report this issue on https://yt-dl.org/bug . Make sure you are using the latest version; see  https://yt-dl.org/update  on how to update. Be sure to call youtube-dl with the --verbose flag and include its complete output.
This was when I right clicked copied the url from the video.
% youtube-dl -F https://www.youtube.com/watch?v=RY9O_kvU-JY
zsh: no matches found: https://www.youtube.com/watch?v=RY9O_kvU-JY
This is the same video, address copied from browser address bar.
This happens with all videos.
youtube-dl on MacOs Ventura.
Thank you.

Search the bugtracker for similar bug reports including closed ones.
https://github.com/ytdl-org/youtube-dl/issues?q=Unable+to+extract+uploader+id
And:
Read this before opening a new issue

Known issues, fixed in git master code:

YouTube: Unable to extract uploader id

Quote the 'URL'. The zsh shell is sensitive to ?.


Can I use a parameter bigger than 20MB in one call

I use a grpc call like
Status status = stub_->GetFeature(&context, point, feature);
And I want to use large point and feature instances bigger than 20MB.
I set the maxmessagesize with
ServerBuilder builder;
builder.SetMaxMessageSize(4000000000);
But it does not work, its error message is like this:
GetFeature rpc failed. error code: 13 error message: {"created":"@1472189931.403060508","description":"RST_STREAM","file":"src/core/ext/transport/chttp2/transport/frame_rst_stream.c","file_line":107,"http2_error":2}
Are there any setting to set for this? or it can not use such large parameter?

well, I find the answer, but I must change the code. have some method no need to rewrite source code?

Max message size is enforced for receiving, not sending. So changing the max message size on the server should resolve the issue.
gRPC is very fine with larger message sizes, but we want applications to be aware they may receive large messages.

well, I find the answer, but I must change the code. have some method no need to rewrite source code?

No. The default is now 4MB, and if you want larger you need to override it. What code change made it work?

/grpc-master/src/core/lib/surface/channel.c DEFAULT_MAX_MESSAGE_LENGTH
this one parameter must be changed, or I can not transfer large parameter.

@yang-g, is there some bug with ServerBuilder.SetMaxMessageSize()?

@markdroth does your pr https://github.com/grpc/grpc/pull/7846 resolve this? Thanks.

I doubt that my PR resolves this.  The PR doesn't really change this check; it just moves it from one place in the code to another.
Looking at the code, though, I don't see why DEFAULT_MAX_MESSAGE_LENGTH needs to be changed.  Setting the value via ServerBuilder::SetMaxMessageSize() should work fine.
Let me see if I can put together a quick test to reproduce this.

@psnbbgy, I can't reproduce this problem.
I have a client that sends a 10MiB request to the server.  When I run the server without overriding max message size, the client fails with the error you're seeing.  However, when I call ServerBuilder::SetMaxMessageSize() to set the limit to 20MiB, the call succeeds.
Are you certain that you're setting the max message size on the server that your client is sending the request to?

@markdroth , I think my setting is wrong, I have set the max message size to<PHONE_NUMBER>, it is out of the int range, and when I set it to<PHONE_NUMBER>, it success.
and thank you for replying.
BTW can the grpc support the PB larger than 2GB?

It looks like our current API can't do that, because we encode the max message size as an int, so the maximum supported value is<PHONE_NUMBER>.  Do you actually need to use a max size larger than that?  If so, we might need to make some API changes.
@ctiller, what do you think about changing channel args to use long instead of int?

We could, and we'd get to 4GiB and need a major revision number change on
our C API. At which point I'd fall back to: if your current problem doesn't
fit in 2GiB, your future problem isn't solved with 4GiB, and you probably
want to change some usage of the APIs.
I'd strongly encourage a design rethink here: aim for much smaller messages
(kilobytes to megabytes) and leverage streaming.
gRPC currently needs to hold the entire serialized message in memory before
deserialization, and so with multi gigabyte messages you're holding huge
amounts of memory hostage, especially compared to a stream.
On Tue, Aug 30, 2016, 7:17 AM Mark D. Roth<EMAIL_ADDRESS>wrote:

It looks like our current API can't do that, because we encode the max
message size as an int, so the maximum supported value is<PHONE_NUMBER>. Do
you actually need to use a max size larger than that? If so, we might need
to make some API changes.
@ctiller https://github.com/ctiller, what do you think about changing
channel args to use long instead of int?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/grpc/grpc/issues/7882#issuecomment-243453558, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AJpudahaLISizxwrUuFVaw7Vk7SPcaljks5qlDthgaJpZM4JtxBn
.

@markdroth our Algorithm engineer has a idea about this. Maybe stream is a good idea, because when the PB size is above 1.5GB , the server always kill my process, and change the API may not help this.

Okay, then I'm going to close this issue.  Please let us know if you need anything else.


Update hugin to 2016.2.0

After making all changes to the cask:

[x] brew cask audit --download {{cask_file}} is error-free.
[x] brew cask style --fix {{cask_file}} left no offenses.
[x] The commit message includes the cask’s name and version.

Thank you for the contribution. It was merged directly as bc198cd9aa86bc19ccc95de9c90812cf77b2c5b8. Your contribution is still credited to you.


Enhancement for Compact JSON

The current implementation seems to yield a pretty printed output of the ECS JSON. Would it be possible to optionally configure the layout to output compact JSON?
Perhaps it would be valuable to add analogous features with the same capability and intent as those related to the "compact", "eventEol" and "endOfLine" etc settings which are available on the OEM JSONLayout.
See https://logging.apache.org/log4j/2.x/manual/layouts.html where pretty print vs compact format is discussed.

I a bit confused. There is no option for pretty printing in this library. By default, its one line per event aka nd-json.

As an example, when you have stackTraceAsArray=true, multiple newline characters are included (one after each stack trace element). I was thinking that these newlines are included to make the JSON human readable.

If you don’t like the new lines just leave the setting at the default value false. Am I missing something?

I would only offer that the newlines are superfluous and perhaps mildly inefficient if the JSON is not read by a human consumer. And, also, perhaps it is confusing for consumer that the layout produces nd-json under some selected configuration options, but not under others.

And, also, perhaps it is confusing for consumers that the layout produces nd-json under some selected configuration options, but not under others.

Maybe this is just a naming issue. The only reason there is a stackTraceAsArray=true is to enhance human readability. It's not really pretty printing as that usually means that the JSON is formatted so that each property is in a new line.
There is no use case where you would set stackTraceAsArray=true but have it all in one line. In fact, if you set this option, you'll have to reverse the effect with a script processor:
https://github.com/elastic/ecs-logging-java/blob/master/README.md#when-stacktraceasarray-is-enabled
        function process(event) {
            event.Put("error.stack_trace", event.Get("error.stack_trace").join("\n"));
        }

The use case would be one where the consumer software would like to persist and subsequently retrieve/format/present/analyze the stack in its original form (with each stack trace element as a distinctly identifiable piece of data). Yes, absolutely, you can do this as well by splitting the very large string on the newline character. The same result can be achieved in the status quo implementation. However, It would be preferable to avoid a split operation on very large strings if possible. Giving the consumer the option to take either approach might be considered if the effort to offer it is minimal/practical.


Clarify pubspec.yaml whitespace errors in pub.

This issue was originally filed by @butlermatt

When creating a pubspec.yaml file in the editor, use tab to delimit the file:
==sample file==
name: sampleFile
dependencies:
    unittest:
        sdk: unittest
==end sample file==
When trying to run pub install, receive a cryptic error:
Syntax error on line 3, column 2: invalid YAML in mapping value
In this case it is because the editor insert full tabs instead of the two-space delimiter pub expects.
Is it possible to create an error message that has clearer syntax? Or allow any whitespacing as long as its consistent? (ie, tabs, 4 spaces, 2 spaces, etc)
Will create a separate bug for editor support for tab spacing / autoindent

This issue has been moved to dart-lang/pub#79.


Add lints checking for underscores in labels pre-and-post CABF 1.6.2

In the interest of moving #646 over the finish line (@CBonnell because I don't think I can add you as a reviewer), I believe that it would be prudent to add two lints regarding the presence of underscores in DNS lables.

Ballot SC12 sunsetted the permissibility of underscores in DNS names on April 1st, 2019 via CABF 1.6.2.
The language is as follows:

Prior to April 1, 2019, certificates containing underscore characters (“_”) in domain labels in dNSName entries MAY be issued as follows:

dNSName entries MAY include underscore characters such that replacing all underscore characters with hyphen characters (“-“) would result in a valid domain label, and;
Underscore characters MUST NOT be placed in the left most domain label, and;
Such certificates MUST NOT be valid for longer than 30 days.

This change adds two lints:

One which allows for underscores, albeit with a WARN and only if the above clauses apply. Else the underscore is an error.
1.a. This lint is ineffective after April 1st, 2019.
One which is disallows underscores altogether.
2.a: This lint is effectivve after April 1st, 2019.

Integration Test Failures
There are a large number of integration test failures (over 300) and a smoke check is showing that they are likely valid in that these certificates are valid for longer than the required thirty days. I will do a deep dive on these test failure, however.

#646 is now closed.


F2 highlight instruction

F2 in ida will highlight the instruction red and set a breakpoint.
While breakpoints may not be added soon, the highlighting would make it easier to flag points of interest.
related: https://github.com/Vector35/binaryninja-api/issues/223 (Convert to Breakpoint API)

#223 is about patching the Binary, not a debugging API. This is really just equivalent to the already existing keystroke refactor (#481) as once we allow arbitrary keystroke plugins it becomes trivial for someone to customize the keystroke to do any easy API call like this so I'm marking this as a dupe and closing.

Tracking is now in #92 instead of 481.


Suboptimal graph structure when read-writing a parquet

What happened:
to-parquet ops don't appear to "fuse" together with the rest of the linear chain. Since fusing chains is the current workaround for https://github.com/dask/distributed/issues/3974, this results in larger-than-necessary memory usage due to workers picking up work from other partitions earlier than they should.
What you expected to happen:
to-parquet ops should be merged into the linear chain like the other ops do. See code below for more explanation.
Minimal Complete Verifiable Example:
import pandas as pd
import dask.dataframe as dd
import numpy as np

df = pd.DataFrame(np.random.randn(100,100), columns=[str(x) for x in range(100)])

ddf = dd.from_pandas(df, npartitions=2)
ddf.to_parquet("input")

ddf = dd.read_parquet("input")
ddf = ddf.to_parquet('test', compute=False)
ddf.visualize(optimize_graph=True)

This is the unoptimized graph:

This is the optimized graph:

Ideally the to-parquet op would be part of the fused chain. That way workers have no chance to prematurely switch to working on a different chain. I'm not aware of any reason that the to-parquet op should remain unfused.
Anything else we need to know?:
Environment:

Dask version: 2021.11.2
Python version: 3.8.x
Operating System:
Install method (conda, pip, source):

@davidhao3300 thanks for raising this. You're totally right. As a workaround right now, I'd recommend:
with dask.config.set({"optimization.fuse.active": True}):
    ddf.visualize(...)
    # or
    ddf.compute()
    # or
    ddf.persist()

@rjzamora I guess I'd thought with https://github.com/dask/dask/pull/7620 that the O side of I/O was Blockwise'd as well, but reading through to_parquet, it's not: https://github.com/dask/dask/blob/a5aecac8313fea30c5503f534c71f325b1775b9c/dask/dataframe/io/parquet/core.py#L738-L770
Looks to me like this would be pretty easy to convert to a map_partitions once my changes in https://github.com/dask/dask/pull/8310 are merged (letting you pass BlockwiseDeps as arguments to map_partitions).
More broadly, I'm starting to become concerned that https://github.com/dask/dask/pull/7620 was premature; going to open a separate issue about that.
cc @rjzamora, @ian-r-rose.

Thank you for the fast response, I confirm that setting optimization.fuse.active to True fuses to-parquet into the chain.
Are there any cons to enabling this globally? I guess all task graphs will have fusions that reduce opportunities for workers to share work?

Great to confirm, thanks.
The main con is just that you'll be converting all high-level graphs to low-level graphs, which are slower to transfer to the scheduler. Additionally, it appears that this may adversely affect set_index with the distributed scheduler, see https://github.com/dask/dask/pull/8451#issuecomment-985215013. If you're using set_index, this could be a significant problem; @rjzamora might be able to say more.

I guess all task graphs will have fusions that reduce opportunities for workers to share work?

Not particularly; the fusions that it makes should be pretty reasonable.

If you're using set_index, this could be a significant problem; @rjzamora might be able to say more.

Right - @madsbk discovered a while back (see #6051) that shuffling (set_index) performance can be significantly improved by modifying the priority of certain tasks. This optimization was eventually implemented in the form of HLG annotations. This seemed "nice" at the time, because we were no longer adding a shuffle-specific hack in dask-core code. However, the optimization completely depends on the ShuffleLayer not being materialized on the client.
The current "priority" solution is clearly a problem if your shuffle-based workflow happens to require low-level task fusion, for non-Blockwise layers. This is because Blockwise is the only Layer type where fusion at the HLG level is implemented. At the moment, any other form of fusion requires graph materialization, and it is hard to imagine a simple way to enable Blockwise fusion with other Layer types.

Note that I should be able to implement a to_parquet HLG layer soon.  I suspect that breaking it into a Blockwise + Reduction (new), we should be able to utilize Blockwise fusion for the particular case motivating this issue.

@rjzamora what's Reduction? Naively reading the graph, I think it could be done easily with just Blockwise + BlockwiseDepDict to pass in the filenames to tasks (see https://github.com/dask/dask/pull/8310#discussion_r762305810). But Reduction sounds cool :)

@rjzamora what's Reduction? Naively reading the graph, I think it could be done easily with just Blockwise + BlockwiseDepDict to pass in the filenames to tasks (see #8310 (comment)). But Reduction sounds cool :)

I think it makes sense to add a general Reduction Layer (or maybe TreeReduction) to reduce a Blockwise Layer down to a single output task. This would be used in to_parquet to collect the parquet metadata from every write task, and  produce a single _metadata file.

TreeReduction would be a great one! That's probably the most common pattern that's not high-level right now.

TreeReduction would be a great one! That's probably the most common pattern that's not high-level right now.

I took a first stab at this in #8468 - I'm hoping we can use the same reduction layer for the metadata stage in to_parquet


Add UpgradeTimeoutPath to 24-host

Summary

The timeout path is a public path set by the upgrade initiator to determine when the TRY step should timeout. It stores the timeoutHeight and timeoutTimestamp by which point the counterparty must have progressed to the TRY step. The TRY step will prove the timeout values set by the initiating chain and ensure the timeout has not passed. Or in the case of a timeout, in which case counterparty proves that the timeout has passed on its chain and restores the channel.

Add UpgradeTimeoutPath to 24-host with associated key func.

UpgradeTimeoutPath
UpgradeTimeoutKey

Ref: 24-host/keys.go
function timeoutPath(portIdentifier: Identifier, channelIdentifier: Identifier) Path {
    return "channelUpgrade/ports/{portIdentifier}/channelIdentifier/{channelIdentifier}/upgradeTimeout"
}

For Admin Use

[ ] Not duplicate issue
[ ] Appropriate labels applied
[ ] Appropriate contributors tagged/assigned

Review spec for any updates to key paths

The spec has been updated with
function channelUpgradeTimeoutPath(portIdentifier: Identifier, channelIdentifier: Identifier) Path {
    return "channelUpgrades/ports/{portIdentifier}/channels/{channelIdentifier}/upgradeTimeout"
}

closed by #1821


fix(pluginservers): workers invalidate instances

Ensure that if a pluginserver is restarted all workers invalidate their running instances.
Fixes FTI-5238
This is a cherry-pick from EE - https://github.com/Kong/kong-ee/pull/6207.

Waiting for CI before merging.


Add the headless version

Package

[x] @clerk/clerk-js
[ ] @clerk/clerk-react
[ ] @clerk/nextjs
[ ] @clerk/remix
[ ] @clerk/types
[ ] @clerk/themes
[ ] @clerk/localizations
[ ] @clerk/clerk-expo
[ ] @clerk/backend
[ ] @clerk/clerk-sdk-node
[ ] @clerk/shared
[ ] @clerk/fastify
[ ] @clerk/chrome-extension
[ ] gatsby-plugin-clerk
[ ] build/tooling/chore
[ ] other:

Description
I see that there's a headless version here but is never exported in the package.json file. Is it possible to add it there? Something like:
{
  "main": "dist/clerk.js",
  "module": "dist/clerk.mjs",
  "types": "dist/types/index.d.ts",
  "exports": {
    ".": {
      "import": "dist/clerk.mjs",
      "require": "dist/clerk.js"
    },
    "./headless": {
      "import": "headless/index.mjs",
      "require": "headless/index.js"
    }
  }
}

You can import this with import headless from '@clerk/clerk-js/headless as it stands without any changes 😁

This issue has been automatically locked since there has not been any recent activity after it was closed. Please open a new issue for related bugs.


SSR/Hydration: Re-Render due to hydration mismatch creates inconsistent DOM - textContent updated correctly, class attr isn't.

Version
3.2.23
Reproduction link
github.com
Steps to reproduce

step 1

yarn && yarn dev

What is expected?
Class and text values are the  same.
What is actually happening?

<template>
  <div :class="color">
    {{ color }}
  </div>
</template>

<script lang="ts" setup>
import { computed } from "vue";

console.log(process.client);

const color = computed(() => {
  return process.client ? "black" : "red";
});
</script>

<style>
.red {
  color: red;
}
.black {
  color: black;
}
</style>

@posva

@loyep Even though yes, this is a bug - your usage of a computed like this is wrong. Looking at the console, you can see that it causes a hydration mismatch.

Yes, I know. Only in this way can we reproduce this problem quickly.

LinusBorg

Not only class, but also style attributes


Sparse lagged time series transformation operation implementation

Sparse lagged ts_transformation was added. It based on sklearn TruncatedSVD operation with extracting significant components. The optimal number of components is determined on the threshold for the increase in the proportion of explained variance depending on the number of components.

Hello @ChrisLisbon! Thanks for opening this PR. We checked the lines you've touched for PEP 8 issues, and found:

In the file test/unit/pipelines/test_pipeline_tuning.py:

Line 231:52: E127 continuation line over-indented for visual indent
Line 235:30: W292 no newline at end of file


[FEATURE REQUEST] Expression to bring in file as a string - use case: Deployment Scripts/UserData

Is your feature request related to a problem? Please describe.
I have a powershell .ps1 script that I want to use to do some advanced calculations and return some outputs (subnet math). Currently I have to embed the script in the arm template with ScriptContent or awkwardly place it on a github script URI which makes it less portable and more difficult to locally test changes.
Ideally I could keep the .ps1 as a separate file (so I can unit test it with pester and whatnot) and then at bicep compilation pull it in as a string to ScriptContent. Currently I am doing this with a separate powershell step after the bicep compilation but it would be nice to have it native in the bicep template.
Describe the solution you'd like
To keep this generic, a bicep expression that will read a file and output it as a string. That way it could be used outside of just deploymentscripts, basically a cat operator though the name maybe should be file or something, I'll leave to the team to decide.
Concerns

Should expressions in the file be preserved or escaped? Since Powershell often uses ${} syntax. I say escaped and you can sub in expressions with the format operator if you need to (maybe)? Maybe an operator true/false parameter? EDIT: For Powershell at least, expressions can be replaced by using the arguments parameter, but something like UserData may still need a way to substitute in expressions.

Closing since we are tracking this with #471. I think we will get to this in 0.4.

@alex-frankel whoops, I swear I did a due diligence search. Agreed.


[Docs] Add note for intel users when setting up clion

This pull request addresses any hassle that an intel user might face while following the already-written documentation on setting up CLion to work with swift. This was added because while following the documentation, a new user (such as myself) might get confused as to why their llvm or clang build isn't showing up.

@swift-ci please smoke test and merge

Tests failed due to an unrelated issue.

@ktoso Could you run swift-ci again and see if the merge fixed it?

@swift-ci please smoke test and merge


PPO Example Script Accelerator error: initialize your accelerator via accelerator = Accelerator()

System Info

Platform: Linux-5.10.227-219.884.amzn2.x86_64-x86_64-with-glibc2.26
Python version: 3.10.15
PyTorch version: 2.5.1
CUDA device(s): Tesla T4, Tesla T4, Tesla T4, Tesla T4
Transformers version: 4.46.3
Accelerate version: 1.1.1
Accelerate config: not found
Datasets version: 3.1.0
HF Hub version: 0.26.2
TRL version: 0.12.1
bitsandbytes version: not installed
DeepSpeed version: 0.15.4
Diffusers version: not installed
Liger-Kernel version: not installed
LLM-Blender version: not installed
OpenAI version: not installed
PEFT version: not installed

Information

[X] The official example scripts
[ ] My own modified scripts

Tasks

[X] An officially supported task in the examples folder
[ ] My own task or dataset (give details below)

Reproduction
# Running the code on ml.g4dn.12xlarge instance

# Setup environment
conda create -n py_310_conda python="3.10" -y
conda activate py_310_conda
pip install trl
pip install deepspeed

# Clone the repo
git clone https://github.com/huggingface/trl.git
cd trl

# To Resolve some NVJIT link error (irrelevant for this issue)
export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH=/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/nvidia/nvjitlink/lib:$LD_LIBRARY_PATH

# Change num_processes to 4 in examples/accelerate_configs/deepspeed_zero2.yaml
# Launch the example script
accelerate launch --config_file examples/accelerate_configs/deepspeed_zero2.yaml \
    examples/scripts/ppo/ppo_tldr.py \
    --dataset_name trl-internal-testing/tldr-preference-sft-trl-style \
    --dataset_test_split validation \
    --output_dir models/minimal/ppo_tldr \
    --learning_rate 3e-6 \
    --per_device_train_batch_size 16 \
    --gradient_accumulation_steps 4 \
    --total_episodes 1000000 \
    --model_name_or_path EleutherAI/pythia-1b-deduped \
    --sft_model_path cleanrl/EleutherAI_pythia-1b-deduped__sft__tldr \
    --reward_model_path cleanrl/EleutherAI_pythia-1b-deduped__reward__tldr \
    --local_rollout_forward_batch_size 16 \
    --missing_eos_penalty 1.0 \
    --stop_token eos \
    --eval_strategy steps \
    --eval_steps 100

outputs:
(py_310_conda) -sh-4.2$ accelerate launch --config_file examples/accelerate_configs/deepspeed_zero2.yaml examples/scripts/ppo/ppo_tldr.py --dataset_name trl-internal-testing/tldr-preference-sft-trl-style --dataset
_test_split validation --output_dir models/minimal/ppo_tldr --learning_rate 3e-6 --per_device_train_batch_size 16 --gradient_accumulation_steps 4 --total_episodes 1000000 --model_name_or_path EleutherAI/pythia-1b-
deduped --sft_model_path cleanrl/EleutherAI_pythia-1b-deduped__sft__tldr --reward_model_path cleanrl/EleutherAI_pythia-1b-deduped__reward__tldr --local_rollout_forward_batch_size 16 --missing_eos_penalty 1.0 --sto
p_token eos
[2024-11-21 01:56:22,808] [INFO] [real_accelerator.py:219:get_accelerator] Setting ds_accelerator to cuda (auto detect)
W1121 01:56:24.612000 6458 site-packages/torch/distributed/run.py:793]
W1121 01:56:24.612000 6458 site-packages/torch/distributed/run.py:793] *****************************************
W1121 01:56:24.612000 6458 site-packages/torch/distributed/run.py:793] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune t
he variable for optimal performance in your application as needed.
W1121 01:56:24.612000 6458 site-packages/torch/distributed/run.py:793] *****************************************
[2024-11-21 01:56:27,920] [INFO] [real_accelerator.py:219:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-11-21 01:56:27,963] [INFO] [real_accelerator.py:219:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-11-21 01:56:27,967] [INFO] [real_accelerator.py:219:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-11-21 01:56:27,972] [INFO] [real_accelerator.py:219:get_accelerator] Setting ds_accelerator to cuda (auto detect)
[2024-11-21 01:56:29,627] [INFO] [comm.py:652:init_distributed] cdb=None
[2024-11-21 01:56:29,648] [INFO] [comm.py:652:init_distributed] cdb=None
[2024-11-21 01:56:29,649] [INFO] [comm.py:652:init_distributed] cdb=None
[2024-11-21 01:56:29,649] [INFO] [comm.py:683:init_distributed] Initializing TorchBackend in DeepSpeed with backend nccl
[2024-11-21 01:56:29,651] [INFO] [comm.py:652:init_distributed] cdb=None
[rank1]:[W1121 01:56:31.240210284 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 1]  using GPU 1 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if t
his rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id.
[rank3]:[W1121 01:56:31.281175904 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 3]  using GPU 3 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if t
his rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id.
[rank0]:[W1121 01:56:31.363231178 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 0]  using GPU 0 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if t
his rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id.
[rank2]:[W1121 01:56:32.470602356 ProcessGroupNCCL.cpp:4115] [PG ID 0 PG GUID 0 Rank 2]  using GPU 2 to perform barrier as devices used by this process are currently unknown. This can potentially cause a hang if t
his rank to GPU mapping is incorrect.Specify device_ids in barrier() to force use of a particular device,or call init_process_group() with a device_id.
[rank0]: Traceback (most recent call last):
[rank0]:   File "/home/ec2-user/SageMaker/trl_nov_20/trl/examples/scripts/ppo/ppo_tldr.py", line 165, in <module>
[rank0]:     trainer = PPOTrainer(
[rank0]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/transformers/utils/deprecation.py", line 165, in wrapped_func
[rank0]:     return func(*args, **kwargs)
[rank0]:   File "/home/ec2-user/SageMaker/trl_nov_20/trl/trl/trainer/ppo_trainer.py", line 179, in __init__
[rank0]:     accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps)
[rank0]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/accelerator.py", line 292, in __init__
[rank0]:     deepspeed_plugins = AcceleratorState().deepspeed_plugins
[rank0]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/state.py", line 887, in __init__
[rank3]:     trainer = PPOTrainer(
[rank3]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/transformers/utils/deprecation.py", line 165, in wrapped_func
[rank3]:     return func(*args, **kwargs)
[rank3]:   File "/home/ec2-user/SageMaker/trl_nov_20/trl/trl/trainer/ppo_trainer.py", line 179, in __init__
[rank3]:     accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps)
[rank3]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/accelerator.py", line 292, in __init__
[rank3]:     deepspeed_plugins = AcceleratorState().deepspeed_plugins
[rank3]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/state.py", line 887, in __init__
[rank3]:     raise ValueError(
[rank3]: ValueError: Please make sure to properly initialize your accelerator via `accelerator = Accelerator()` before using any functionality from the `accelerate` library.
[rank2]: Traceback (most recent call last):
[rank2]:   File "/home/ec2-user/SageMaker/trl_nov_20/trl/examples/scripts/ppo/ppo_tldr.py", line 165, in <module>
[rank2]:     trainer = PPOTrainer(
[rank2]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/transformers/utils/deprecation.py", line 165, in wrapped_func
[rank2]:     return func(*args, **kwargs)
[rank2]:   File "/home/ec2-user/SageMaker/trl_nov_20/trl/trl/trainer/ppo_trainer.py", line 179, in __init__
[rank2]:     accelerator = Accelerator(gradient_accumulation_steps=args.gradient_accumulation_steps)
[rank2]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/accelerator.py", line 292, in __init__
[rank2]:     deepspeed_plugins = AcceleratorState().deepspeed_plugins
[rank2]:   File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/state.py", line 887, in __init__
[rank2]:     raise ValueError(
[rank2]: ValueError: Please make sure to properly initialize your accelerator via `accelerator = Accelerator()` before using any functionality from the `accelerate` library.
[rank0]:[W1121 01:56:32.261786959 ProcessGroupNCCL.cpp:1250] Warning: WARNING: process group has NOT been destroyed before we destruct ProcessGroupNCCL. On normal program exit, the application should call destroy_
process_group to ensure that any pending NCCL operations have finished in this process. In rare cases this process can exit before this point and block the progress of another member of the process group. This con
straint has always been present,  but this warning has only been added since PyTorch 2.4 (function operator())
W1121 01:56:34.039000 6458 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 6618 closing signal SIGTERM
W1121 01:56:34.039000 6458 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 6619 closing signal SIGTERM
W1121 01:56:34.040000 6458 site-packages/torch/distributed/elastic/multiprocessing/api.py:897] Sending process 6620 closing signal SIGTERM
E1121 01:56:34.254000 6458 site-packages/torch/distributed/elastic/multiprocessing/api.py:869] failed (exitcode: 1) local_rank: 0 (pid: 6617) of binary: /home/ec2-user/anaconda3/envs/py_310_conda/bin/python3.10
Traceback (most recent call last):
  File "/home/ec2-user/anaconda3/envs/py_310_conda/bin/accelerate", line 8, in <module>
    sys.exit(main())
  File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 48, in main
    args.func(args)
  File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1153, in launch_command
    deepspeed_launcher(args)
  File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/accelerate/commands/launch.py", line 846, in deepspeed_launcher
    distrib_run.run(args)
  File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/torch/distributed/run.py", line 910, in run
    elastic_launch(
  File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 138, in __call__
    return launch_agent(self._config, self._entrypoint, list(args))
  File "/home/ec2-user/anaconda3/envs/py_310_conda/lib/python3.10/site-packages/torch/distributed/launcher/api.py", line 269, in launch_agent
    raise ChildFailedError(
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:
============================================================
examples/scripts/ppo/ppo_tldr.py FAILED
------------------------------------------------------------
Failures:
  <NO_OTHER_FAILURES>
------------------------------------------------------------
Root Cause (first observed failure):
[0]:
  time      : 2024-11-21_01:56:34
  host      : ip-10-10-10-83.ec2.internal
  rank      : 0 (local_rank: 0)
  exitcode  : 1 (pid: 6617)
  error_file: <N/A>
  traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html
============================================================```

### Expected behavior

The code throws an error on how accelerator = Accelerator.

### Checklist

- [X] I have checked that my issue isn't already filed (see [open issues](https://github.com/huggingface/trl/issues?q=is%3Aissue))
- [X] I have included my system information
- [X] Any code provided is minimal, complete, and reproducible ([more on MREs](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/creating-and-highlighting-code-blocks))
- [X] Any code provided is properly formatted in code blocks, (no screenshot, [more on code blocks](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/creating-and-highlighting-code-blocks))
- [X] Any traceback provided is complete

I encountered this issue previously and temporarily worked around it by adjusting the accelerate version to 0.34.2. Here are the versions I used:

accelerate==0.34.2
torch==2.5.1
transformers==4.46.2
deepspeed==0.15.4

same issues above

@lzy37ld
I fixed this problem by tweaking the torch version to 2.4.0, and maybe some other older version would have worked.

accelerate==0.34.2
torch==2.4.0
tansformers==4.46.2
deepspeed==0.15.4


AZURE_DEVOPS_EXT_PAT -- never worked

Hello Team,
I have followed the steps you suggested. However the approach AZURE_DEVOPS_EXT_PAT never worked for me.
Solutions worked for me is: echo $AZURE_DEVOPS_EXT_PAT | az devops login
I do not want to echo since am exposing PAT on command line.
Am I missing something?

Use echo to push it in, as in this gent's article.  [(https://medium.com/objectsharp/azure-cli-azure-devops-extension-7b77a7623911)] .  MSFT docs dont really show this.  Tested and it works.
echo $env:AZURE_DEVOPS_EXT_PAT | az devops login --org $ORG


Typo Error in readme file

Describe the bug
Change: "Use any library and models"
To: "Use any libraries and models"
To Reproduce
Steps to reproduce the behavior:

Go to readme
Click on use any library
Scroll down to '....'
See error

Expected behavior
"Use any libraries and models"
Screenshots
If applicable, add screenshots to help explain your problem.
Desktop (please complete the following information):

OS: [e.g. iOS]
Browser [e.g. chrome, safari]
Version [e.g. 22]

Smartphone (please complete the following information):

Device: [e.g. iPhone6]
OS: [e.g. iOS8.1]
Browser [e.g. stock browser, safari]
Version [e.g. 22]

Important Context
Add context about the problem here.

Network Logs in the Browser:

If applicable, Take a screenshot of the network logs or copy and paste any relevant log entries.

Docker Containers Information:

If applicable, Provide a screenshot showing the list of running and stopped containers.
Please provide us the with a screenshot of the logs for the agenta-backend docker container.

Additional Information:

Include any additional details, error messages, or observations that may be helpful.

Please make sure to provide all the requested information to expedite the debugging process. Thank you for helping us improve our project!

hey @chinmay7016 I believe you don't need to open a new issue + pr for every typo you found in the docs.
It would be nice if you can open 1 pr for all typos !
and again, thanks for the PRs

ok @aakrem


[F] getColumns(from, to) function similar to getRows()

🚀 Feature Proposal
Having a getColumns(from, to) function would be great - similar to the getRows() function !
Motivation
Would simplify selecting multiple columns drastically!
Example
// Get multiple column objects.
const cols = worksheet.getCols(5, 2); // start, length (>0, else undefined is returned)

OR
// Get multiple column objects.
const cols = worksheet.getCols(5, 9); // firstCol, lastCol (>0, else undefined is returned)

Hey @Sammeeey,
thanks for opening this issue.
Will start working on this during this weekend 🙏

Thanks @Siemienik !
Currently I'm using it only for work.
If we keep using it long-term I'll consider to contribute.
Feel free to remind me in case I raise other requests etc.😁

Just for reminder, if any feature or bug fix that your employer need can buy support on<EMAIL_ADDRESS>or contact us on discord.


Problem: schedules are deleted after (associated) template update

Issue
Hello team,
We encounter a blocking problem after updating to version 2.10.11-d31ebd3-1719394739.
Schedules are deleted after every template update.
Steps to reproduce:

Create a template.
Create a schedule and assign to the template.
(Manual execution: OK, schedule execution: OK)
Edit template, and save.
Schedule have been deleted.

The delete action is listed in project activity, see attached capture.
Nothing in semaphore service logs.
Impact
Service (scheduled tasks, alerts)
Installation method
Binary
Database
MySQL
Browser
Firefox
Semaphore Version
2.10.11-d31ebd3-1719394739
Ansible Version
No response
Logs & errors

Manual installation - system information
No response
Configuration
No response
Additional information
No response

Tested 2.10.21 with BoltDB (docker)
Same blocking bug

Seems to be related to https://github.com/semaphoreui/semaphore/blob/24bc4a83b8f1c75a870e2b88b980454dddb61b2e/web/src/components/TemplateForm.vue#L588
Schedule is dropped during registering.
I can provide a PR with fix, but need to understand the concept.
Here, if we have only 1 schedule for the template => it will be this.schedules[0] and it will always be deleted.

Should be fixed by 2.10.22
Testing

Hi @gaeldb yes, has been fixed in v2.10.222.

I confirm => all good now
Thank you ++


Various Changes and Improvements, Additional Flags

Various changes and improvements. Changes should all be backwards compatible and behind flags, should be almost no change in behavior unless the new flags are used. Open to feedback, feel free to merge as is, cherry-pick, or reject. Changes include:

Adding an output folder parameter (-OutputFolderPath,-o) to select an output folder separate from the input file.
Added a flag (-OutputUnconverted, -u) which will copy image files already in the converted format, jpeg, to the output folder if it is specified.
Added an interactive mode flag (-InteractiveMode, -t) which will open dialog file pickers for input files and output folder if they are not specified in a parameter.
Added a flag to allow file conversion to continue on a failed convert (-NoFailOnConvert). Files that failed to convert are printed in a message at the end of the script.
File logging now includes the full output file path, since it may be different from the input file.

Thank you for the submission! These look like some interesting changes and you seem to have been very thorough about the process. The challenge on my side is I haven’t used this script (or PowerShell) for a few years and confidence in my ability to review effectively is low.
My head is not in the right place to accept this PR now, but I will leave it open for consideration. For your own future reference, maintainers will generally be more receptive to multiple standalone changes vs. a single one that adds unrelated features.
Thank you again for sharing this! If you decide to fork the project out of impatience, I will understand. :)

Totally understand, feel free to leave it open, close it, or copy only what you want whenever you get around to it. My changes were to make it easier for a family member to use the script, using a shortcut to populate some of the flags, and thought someone else might get some use out of it. Thanks for your work 😊


[TypeScript] Compilation failure when allowSyntheticDefaultImports is false

What RMWC Version are you using [major.minor.patch]: 5.5.1
Name your build system [Webpack, Rollup...]: Webpack 4, TypeScript 3.4.5
When attempting to compile the latest version of RMWC we receive the following errors in our TypeScript project. This is because allowSyntheticDefaultImports is false in our project.
yarn run v1.13.0
$ yarn workspaces run build-tsc
$ tsc --build
../../../node_modules/@rmwc/dialog/dist/dialog-queue.d.ts:1:8 - error TS1192: Module '"/git/kaggleazure/node_modules/@types/react/index"' has no default export.

1 import React from 'react';
         ~~~~~

../../../node_modules/@rmwc/snackbar/dist/snackbar-queue.d.ts:1:8 - error TS1192: Module '"/git/kaggleazure/node_modules/@types/react/index"' has no default export.

1 import React from 'react';
         ~~~~~

The easiest solution is to change the React import to import * as React from 'react';

I'm not opposed to making this change for you since it would be consistent with most of the other imports, but I did some digging.
React absolutely does have a real default export, non synthetic. There are a few examples.
This is present in the main index, both defult exports
'use strict';

if (process.env.NODE_ENV === 'production') {
  module.exports = require('./cjs/react.production.min.js');
} else {
  module.exports = require('./cjs/react.development.js');
}

And this is present at the bottom of react.development.js
`module.exports = react;`

Both of those are real default exports, not synthetic ones, so it makes me wonder what other issue you might be having.

Fixed with 5.5.2

That is because TypeScript doesn't consider the code snippet you posted above to contain a default export...

In general, TypeScript’s view of CommonJS (and AMD) modules is that namespace imports always correspond to the shape of a CommonJS module object, and that a default import just corresponds to a member on that module named default.

https://devblogs.microsoft.com/typescript/announcing-typescript-2-7/#easier-ecmascript-module-interoperability

Out of curiousity, why do you have allowSyntheticDefaultImports disabled? Also, is your issue fixed?

Legacy reasons, I'd love to enable it but the current web app I'm working on breaks when I do and that's a deep rabbit hole we don't have time to invest in at the moment 🙂 🐰

Well, hopefully this helps for now then

It certainly does, thanks!

This is a regression as of v6.0.0... @jamesmfriedman could you re-apply the patch? Thanks for supporting the library for so many years, by the way; it's been my go-to for many months now.


Solve PhantomJS issue with MetadataProvider test

When merge @danigomez refactor, we now that it was a trouble with MetadataProvider test when running with Karma on PhantomJS. It seems to be a trouble of phantomJS, needs a little bit of investigation.

Can you link to the problem? What is that?

@andrerpena The current build of the travis-ci is failing due to the phantomJS test, when running it with karma it throws a:
          undefined is not a function/constructor

So.. it seems that find is not a function. This is the result of the attempt to remove underscore.

I'll take a look at it now

It's not a problem with find, it seems to be a PhantomJS issue, the tests works correctly using the Chrome browser option in Karma, or running them directly with Mocha.....

@andrerpena find is a function and exists because on chrome we can execute the test without a trouble, and chrome is a native browser, PhantomJS emulates the internal browser apis

I see.. At least it's possible to reproduce locally using phantom

Yes, that's the error :confused: we will try to investigate a bit about this and try solve it.

Find is undefined specifically in this case:

This logs this:

okey.. this is because find is for arrays and it should iterate over fields.. okey :/

Okey, excuse what I say before.

But, it is an array as i can see in the log....

Jaja bad mine, I looked fastly! :/

For some reason this array doesn't have find...

There is a polyfill in the PhantomJS for the find function.... https://github.com/ariya/phantomjs/issues/14054 , maybe that solves the issue!

@danigomez great. Can you test then? Thank you.

As a side note, @danigomez , I've seen you refactored all the methods to be static, which makes sense.. but does it makes sense to use this inside static methods? I mean.. I come from C# and this is like heresy. I know it works.. but this is for instance types. Wouldn't you agree?

@andrerpena using the keyword "this" to reference a static method in ES6 is needed because, after all, a javascript class is a prototype at low level.. that is the reason that you need to use this.

@andrerpena we come from java world and this is a little bit creepy... but sadly this is the way :/

ok.. if that's how the world is today.. :disappointed: :smile: :smile:

Our eyes bleeded when we found out that we must bind all the methods to his class in the constructor in ES6 xD

Seems strange for us... but we don't have to forget that javascript is prototype oriented, so It may vary a little bit much more than our precious c++ like languages jajaja

@danigomez but then we found that class properties solved this dirty part of method binding jaja xD

Fixed! :smile:

Great!


[Android] Maintain current (Android < 35) SystemUiMode behavior on Android >= 35

According to docs, edge-to-edge will become the default layout mode for apps targeting Android 15/35 or later. In order to avoid completely breaking Flutter apps once they start targeting SDK 35+ or run on Android 15 devices, we need to make sure that the current non-edge-to-edge system UI modes work the same as before. This means that for those system UI modes, we must ensure that we disable edge-to-edge.
Additionally, we should change our logic for opting into edge-to-edge to use the recommended EdgeToEdge API versus setting deprecated window flags ourselves; see the official recommendation.

Note to self: Start with changing Flutter apps to disable edge-to-edge mode by default then try to use the updated way to use edge-to-edge mode.

https://developer.android.com/reference/android/R.attr#windowOptOutEdgeToEdgeEnforcement is what we'll need to opt Flutter apps out of edge-to-edge but this will require a check that API 35 is the SDK in use.

Testing for this step should involve writing Golden tests to ensure that the behavior is what we expect before/after this change.

Going to focus on writing tests for the System UI modes first because using Android styles in the Flutter engine has turned out to be a complicated task that should not block making sure we are prepared for the Android change in terms of tests and documentation (https://github.com/flutter/website/issues/10755).

We determined that neither maintaining the current behavior nor writing goldens test to test the SystemUiModes is possible.
We cannot maintain the current behavior, because we must create a style that the engine can reference to opt out of edge-to-edge by default, and this is not possible with the way the engine is currently compiled and used as a dependency in the framework. This work could be done, but we determined it is out of scope for this particular edge-to-edge work.
We cannot write goldens tests because golden tests + integration tests currently does not work. It is a WIP though by @/matanlurey I think (https://github.com/flutter/flutter/issues/143299), so this piece may be addressable in the future. Filed https://github.com/flutter/flutter/issues/153970 to track.


[lvm] simple lvm usage

Reference

https://moeover.com/2015/04/10/lvmlogical-volume-manager.html

Function

create
remove
use
add

added, but should do more experiencement


Initial argocd password

It doesn't make sense to add it here (yet) as the user does nothing with the password. Where it does make sense is as an alternative to the argo admin initial-password command here
The initial readme doesn't (yet) tell the user that they need the argo CLI so could we move your commands down to that line as an alternative? Then the user can retrieve the password, with or without argo CLI.

Agree, I will do a PR to add it as alternative to using the CLI. With that change, there is no need to use the CLI (which it has to be installed during the workshop).


Crop produces warning

It looks like this:
Warning: State updates from the useState() and useReducer() Hooks don't support the
second callback argument. To execute a side effect after rendering, declare it in the
component body with useEffect(). index.js:1375
    e index.js:1375
    React 3
    t ReactCrop.min.js:417

I'm guessing this is coming from outdated use of useState() in the cropper.

Hm there is no use of useState or hooks in the component, are you sure this isn't coming from your code?

I thought so too (I'm using hooks), but the traceback would suggest otherwise. I'm not using callbacks in my useState hooks either :/

If you comment out <ReactCrop part from render(), does the error go away?

If you comment out <ReactCrop part from render(), does the error go away?
On Tue, Aug 6, 2019 at 10:23 PM James Thistlewood<EMAIL_ADDRESS>wrote:

I thought so too (I'm using hooks), but the traceback would suggest
otherwise. I'm not using callbacks in my useState hooks either :/
—
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.

Weird, I haven't changed anything and now I can't reproduce this. Seems like a rogue error... sorry about that. Closing.

I also saw this warning when I was using this component follow the Example of README.md:
<ReactCrop src={src} crop={crop} onChange={setCrop} />;

search the warning message then I saw someone else also got this warning: fuafa/not-a-hub/issues/12 and there is a solution to avoid this warning:
<ReactCrop src={src} crop={crop} onChange={newCrop => setCrop(newCrop)} />;


JavaTestRunner fails to run jck-compiler-lang-EXPR-group1

JavaTestRunner fails with "Bad Tests" when run against jck-compiler-lang-EXPR-group1
Passes when run with: oct-2021-prerelease

This should be fixed via: https://github.com/adoptium/aqa-tests/pull/3104


Refactor: add generated dir to make proto.rs IDE indexing friendly

Summary by CodeRabbit

Chores

Added the proto/src/generated directory to the .gitignore file.

Refactor

Streamlined and updated import statements across multiple modules for consistency and improved maintainability.

New Features

Enhanced proto/build.rs to automatically create the src/generated directory if it does not exist, ensuring smoother build processes.

Documentation

Introduced modules filer, helyim, and volume in proto/src/generated.rs, with initialization methods and detailed field setups for VolumeLocation.

@thexiay Hi, Thanks for your contribution and please fix the error check

@thexiay Sorry for the late reply. I don't think this pr should be merged. At present, the rs files generated by prost can be indexed by the IDEs (rustrover, vscode etc.) and I don't want to add generated files to the main code tree.

@thexiay Sorry for the late reply. I don't think this pr should be merged. At present, the rs files generated by prost can be indexed by the IDEs (rustrover, vscode etc.) and I don't want to add generated files to the main code tree.

but jump to the code will be index to include macro, and generated files will not be into main code tree, it will be ignore by .gitignore. But just jump to code will directly into prost generated code.

but jump to the code will be index to include macro
What does it mean?

But just jump to code will directly into prost generated code.
That's how it is now

but jump to the code will be index to include macro

@thexiay Hi, What does it mean?

But just jump to code will directly into prost generated code.

That's how it is now

ok, i try to compile branch main code again, and include! macro code jump works! I will close this, it's a little bit confused when i first try code jump but does not work.

but jump to the code will be index to include macro

@thexiay Hi, What does it mean?

But just jump to code will directly into prost generated code.

That's how it is now

ok, i try to compile branch main code again, and include! macro code jump works! I will close this, it's a little bit confused when i first try code jump but does not work.

@iamazy see https://github.com/rust-lang/rust-analyzer/issues/10178


Laravel Queues,jobs equivalent

Do we have any thing equivalent to the Laravel Queues and jobs in Yii2 ?

https://github.com/yiisoft/yii2-queue

Please mention this package in the extention lists, also do we have the broadcast function on the event like laravel ?

it is not stable yet.


Allow one hot encoding for dataframes, for all categorical columns

if the column name is not passed, would be good to scan the dataframe for all categorical columns and one-hot encode them

Extra information:
A categorical column is a column that contains text values.  As for machine learning, all values have to be translated into numeric values, the concept of one-hot encoding is applied.  That concept is easily explained with the picture below.
So, this issue could be seen to implement a function that takes all text-columns of a dataframe and one-hot-encodes them.