Compatibility with tilelive?

This looks excellent.
I've been working a rather similar piece of software for a while (tessera), presumably with slightly different requirements / philosophy (but also borne out of experience with TileStache).
tessera relies on tilelive modules for everything (as does its sibling, tl and I expect that we have very similar desires for future modules (I was about to embark on an ImageMagick module this morning before seeing tilestrata-gm).  As such, it would be great to find a way to write adapters that map between tilelive and tilestrata modules so we can keep the core functionality centralized and shareable.
Thoughts?

@mojodna I considered tessera for awhile! I never really could wrap my head around configuration through URI's though (tilelive thing, not tessera), which is what my hangup was. Also, I couldn't totally figure out what tilelive was – and how caches, transforms, providers, etc could work together. It does have a great ecosystem though. Writing two adapters (tilestrata to tilelive and tilelive to tilestrata) wouldn't be that hard and don't see why not!
tilestrata-mapnik is an example of something using a tilelive module under the hood.

Ah, yeah.  That took a bit for me to wrap my head around as well, but I realized how powerfully composable the different pieces are, especially when rendering vector tiles, rendering them to images, and then transforming them.
Here's an example from the OpenTerrain project that applies some blend operations to the hillshades:
https://github.com/stamen/openterrain-map/blob/master/tessera.json
(These can be nested since everything is ultimately a source.  https://github.com/stamen/sm2 is a Mapnik-powered version of the compositing tech behind Map Stack (which actually uses node-cairo under the hood and I haven't built a tilelive source for that yet).)
Good point re: "what is tilelive?"  I've proposed talks about it in the past because I think it's a really powerful abstraction that's not well-understood, but that's never gone anywhere.
We should see to what extent we can converge our rendering stacks since we have pretty common needs.

This is a really interesting thread: we (mapbox) haven't done nearly enough to document how tilelive parts fit together, despite that system being the backbone of tile serving. I'll try writing some docs and running them past @yhahn

@tmcw @yhahn Cool! I think different options in the space are good. As far as node tile servers go, we're not to the "paralyzed by choice" stage yet :) If you want someone naive to review, I'd be happy to help.


add open finder results in tab, and add a resp == nil judge

#293 feature added

any update about this pr?


Fractional scaling causing issue with blur

Regression?
Yes
System Info and Version
 System/Version info
Hyprland, built from branch aquamarine at commit 10bbd96868967c272963ce8d8132b93f18f6d574  (Aquamarine headers for no pch build and a heap use after free (6892)).
Date: Mon Jul 15 11:01:48 2024
Tag: v0.41.2-129-g10bbd968, commits: 5015

Description
One of my monitors is scaled up and when i first start my session the blurring towards the edge of the window fades from blur to transparency. Once I reset my scaling to 1 and back to fs setting the effect goes away. I've tested on both aquamarine branch and main and it appears in both.

__
How to reproduce
Start session with fractionally scaled monitor.
Crash reports, logs, images, videos
No response

you say regression, can you bisect?

I just tried to bisect for about 20 minutes (back to 0.40) and came to the realization that it was probably a rounding error that I never noticed before.


adding test.txt files in order to test pr workflow.

testing pr workflow.
Co-authored-by: Hadwa Gaber<EMAIL_ADDRESS>

Repoman Generation Results
Repoman pushed changes to remotes for the following projects:
Project: todo-nodejs-mongo
Remote: azure-samples
Branch: pr/15
You can initialize this project with:
azd init -t kaizentm/todo-nodejs-mongo -b pr/15

View Changes | Compare Changes

Project: todo-python-mongo
Remote: azure-samples
Branch: pr/15
You can initialize this project with:
azd init -t kaizentm/todo-python-mongo -b pr/15

View Changes | Compare Changes


[$250] The "Not Found" page does not display when we press on the deleted message link.

If you haven’t already, check out our contributing guidelines for onboarding and email<EMAIL_ADDRESS>to request to join our Slack channel!

Version Number: 9.0.43-4
Reproducible in staging?: y
Reproducible in production?: y
If this was caught during regression testing, add the test name, ID and link from TestRail:
Email or phone of affected tester (no customers):
Logs: https://stackoverflow.com/c/expensify/questions/4856
Expensify/Expensify Issue URL:
Issue reported by: @jayeshmangwani
Slack conversation: https://expensify.slack.com/archives/C049HHMV9SM/p1727868246323429
Action Performed:

Go to any chat.
Long-press on any message that you have sent and select "Copy Link."
Send that link in the chat.
Delete the message for which you selected "Copy Link."
Press on the link in the chat.
The user scrolls in the chat, but the "Not Found" page does not appear.
Now press any pressable on the page, e.g., Emoji.
Now, we can see the "Not Found" page after pressing the button.

Expected Result:
The "Not Found" page should be visible immediately if the message is deleted.
Actual Result:
The "Not Found" page does not display when we press on the deleted message link.
Workaround:
unknown
Platforms:

Which of our officially supported platforms is this issue occurring on?

[ ] Android: Native
[ ] Android: mWeb Chrome
[x] iOS: Native
[ ] iOS: mWeb Safari
[ ] MacOS: Chrome / Safari
[ ] MacOS: Desktop

Screenshots/Videos
https://github.com/user-attachments/assets/7fa3489a-b512-41c5-a4ea-f62834cf1ba9
https://github.com/user-attachments/assets/c4104637-fe09-4179-95a9-89dd182f9c16

Add any screenshot/video evidence

View all open jobs on GitHub
Upwork Automation - Do Not Edit

Upwork Job URL: https://www.upwork.com/jobs/~021841649844209879395
Upwork Job ID:<PHONE_NUMBER>209879395
Last Price Increase: 2024-10-03
Automatic offers:

rayane-djouah | Reviewer | 104343030
Nodebrute | Contributor | 104343031

Issue OwnerCurrent Issue Owner: @rayane-djouah

Typically I'd put this in #vip-vsb but that project is closed/paused. It sounds like this kind of chat bugs falls under #newdot-quality now per DBs comment here.

Proposal
Please re-state the problem that we are trying to solve in this issue.
he "Not Found" page does not display when we press on the deleted message link.
What is the root cause of that problem?
prevIsLinkedActionDeleted returns undefined because the previous value is undefined. As a result, the "Not found" page cannot be displayed due to this condition
https://github.com/Expensify/App/blob/f83b69e45451946c7505b773fb6e085fb2fe66c0/src/pages/home/ReportScreen.tsx#L364
What changes do you think we should make in order to solve the problem?
To resolve this issue, we simply trigger an update to the value of prevIsLinkedActionDeleted(https://github.com/Expensify/App/blob/main/src/pages/home/ReportScreen.tsx#L340).
// .src/pages/home/ReportScreen.tsx#L666
useEffect(() => {
        // If the linked action is previously available but now deleted,
        // remove the reportActionID from the params to not link to the deleted action.
        const isLinkedActionBecomesDeleted = prevIsLinkedActionDeleted !== undefined && !prevIsLinkedActionDeleted && isLinkedActionDeleted;
        if (!isLinkedActionBecomesDeleted) {
+           if (!isLinkedActionInaccessibleWhisper && isLinkedActionDeleted) {
+                fetchReportIfNeeded();
+            }
            return;
        }
        Navigation.setParams({reportActionID: ''});
-    }, [prevIsLinkedActionDeleted, isLinkedActionDeleted]);
+   }, [prevIsLinkedActionDeleted, isLinkedActionDeleted, isLinkedActionInaccessibleWhisper, fetchReportIfNeeded]);

POC
https://github.com/user-attachments/assets/b89886fe-73a8-4c54-8cb7-26e29b0da459

PR is up, looks like waiting on @aldo-expensify to review next!

Merged


Run postgres as another user

Using:
https://github.com/docker-library/docs/blob/master/postgres/README.md#arbitrary---user-notes
and
https://docs.docker.com/compose/compose-file/compose-file-v3/#domainname-hostname-ipc-mac_address-privileged-read_only-shm_size-stdin_open-tty-user-working_dir
change the user running the postgres process to one to which the deployment has permissions.

This did not work as advertised.


oauth2 and artemis-jms changes

Comment out oauth2 extension as it colides with JWT expensio
Removing artemis-jms from many-extensions case

GH actions issue, https://github.com/quarkus-qe/beefy-scenarios/pull/12 checks were fine, merging


Is libra codebase compilable against arm

❓ Questions and Help
Please note that this issue tracker is not a help form and this issue will be closed.
Please contact the development team on Discourse
If not, any plan to support arm in the future? Thanks!

Hi! =)
Currently, there is no plan to include ARM support, sorry.

Hm... okay, thanks for the confirmation :-)

@aching FYI, tested that vm is runnable on aarch64


ESLint, with the Google config

R: @gauntface @ebidel @beaufortfrancois @addyosmani @wibblymat or whomever wants to take the time to read through this...
This switches over our linting to ESLint, using the new eslint-config-google config as the base.
The majority of the changes boil down to the 80 character line length limit, and missing spaces. I don't think there's anything particularly controversial.
I ended up putting in directory-level .eslintrc files in a couple of places when there were specific rules that needed to be specifically ignored in order to properly demonstrate the functionality, or when there's, e.g., code that relies on the serviceworker environment. I opted for those instead of inline ESLint config via comments so as not to add extra noise to the code that gets included in the sample landing pages.
Note that we're only linting standalone .js files now, so the process of migrating all the inline JavaScript code out of HTML files needs to be completed before we'll have 100% coverage. Given that all new development will have standalone .js files, I think we're safe to move forward.
Closes #265

:+1:


More advanced frequency analysis functions in HCOM

Energy density spectrum
Power density spectrum
Root mean square of vector

Resolves #1891.

The HCOM fft() function is now split into three functions for energy, power and RMS spectral density:
psd(vector, timevector, windowing[optional], mintime[optional] maxtime[optional])
esd(vector, timevector, windowing[optional], mintime[optional] maxtime[optional])
rmsd(vector, timevector, windowing[optional], mintime[optional] maxtime[optional])

where
windowing = flattop/rectangular/hann


Improve xfail reasons for test_dataclasses

(Also make trivial modifications to get some more tests passing)

please review


HBASE-24791 Improve HFileOutputFormat2 to avoid always call getTableRelativePath method

HBASE-24791 Improve HFileOutputFormat2 to avoid always call getTableRelativePath method

This can imporve a lot
A simple test case
before improve cost:
8566118066<PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER><PHONE_NUMBER>
after improve cost: 1536854	50156	1097601	33953	9907	10927	10445	13076	8596	10386
before all cost: 81227.639801 ms
after all cost : 2.781901 ms
before vs after: 29198.60908098455:1
The test code in
https://github.com/utf7/hbase-client-example/blob/master/src/test/java/TestGetTableRelativePathImprove.java

why don't trigger the related link to HBASE JIRA ?

mind have  a look ? thanks @Apache9 @infraio @guangxuCheng @pankaj72981

:confetti_ball: +1 overall

Vote
Subsystem
Runtime
Comment

+0 :ok:
reexec
1m  0s
Docker mode activated.

_ Prechecks _

+1 :green_heart:
dupname
0m  0s
No case conflicting files found.

+1 :green_heart:
hbaseanti
0m  0s
Patch does not have any anti-patterns.

+1 :green_heart:
@author
0m  0s
The patch does not contain any @author tags.

_ master Compile Tests _

+0 :ok:
mvndep
0m 20s
Maven dependency ordering for branch

+1 :green_heart:
mvninstall
3m 54s
master passed

+1 :green_heart:
checkstyle
1m 28s
master passed

+1 :green_heart:
spotbugs
2m 48s
master passed

_ Patch Compile Tests _

+0 :ok:
mvndep
0m 12s
Maven dependency ordering for patch

+1 :green_heart:
mvninstall
3m 47s
the patch passed

-0 :warning:
checkstyle
0m 17s
hbase-mapreduce: The patch generated 1 new + 1 unchanged - 0 fixed = 2 total (was 1)

+1 :green_heart:
whitespace
0m  0s
The patch has no whitespace issues.

+1 :green_heart:
hadoopcheck
12m 10s
Patch does not cause any errors with Hadoop 3.1.2 3.2.1.

+1 :green_heart:
spotbugs
3m  7s
the patch passed

_ Other Tests _

+1 :green_heart:
asflicense
0m 22s
The patch does not generate ASF License warnings.

38m 37s

Subsystem
Report/Notes

Docker
Client=19.03.12 Server=19.03.12 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/artifact/yetus-general-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/2167

Optional Tests
dupname asflicense spotbugs hadoopcheck hbaseanti checkstyle

uname
Linux 443a8011a1ea 4.15.0-101-generic #102-Ubuntu SMP Mon May 11 10:07:26 UTC 2020 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
master / 7974a1e9bf

checkstyle
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/artifact/yetus-general-check/output/diff-checkstyle-hbase-mapreduce.txt

Max. process+thread count
86 (vs. ulimit of 12500)

modules
C: hbase-server hbase-mapreduce U: .

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/console

versions
git=2.17.1 maven=(cecedd343002696d0abb50b32b541b8a6ba2883f) spotbugs=3.1.12

Powered by
Apache Yetus 0.11.1 https://yetus.apache.org

This message was automatically generated.

remove the HBASE-24790 code and do more  code clean by review
@anoopsjohn @pankaj72981  please have a look, thanks

:confetti_ball: +1 overall

Vote
Subsystem
Runtime
Comment

+0 :ok:
reexec
0m 28s
Docker mode activated.

-0 :warning:
yetus
0m  3s
Unprocessed flag(s): --brief-report-file --spotbugs-strict-precheck --whitespace-eol-ignore-list --whitespace-tabs-ignore-list --quick-hadoopcheck

_ Prechecks _

_ master Compile Tests _

+0 :ok:
mvndep
0m 23s
Maven dependency ordering for branch

+1 :green_heart:
mvninstall
4m  3s
master passed

+1 :green_heart:
compile
1m 40s
master passed

+1 :green_heart:
shadedjars
6m 42s
branch has no errors when building our shaded downstream artifacts.

+1 :green_heart:
javadoc
1m  1s
master passed

_ Patch Compile Tests _

+0 :ok:
mvndep
0m 16s
Maven dependency ordering for patch

+1 :green_heart:
mvninstall
4m  0s
the patch passed

+1 :green_heart:
compile
1m 32s
the patch passed

+1 :green_heart:
javac
1m 32s
the patch passed

+1 :green_heart:
shadedjars
5m 45s
patch has no errors when building our shaded downstream artifacts.

+1 :green_heart:
javadoc
0m 54s
the patch passed

_ Other Tests _

+1 :green_heart:
unit
140m 55s
hbase-server in the patch passed.

+1 :green_heart:
unit
11m  1s
hbase-mapreduce in the patch passed.

181m  6s

Subsystem
Report/Notes

Docker
Client=19.03.12 Server=19.03.12 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/artifact/yetus-jdk8-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/2167

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux 546e3fbd7203 4.15.0-60-generic #67-Ubuntu SMP Thu Aug 22 16:55:30 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
master / 7974a1e9bf

Default Java
1.8.0_232

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/testReport/

Max. process+thread count
4697 (vs. ulimit of 12500)

modules
C: hbase-server hbase-mapreduce U: .

_ Patch Compile Tests _

+0 :ok:
mvndep
0m 16s
Maven dependency ordering for patch

+1 :green_heart:
mvninstall
4m 18s
the patch passed

+1 :green_heart:
compile
1m 39s
the patch passed

+1 :green_heart:
javac
1m 39s
the patch passed

+1 :green_heart:
shadedjars
6m 19s
patch has no errors when building our shaded downstream artifacts.

-0 :warning:
javadoc
0m 40s
hbase-server in the patch failed.

-0 :warning:
javadoc
0m 21s
hbase-mapreduce in the patch failed.

_ Other Tests _

+1 :green_heart:
unit
151m 25s
hbase-server in the patch passed.

+1 :green_heart:
unit
10m 13s
hbase-mapreduce in the patch passed.

193m 47s

Subsystem
Report/Notes

Docker
Client=19.03.12 Server=19.03.12 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/artifact/yetus-jdk11-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/2167

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux e2a1c17eb1dd 4.15.0-60-generic #67-Ubuntu SMP Thu Aug 22 16:55:30 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
master / 7974a1e9bf

Default Java
2020-01-14

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-mapreduce.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-server.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/artifact/yetus-jdk11-hadoop3-check/output/patch-javadoc-hbase-server.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/artifact/yetus-jdk11-hadoop3-check/output/patch-javadoc-hbase-mapreduce.txt

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/testReport/

Max. process+thread count
4673 (vs. ulimit of 12500)

modules
C: hbase-server hbase-mapreduce U: .

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/1/console

versions
git=2.17.1 maven=(cecedd343002696d0abb50b32b541b8a6ba2883f)

Powered by
Apache Yetus 0.11.1 https://yetus.apache.org

This message was automatically generated.

:confetti_ball: +1 overall

Vote
Subsystem
Runtime
Comment

+0 :ok:
reexec
0m 31s
Docker mode activated.

_ Patch Compile Tests _

+1 :green_heart:
mvninstall
4m  4s
the patch passed

+1 :green_heart:
compile
0m 30s
the patch passed

+1 :green_heart:
javac
0m 30s
the patch passed

+1 :green_heart:
shadedjars
5m 44s
patch has no errors when building our shaded downstream artifacts.

-0 :warning:
javadoc
0m 20s
hbase-mapreduce in the patch failed.

_ Other Tests _

+1 :green_heart:
unit
10m 21s
hbase-mapreduce in the patch passed.

33m 36s

Subsystem
Report/Notes

Docker
Client=19.03.12 Server=19.03.12 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/2/artifact/yetus-jdk11-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/2167

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux 2af7b5245bdb 4.15.0-58-generic #64-Ubuntu SMP Tue Aug 6 11:12:41 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
master / 56f32ea895

Default Java
2020-01-14

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/2/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-mapreduce.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/2/artifact/yetus-jdk11-hadoop3-check/output/patch-javadoc-hbase-mapreduce.txt

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/2/testReport/

Max. process+thread count
3818 (vs. ulimit of 12500)

modules
C: hbase-mapreduce U: hbase-mapreduce

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/2/console

versions
git=2.17.1 maven=(cecedd343002696d0abb50b32b541b8a6ba2883f)

Powered by
Apache Yetus 0.11.1 https://yetus.apache.org

This message was automatically generated.

:confetti_ball: +1 overall

Vote
Subsystem
Runtime
Comment

+0 :ok:
reexec
0m 27s
Docker mode activated.

_ Patch Compile Tests _

+1 :green_heart:
mvninstall
5m 45s
the patch passed

+1 :green_heart:
compile
0m 36s
the patch passed

+1 :green_heart:
javac
0m 36s
the patch passed

+1 :green_heart:
shadedjars
8m  6s
patch has no errors when building our shaded downstream artifacts.

-0 :warning:
javadoc
0m 24s
hbase-mapreduce in the patch failed.

_ Other Tests _

+1 :green_heart:
unit
12m 12s
hbase-mapreduce in the patch passed.

43m 35s

Subsystem
Report/Notes

Docker
Client=19.03.12 Server=19.03.12 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/3/artifact/yetus-jdk11-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/2167

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux bb3e99ed930a 4.15.0-58-generic #64-Ubuntu SMP Tue Aug 6 11:12:41 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
master / d65fb87a2e

Default Java
2020-01-14

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/3/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-mapreduce.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/3/artifact/yetus-jdk11-hadoop3-check/output/patch-javadoc-hbase-mapreduce.txt

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/3/testReport/

Max. process+thread count
3810 (vs. ulimit of 12500)

modules
C: hbase-mapreduce U: hbase-mapreduce

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/3/console

versions
git=2.17.1 maven=(cecedd343002696d0abb50b32b541b8a6ba2883f)

Powered by
Apache Yetus 0.11.1 https://yetus.apache.org

This message was automatically generated.

Can you see why javadoc for hbase-mapreduce didn't pass ?
Thanks

thanks ,@tedyu
in my local env
 mvn --batch-mode --threads=2 -DHBasePatchProcess clean javadoc:javadoc -DskipTests=true
all passed
how to trigger a retry ?

rery qa

https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/3/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-mapreduce.txt
See the bottom of above page

The failure of javadoc for jdk11 is expected, we still have problems building javadoc with java11, that's why we just issue a -0, not -1.

ok, i will retry in jdk 11 and find it why failed
thanks @tedyu @Apache9

ok, i will retry in jdk 11 and find it why failed
thanks @tedyu @Apache9

This could be another issue. Do not need to address it in this PR. It is not a blocker.

ok, i will retry in jdk 11 and find it why failed
thanks @tedyu @Apache9

This could be another issue. Do not need to address it in this PR. It is not a blocker.

_ Patch Compile Tests _

+1 :green_heart:
mvninstall
4m  3s
the patch passed

+1 :green_heart:
compile
0m 28s
the patch passed

+1 :green_heart:
javac
0m 28s
the patch passed

+1 :green_heart:
shadedjars
5m 48s
patch has no errors when building our shaded downstream artifacts.

-0 :warning:
javadoc
0m 20s
hbase-mapreduce in the patch failed.

_ Other Tests _

+1 :green_heart:
unit
9m 16s
hbase-mapreduce in the patch passed.

32m 29s

Subsystem
Report/Notes

Docker
Client=19.03.12 Server=19.03.12 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/4/artifact/yetus-jdk11-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/2167

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux 7d6c473a9149 4.15.0-58-generic #64-Ubuntu SMP Tue Aug 6 11:12:41 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
master / 9a1bad84bf

Default Java
2020-01-14

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/4/artifact/yetus-jdk11-hadoop3-check/output/branch-javadoc-hbase-mapreduce.txt

javadoc
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/4/artifact/yetus-jdk11-hadoop3-check/output/patch-javadoc-hbase-mapreduce.txt

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/4/testReport/

Max. process+thread count
4874 (vs. ulimit of 12500)

modules
C: hbase-mapreduce U: hbase-mapreduce

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/4/console

versions
git=2.17.1 maven=(cecedd343002696d0abb50b32b541b8a6ba2883f)

Powered by
Apache Yetus 0.11.1 https://yetus.apache.org

This message was automatically generated.

:confetti_ball: +1 overall

Vote
Subsystem
Runtime
Comment

+0 :ok:
reexec
1m  8s
Docker mode activated.

-0 :warning:
yetus
0m  3s
Unprocessed flag(s): --brief-report-file --spotbugs-strict-precheck --whitespace-eol-ignore-list --whitespace-tabs-ignore-list --quick-hadoopcheck

_ Prechecks _

_ master Compile Tests _

+1 :green_heart:
mvninstall
3m 50s
master passed

+1 :green_heart:
compile
0m 27s
master passed

+1 :green_heart:
shadedjars
5m 59s
branch has no errors when building our shaded downstream artifacts.

+1 :green_heart:
javadoc
0m 19s
master passed

_ Patch Compile Tests _

+1 :green_heart:
mvninstall
3m 39s
the patch passed

+1 :green_heart:
compile
0m 26s
the patch passed

+1 :green_heart:
javac
0m 26s
the patch passed

+1 :green_heart:
shadedjars
5m 30s
patch has no errors when building our shaded downstream artifacts.

+1 :green_heart:
javadoc
0m 18s
the patch passed

_ Other Tests _

+1 :green_heart:
unit
10m 33s
hbase-mapreduce in the patch passed.

33m 17s

Subsystem
Report/Notes

Docker
Client=19.03.12 Server=19.03.12 base: https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/4/artifact/yetus-jdk8-hadoop3-check/output/Dockerfile

GITHUB PR
https://github.com/apache/hbase/pull/2167

Optional Tests
javac javadoc unit shadedjars compile

uname
Linux 16248f5deec7 4.15.0-60-generic #67-Ubuntu SMP Thu Aug 22 16:55:30 UTC 2019 x86_64 x86_64 x86_64 GNU/Linux

Build tool
maven

Personality
dev-support/hbase-personality.sh

git revision
master / 9a1bad84bf

Default Java
1.8.0_232

Test Results
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/4/testReport/

Max. process+thread count
4751 (vs. ulimit of 12500)

modules
C: hbase-mapreduce U: hbase-mapreduce

Console output
https://ci-hadoop.apache.org/job/HBase/job/HBase-PreCommit-GitHub-PR/job/PR-2167/4/console

versions
git=2.17.1 maven=(cecedd343002696d0abb50b32b541b8a6ba2883f)

Powered by
Apache Yetus 0.11.1 https://yetus.apache.org

This message was automatically generated.


Release workflow1

Description
Changes proposed in this pull request:

first part of a release workflow

Related issue(s)

/retest

/retest


typo add oracle jdbc catalog FAQ of orai18n.jar

Proposed changes
Issue Number: close #21974

Further comments
If this is a relatively large or complex change, kick off the discussion at<EMAIL_ADDRESS>by explaining why you chose the solution you did and what alternatives you considered, etc...

run buildall


Fixtures error

I'm getting an error while trying to load fixtures after initial migration (migration for existing data works fine)
Error as result of python manage.py loaddata initial_data:
TypeError: Problem installing fixture '/project/app/fixtures/initial_data.json': Hashid(1): HASH is not JSON serializable

model.py:
class Object(models.Model):
    id = HashidAutoField(
        primary_key=True,
        min_length=6
    )

fixture:
[
  {
    "model": "app.object",
    "pk": 1,
    "fields": {
     …
    }
  }
]

Thanks for the report @Jastrzebowski, but I'm having problems duplicating the issue. I've tested with Python 2.7 and 3.5 each with Django 1.8, 1.9 and 1.10, and I can't duplicate the error. In all instances I'm able to dumpdata and loaddata with keys as either integers or strings. Maybe you could shed some light on your environment? What version of Python and Django are you using? Are there any other fields in your models using HashidField or HashidAutoField? Anything else that might help me narrow down the issue?

works for me on
Python 3.6.8
Django==2.1
djangorestframework==3.10.2

using the APIClient from DRF


Teams - We are sorry we've run into an issue

Hello,
I discovered station today but found out that the private message display is not working and this error message is shown.
I dont reproduce this issue in a classic chrome browser with webapp Teams.
Any hints ?

#80


How to change camera positions before Evaluating

I am trying to evaluate transfuser on a bigger vehicle. (carlaCola), If it try to use the default settings with the car model changed only, I get pretty bad results, the truck wanders off the road and fails to perform basic maneuvers. I think this is because the camera positions were set according to a sedan, and i'll have to change it for the truck.
I see some relevant code in scenario_manager_local.py>setup_sensors.py, but can't figure out how to change the positions, also how to visualize what the camera is looking at, before going on with it.
and... If someone can comment on whether a model trained using a car autopilot would work on a bigger vehicle or not. (i dont see why it wouldn't given that both can follow a bicycle model).

The problem you are facing is called Viewpoint Robustness.
Neural networks are not naively viewpoint robust which means they only work on the sensor configuration they have been trained for.
E.g.: here is a recent paper in that direction.
https://arxiv.org/abs/2309.05192
The problem is likely more the computer vision and not the vehicle dynamics (for which you could just tune the controller).
CARLA simulates physics and does not use a bicylce model as far as I know.
For your case the best solution would be to collect a new dataset with a new sensor configuration designed for the carlaCola truck.
You need to write a script for your compute cluster to do that. We provide a slurm script in this repo that should be easy to adapt.

Thank You so much for your response, I am looking into the solutions.


Create Database of FOSS <--> Proprietory alternatives for Calculator

Data Sources

try and either contact the owners and/or scrape osalt.com

Tech

MongoDB

See also:
https://github.com/OpenScienceMOOC/Main/issues/17
https://github.com/OpenScienceMOOC/Main/issues/19
https://github.com/OpenScienceMOOC/Main/issues/18

See meta-open-db


[BEAM-8586] [SQL] Fix MongoDb integration tests

MongoDb Sql integrations tests should start and use a local instance of a MongoDb service.

Thank you for your contribution! Follow this checklist to help us incorporate your contribution quickly and easily:

[x] Choose reviewer(s) and mention them in a comment (R: @username).
[x] Format the pull request title like [BEAM-XXX] Fixes bug in ApproximateQuantiles, where you replace BEAM-XXX with the appropriate JIRA issue, if applicable. This will automatically link the pull request to the issue.
[ ] If this contribution is large, please file an Apache Individual Contributor License Agreement.

See the Contributor Guide for more tips on how to make review process smoother.

Run sql postcommit

R: @apilloud
cc: @TheNeuralBit

Run sql postcommit

Run sql postcommit


TypeError when rendering basic example

Expected behavior:
Following the basic example instructions works
Observed behavior:
When I run the render task, Sketch opens, but the following error
TypeError: null is not an object (evaluating 'context.document.currentPage')
line: 9246
column: 114

How to reproduce:
cameronlittle@Chelan:~/Dev
$ curl https://codeload.github.com/airbnb/react-sketchapp/tar.gz/master | tar -xz --strip=2 react-sketchapp-master/examples/basic-setup
cameronlittle@Chelan:~/Dev
$ cd basic-setup
cameronlittle@Chelan:~/Dev/basic-setup
$ npm install
# for brevity, I've removed this output, since it's all normal
cameronlittle@Chelan:~/Dev/basic-setup
$ npm run render

><EMAIL_ADDRESS>render /Users/cameronlittle/Dev/basic-setup
> skpm build --watch --run

🖨  Copied src/manifest.json in 6ms
Executing post-build scripts
🛠  Built ./my-command.js in 1391ms
TypeError: null is not an object (evaluating 'context.document.currentPage')
line: 9246
column: 114

Version information:
Sketch: 43.1
node: v7.2.1
npm: 3.10.10
os: macOS Sierra 10.12.3 (16D32)

You need to have a document opened

This should be way clearer, sorry - you need to have a new Sketch document open when you call render.
We've asked the Sketch devs to help us out on this but haven't got a timeline thus far :(

Great, thanks for the info!

Will it be better to verbose a info indicating the user a new sketch doc is required ?


Improved Update() by utilizing newer EF5+'s features & obeying open/closed principle by providing IQueryable instead of ICollection

Sorry for me being late this time, but I couldn't reply sooner.
Regarding your question: as the MSDN states that async EF is done by using async and await, there's no real asynchronous operation. Sure, it prevents blocking the current thread. But other than that, there's no benefit, because EF itself isn't even capable of doing asynchronous queries due to its desire to ensure database consistency - otherwise, you would be able to modify entities which others are possibly reading or even modifying at the same time.
Hence my suggestion to drop this, because your repository is entitled as being generic. If one really needs the query thread to be non-blocked, then s/he can inherit the generic interface and do it on her/his own. 😃

Prevention of blocking the current thread is the purpose of async. True the EF query won't be async, but the query takes time - and during that time the .NET code can be free to continue processing requests while the EF query is running.
I'd prefer to keep the Async methods for Add, Update, Delete, and Count. They don't have to be used but it's convenient to have the option in the generic.

My recent commit just updated my name, but to reply to your comment: I explicitly checked Allow edits from maintainers, because of my atomic commits. This way, you can leverage from my implemented improvements while leaving out the async removals by cherry-picking (i. e. unchecking 79765cc upon your merge of my PR).

My recent commit just updated my name, but to reply to your comment: I explicitly checked Allow edits from maintainers, because of my atomic commits. This way, you can leverage from my implemented improvements while leaving out the async removals by cherry-picking (i. e. unchecking 79765cc upon your merge of my PR).
Looking forward to your merge, so that I can close & delete this patch-branch afterwards as it's been around almost 2 years now.. :wink:

@mombrea Please delete this PR of mine as I seem to be disallowed to do so myself.
As a friendly suggestion: doing a (generic) repository atop EF is just wrong as it "over-engineers" the fact that EF itself is already the repository to be consumed/used.


drag-content="false"

Hi.
Is it possible to use this with your {{#ionSideMenuContent}} ?
Or a suggested work around would be great!
Thanks in advance, awesome package, thanks!
Kind regards
Chrs

Hi Chris,
Can you give me some background on this? Is drag-content something from Ionic? What is the expected behavior?
Thanks,
Nick

Hi,
it's an <ion-side-menu-content> attribute
http://ionicframework.com/docs/api/directive/ionSideMenuContent/

Yes, I tried to use it like this {{#ionSideMenu drag-content="false"}}

Ok guys, you can now pass a dragContent option to ionSideMenuContainer like so:
{{#ionSideMenuContainer dragContent=false}}

Awesome Nick! Much appreciated, great package!

If you remember give us a shout when you release the version to atmosphere with the fix, I'll keep trying, thanks!


API doc link request

Hi @itsliuhongyu,  Great notebook!  I was trying to get some similar data in a project I am working on and I noticed that the URL in your project is not one of the endpoints I found documented on the weather.gov website.  The data your URL retrieves is a better fit for me than what's noted in the documentation I found, so I'm wondering if you can provide a link to the docs you used to come up with your URL.  Thanks in advance!

Hi! This is the series of API that is public on the weather.gov website. I can't find the landing page for the API but it is in the format of https://www.weather.gov/source/chs/cliplot/KCHS202302.json
Replace the KCHS with the station you're looking for, also swap the year and month, and you can see the data


GH-41862: [C++][S3] Fix potential deadlock when closing output stream

Rationale for this change
When the Future returned by OutputStream::CloseAsync finishes, it can invoke a user-supplied callback. That callback may well destroy the stream as a side effect. If the stream is a S3 output stream, this might lead to a deadlock involving the mutex in the output stream's UploadState structure, since the callback is called with that mutex locked.
What changes are included in this PR?
Unlock the UploadState mutex before marking the Future finished, to avoid deadlocking.
Are these changes tested?
No. Unfortunately, I wasn't able to write a test that would trigger the original condition. Additional preconditions seem to be required to reproduce the deadlock. For example, it might require a mutex implementation that hangs if destroyed while locked.
Are there any user-facing changes?
No.

GitHub Issue: #41862

@github-actions crossbow submit -g cpp

@github-actions crossbow submit -g cpp

Ok, since there are two +1s, I will merge if CI is green (or the failures are unrelated).


#1603 Add configuration to override localstack image location

Adds support for propertylocalstack.container.image in testcontainer.properties.
Also moves the default VERSION in LocalStackContainer to be read from TestcontainersConfiguration.

Closing, as #1873 proceeded to make this configurable.


Session dropdown menu is outside the visible view.

Type: Bug
When I have more than one session running in debug, the dropdown menu that has disconnect, stop options is outside of the visible view and is pushed back of the editor area. Only a small portion of the dropdown menu is shown.
It doesn't matter what space I give the Side Bar; it always drops outside the visible side panel.

VS Code version: Code 1.71.0 (784b0177c56c607789f9638da7b6bf3230d47a8c, 2022-09-01T07:36:10.600Z)
OS version: Windows_NT x64 10.0.22000
Modes:
Sandboxed: No

System Info

Item
Value

CPUs
AMD Ryzen 7 4800H with Radeon Graphics          (16 x 2894)

GPU Status
2d_canvas: enabledcanvas_oop_rasterization: disabled_offdirect_rendering_display_compositor: disabled_off_okgpu_compositing: enabledmultiple_raster_threads: enabled_onopengl: enabled_onrasterization: enabledraw_draw: disabled_off_okskia_renderer: enabled_onvideo_decode: enabledvideo_encode: enabledvulkan: disabled_offwebgl: enabledwebgl2: enabledwebgpu: disabled_off

Load (avg)
undefined

Memory (System)
15.37GB (5.46GB free)

Process Argv
--crash-reporter-id d50e185c-0bfc-44b6-9830-5d4a2c2c6978

Screen Reader
no

VM
0%

Extensions (1)

Extension
Author (truncated)
Version

csharp
ms-
1.25.0

@weinand is it possible to add bug tag for better follow-up?

The assignee will do this.

It works from the debug toolbar, right?

Yes, the debug toolbar works just fine:

Sorry I'm actually not sure at what level the shadow dom is used or which widget you are looking for? The dropdown is inside this action view item https://github.com/microsoft/vscode/blob/d2114a401eb6dbe161ca447761758b06b6322dbc/src/vs/workbench/contrib/debug/browser/debugToolBar.ts#L282

Closing as this has been fixed in the meantime


go mod vendor on golang http filter: #cgo noescape envoyGoFilterHttpCopyHeaders

Title: go mod vendor on golang http filter: #cgo noescape envoyGoFilterHttpCopyHeaders
Description:
When I try to locally develop on golang http filter example of the repo ( ./examples/golang-http/simple ), I get this error:
internal error: failed to find embedded files of github.com/envoyproxy/envoy/contrib/golang/filters/http/source/go/pkg/http<EMAIL_ADDRESS>invalid #cgo line: #cgo noescape envoyGoFilterHttpCopyHeaders

Repro steps:
./envoy/examples/golang-http/simple
go mod tidy
go mod vendor

It seems the go:build tag is ignored by  go mod vendor. I will try to figure out why.

Commands such as go mod vendor and other commands currently parse the import statements in all Go files to determine which packages. By definition, this ignores build directives, because one wants to vendor all dependencies in all build configurations.
Here is an ongoing issue to adjust this behavior: https://github.com/golang/go/issues/42504.
Unfortunately, the #cgo directive need to be put above the import "C", so we can't workaround it by moving the unsupported syntax under import.

So the current solution is to not vendor it and use the modules from GOPATH. Thanks.

Since we introduced the new syntax in Golang: https://github.com/golang/go/pull/60399, which is a performance optimization.
It will be released in go 1.22, so we buildtag on go 1.22 here.
Maybe we can remove this cgo_go122.go file temporarily, and add it back after go 1.22 is released.
WDYT @spacewander

LGTM.
Only one tiny thing, unless Go provides a way to recognize the build directive (like the discussion in https://github.com/golang/go/issues/42504), we can't add the file back until we no longer support Go < 1.22, not just after Go 1.22 is released. Otherwise, running go mod vendor with Go < 1.22 won't work well.

yep, I think that's acceptable, we already require Go 1.20 for now.


Type: AndroidConfig: ttl misleading ?

[READ] Step 1: Are you in the right place?

For issues related to the code in this repository file a Github issue.
If the issue pertains to Cloud Firestore, read the instructions in the "Firestore issue"
template.
For general technical questions, post a question on StackOverflow
with the firebase tag.
For general Firebase discussion, use the firebase-talk
google group.
For help troubleshooting your application that does not fall under one
of the above categories, reach out to the personalized
Firebase support channel.

[REQUIRED] Step 2: Describe your environment

Operating System version: Linux
Firebase SDK version: 12.0.0
Firebase Product: messaging
Node.js version: 20.10.0
NPM version: 10.2.3

[REQUIRED] Step 3: Describe the problem
I think the wording on the docs or in this repo are wrong regarding AndroidConfig ttl value.
Relevant Code:
According to
https://github.com/firebase/firebase-admin-node/blob/9ab37f5d6ed6e03307869a3d46ef855b65666047/src/messaging/messaging-api.ts#L394-L397
(also present in latest master, but git blame didnt show any relevant touches here in recent years)
the ttl should be a number in milliseconds.
But according to the web documenation [1] the notation is quite different.
To quote:

string (Duration format)

How long (in seconds) the message should be kept in FCM storage if the device is offline. The maximum time to live supported is 4 weeks, and the default value is 4 weeks if not set. Set it to 0 if want to send the message immediately. In JSON format, the Duration type is encoded as a string rather than an object, where the string ends in the suffix "s" (indicating seconds) and is preceded by the number of seconds, with nanoseconds expressed as fractional seconds. For example, 3 seconds with 0 nanoseconds should be encoded in JSON format as "3s", while 3 seconds and 1 nanosecond should be expressed in JSON format as "3.000000001s". The ttl will be rounded down to the nearest second.

A duration in seconds with up to nine fractional digits, ending with 's'. Example: "3.5s".

So, which is it now? A string, a number? Milliseconds or seconds?
[1] https://firebase.google.com/docs/reference/fcm/rest/v1/projects.messages#androidconfig

What you have linked in [1] are reference docs for the REST API. You can find the Firebase Admin Node.js SDK reference docs at here, which defines ttl as a number in milliseconds.


Release Cert manager 1.3.1

@jakexks Here's me practicing how to release a new cert-manager for OLM

/approve
/lgtm


Build profiler sink

Feature
Based on https://github.com/open-metadata/OpenMetadata/issues/1311
Describe the task
Update the OM Python client and build the sink to send the profiler and test results to the OM API.

I hope the structure of the sink is in such a way that we can extend the implementation in the future to support an external sink such as CloudWatch of OpenTSDB, and make the metrics queryable through Grafana (iframe view embedded in OpenMetadata)
https://grafana.com/docs/grafana/latest/datasources/opentsdb/

The goal of the sink is to pick up the data structures created during the profiling and push them somewhere. We will start by preparing the OM sink, which will make some API calls to OM itself. We can create other sinks as needed, and they get configured in the JSON, e.g.,
"sink": {"type": "metadata-rest", "config": {}},


Cannot importing using Node.js native ESM

When trying to import this library with the native support for ESM that's available in Node.js 12, 14, and 16 I'm running into the following problem:
import { isPointInPolygon } from 'geolib';
         ^^^^^^^^^^^^^^^^
SyntaxError: Named export 'isPointInPolygon' not found. The requested module 'geolib' is a CommonJS module, which may not support all module.exports as named exports.
CommonJS modules can always be imported via the default export, for example using:

import pkg from 'geolib';
const { isPointInPolygon } = pkg;

    at ModuleJob._instantiate (node:internal/modules/esm/module_job:124:21)
    at async ModuleJob.run (node:internal/modules/esm/module_job:179:5)
    at async Loader.import (node:internal/modules/esm/loader:178:24)
    at async Object.loadESM (node:internal/process/esm_loader:68:5)
    at async handleMainPromise (node:internal/modules/run_main:63:12)

According to the readme it seems like this should work:

I think that the problem is that the package.json is missing the exports key which describes how the module should be loaded by the native Node.js ESM.
This is documented here: https://nodejs.org/api/packages.html#packages_package_entry_points
Basically, I think that something like this should be added:
  "exports": {
    ".": "./es/index.js"
  }

I will try this and submit a PR if it works 🚀

@manuelbieh another approach would be to release a breaking change that drops CommonJS altogether. That would be my recommendation!
Many packages are moving to this since all current versions of Node.js supports ESM now 🚀
You can read about Sindres approach (which I, and many other maintainers are also using) here: https://github.com/sindresorhus/meta/discussions/15

It is as simple as:

yarn add --dev esbuild
Update typescript to latest version
Update tsconfig.json
yarn tsc
yarn esbuild dist/tsc/*.js --outdir=dist/tsc --minify --allow-overwrite
Remove babel/webpack etc. :) less boilerplate

tsconfig.json:
{
  "compilerOptions": {
    "target": "es2017",
    "lib": [
      "es2018",
      "dom"
    ],
    "outDir": "dist/tsc",
    "rootDir": "src/",
    "allowJs": false,
    "skipLibCheck": true,
    "esModuleInterop": true,
    "allowSyntheticDefaultImports": true,
    "strict": true,
    "forceConsistentCasingInFileNames": false,
    "declaration": true,
    "declarationDir": "dist/types",
    "module": "esnext",
    "moduleResolution": "node",
    "resolveJsonModule": true,
    "strictNullChecks": true
  },
  "include": [
    "src/**/*.ts",
    "src/**/*.d.ts"
  ],
  "exclude": [
    "node_modules",
    "**/*.test.ts"
  ]
}

Some update?


Run data conversion pipeline with images data hosted on s3

Once we've got an allocated s3, I will upload our data onto it.

ISS data uploaded to s3://hindlimb/datasets/ISS/

As long as s3 credentials are correctly set in nextflow.config. Nextflow will download from s3 to local and then process as a local file. See https://github.com/haniffalab/sci-spatial-data/commit/68563998ec80c4d001c8443daab2271635c93cc0


Provide contribution guide

As we are open for everyone to contribute, we should provide a contribution guide to set expectations, explain how we work and how they can help.

Topics to cover (top of mind):

Open issue before contributing to see if it's something we want
What needs to be provided (tests, etc)
Code styling
How to get started


The PDF file has links, but when opened with PDF.js, there are no links.

Attach (recommended) or Link to PDF file here:
Configuration:

Web browser and its version:
Operating system and its version:
PDF.js version:
Is a browser extension:

Steps to reproduce the problem:

The PDF file has links, but when opened with PDF.js, there is no link, and it becomes a span tag.

What is the expected behavior? (add screenshot)
What went wrong? (add screenshot)
Link to a viewer (if hosted on a site other than mozilla.github.io/pdf.js or as Firefox/Chrome extension):

I hope I can click the click

Unless you provide all of the information requested in https://github.com/mozilla/pdf.js/blob/master/.github/ISSUE_TEMPLATE.md this issue will be closed as INCOMPLETE.

I updated the document on GitHub. You can reply to me when you are free. Thank you.
------------------ 原始邮件 ------------------
发件人: "Jonas<EMAIL_ADDRESS>发送时间: 2019年8月8日(星期四) 下午2:56
收件人<EMAIL_ADDRESS>抄送: "千笔"1009628609<EMAIL_ADDRESS>主题: Re: [mozilla/pdf.js] The PDF file has links, but when opened withPDF.js, there are no links. (#11053)
Unless you provide all of the information requested in https://github.com/mozilla/pdf.js/blob/master/.github/ISSUE_TEMPLATE.md this issue will be closed as INCOMPLETE.
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub, or mute the thread.

Attach (recommended) or Link to PDF file here:
http://scripts.sil.org/cms/scripts/render_download.php?format=file&media_id=DoulosSIL-features5.000.pdf&filename=DoulosSIL-features5.000.pdf
Configuration:

Web browser and its version:
Google Chrome  version: 75.0.3770.142（正式版本） （64 位）

Operating system and its version:

PDF.js version:
pdfjsVersion = '2.3.63';

Is a browser extension:

Steps to reproduce the problem:
1.

 Your browser does not support PDF reading

What is the expected behavior? (add screenshot)
can click the link of pdf
What went wrong? (add screenshot)
https://user-images.githubusercontent.com/28640116/62682154-06dccf00-b9ee-11e9-9778-f3dcbf7390b5.png
Link to a viewer (if hosted on a site other than mozilla.github.io/pdf.js or as Firefox/Chrome extension):

Duplicate of #3172.


How to reduce memory footprint

I would like to know how to setup max used memory for OrientDb (2.0.13).
I am using default configuration (-Xmx512)
I have one big collection with almost 1 000 000 records.
When I try to create an new index. OrientDb will use 1.3GB Ram and it stay on this value after this operation.
Is there any option to  set memory limit for OrientDb with bigger accuracy.
Thank you

This is more a year than an issue. Please post in Community Group where more than 2k users can answer to your question:
https://groups.google.com/forum/#!forum/orient-database
Thanks.


When are -first and -part created?

Under what circumstances does integrity create the -first and -part version files?   Here I have created a very simple directory structure with a get-first folder, but no -first or -part file is created.
(mp) C:\Users\User\Desktop\sec573\sec573a>dir /s
 Volume in drive C has no label.
 Volume Serial Number is 6000-8F6B

 Directory of C:\Users\User\Desktop\sec573\sec573a

04/29/2021  07:43 AM    <DIR>          .
04/29/2021  07:43 AM    <DIR>          ..
04/29/2021  07:38 AM                 7 fileonusb1.txt
04/29/2021  07:40 AM    <DIR>          get-first
               1 File(s)              7 bytes

 Directory of C:\Users\User\Desktop\sec573\sec573a\get-first

04/29/2021  07:40 AM    <DIR>          .
04/29/2021  07:40 AM    <DIR>          ..
04/29/2021  07:40 AM                 8 getmefirst.txt
               1 File(s)              8 bytes

     Total Files Listed:
               2 File(s)             15 bytes
               5 Dir(s)  53,190,905,856 bytes free

(mp) C:\Users\User\Desktop\sec573\sec573a>..\..\integrity.exe -c SEC573-99.1a
[+] Working directory: .
[+] Processing VERSION-SEC573-99.1a.txt...
[+] Processing fileonusb1.txt...
[+] Processing get-first\getmefirst.txt...

(mp) C:\Users\User\Desktop\sec573\sec573a>dir
 Volume in drive C has no label.
 Volume Serial Number is 6000-8F6B

 Directory of C:\Users\User\Desktop\sec573\sec573a

04/29/2021  07:44 AM    <DIR>          .
04/29/2021  07:44 AM    <DIR>          ..
04/29/2021  07:38 AM                 7 fileonusb1.txt
04/29/2021  07:40 AM    <DIR>          get-first
04/29/2021  07:44 AM               297 VERSION-SEC573-99.1a.txt
               2 File(s)            304 bytes
               3 Dir(s)  53,190,942,720 bytes free

Good question... I have the same result which did work before. Investigating now...

Ah. The tool is looking for get_first, not get-first.

The tool has been corrected to look only for get_first if we need to support multiple variations, lets discuss it.  In addition 2.1.0 is out that ensures that first and part files are only created if get_first exists and is not empty.


cogVideoX1.5-5B pipeline is very slow

System Info / 系統信息
ubuntu:20.04
cuda: 12.4
pytorch: 2.5.1
torchao: 0.6.1
diffusers: main branch (last commit: b5fd6f13f5434d69d919cc8cedf0b11db664cf06)
python: 3.10
GPU: NVIDIA RTX 4090
Information / 问题信息

[X] The official example scripts / 官方的示例脚本
[ ] My own modified scripts / 我自己修改的脚本和任务

Reproduction / 复现过程
download model into '/root/models/CogVideoX1.5-5B'
run huggingface model page quick start example (standard or quantized) only change the model path to local file.
GPU usage has reached 100% (but only 110w, fig1), and after waiting for a long time（at least an hour）, it's still at 0/50. When I cancel by ctrl+c, the traceback shows in fig2. If I comment out pipe.enable_sequential_cpu_offload, the model cannot be loaded into the GPU (even using pipe.to('cuda:0') does not work).  Is this normal? (CogVideoX-5B works fine in same environment.)

Expected behavior / 期待表现
achieving normal efficiency on the GPU

I have the same issue as well, I ran the code provided in the previous post on A100-80GB and CogVideoX1.5-5B text to video takes 30 mins to generate a video with num_inference_step set to 10 only. While with CogVideoX-5b it takes less than a minute. Please fix the pipeline,

The computational load of CogVideoX-5B is about one-fourth of CogVideoX1.5-5B. Therefore, you should multiply the time of CogVideoX-5B by 4. If your generation time is 10 seconds, then you also need to generate 5 seconds of time * 4 times in CogVideoX1.5-5B. If you are using A100, I suggest you turn off cpu_offload and turn on pipe.to("cuda"). 1000 seconds can generate a 5-second video.

Thanks for your comment. I double checked if the optimizations are turned off and reran as you suggested but it still takes a huge amount of time to execute. Following is the code that I am using
import torch
from diffusers import CogVideoXPipeline, CogVideoXDPMScheduler
from diffusers.utils import export_to_video
import time

subprocess.run(["nvidia-smi"])
torch.cuda.empty_cache()
print(torch.cuda.memory_allocated()/1024**2)
print(torch.cuda.memory_reserved()/1024**2)

pipe = CogVideoXPipeline.from_pretrained(MODEL_PATH, torch_dtype=torch.bfloat16)
pipe.scheduler = CogVideoXDPMScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
pipe.to("cuda")

#prompt = "A cat holding a sign that says hello world"

prompt: str = (
        "A garden comes to life as a kaleidoscope of butterflies flutters amidst the blossoms, "
        "their delicate wings casting shadows on the petals below. In the background, a grand fountain "
        "cascades water with a gentle splendor, its rhythmic sound providing a soothing backdrop. Beneath "
        "the cool shade of a mature tree, a solitary wooden chair invites solitude and reflection, its smooth "
        "surface worn by the touch of countless visitors seeking a moment of tranquility in nature's embrace."
    )

num_videos_per_prompt = 1
use_dynamic_cfg_flag = True
guidance_scale = 6.0
manual_seed = 4567

start = time.time()

video = self.pipe(
    prompt=prompt,
    num_videos_per_prompt=num_videos_per_prompt,  # Number of videos to generate per prompt
    num_inference_steps=num_inference_steps,  # Number of inference steps
    num_frames=81,  # Number of frames to generate，changed to 49 for diffusers version `0.31.0` and after.
    use_dynamic_cfg=use_dynamic_cfg_flag,  ## This id used for DPM Sechduler, for DDIM scheduler, it should be False
    guidance_scale=guidance_scale,  # Guidance scale for classifier-free guidance, can set to 7 for DPM scheduler
    generator=torch.Generator(device="cuda").manual_seed(manual_seed),  # Set the seed for reproducibility
).frames[0]

print("Time taken ", time.time()-start)

output_path = volume_path / "runs"
output_path.mkdir(parents=True, exist_ok=True)
output_file_path =  Path.joinpath(output_path, 'output.mp4')

This code has already been running for close to 30 mins and is not even at inference step 4. Based on the values you provided it should have finished in less than 1000 secs or about 17 mins but that doesn't seem to be the case. Is there any issue with the code segment and if not is it possible to check somehow on your end?

Hardware and Cuda info
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.90.07              Driver Version: 550.90.07      CUDA Version: 12.4     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA A100-SXM4-80GB          On  |   00000000:80:03.0 Off |                    0 |
| N/A   43C    P0             68W /  400W |       1MiB /  81920MiB |      0%      Default |
|                                         |                        |             Disabled |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+

Please set the default height and width, otherwise it will be 2400 * 2400 (in order to achieve different I2V, for normal operation, if you are t2v, please set weight = 1360, height = 768 to work properly, just like our cli demo).
In addition, what does self mean?
video = self.pipe(

Why not use pipe(.) directly?

Thank you for your prompt response. I added the weight and height and the inference time has come down to about 3 mins! I was following the huggingface example which doesn't specify these two parameters needs to be set. You may want to consider modifying it there else others may report issues.
Please ignore the self.pipe I was using a python class and it got copied over from there.
However there is still a small issue, looks like without the optimization it runs out of the 80 GB gpu memory as I am getting the following error. I tried to get the latest version of docker issued by nvidia (nvidia/cuda:12.6.2-cudnn-devel-ubuntu22.04) but looks like that also don't have the version 9.5.1 of cudnn. If you have any suggestions how to got about this or enable the v8 API let me know. Thanks again!
Loading checkpoint shards: 100%|██████████| 4/4 [00:11<00:00,  2.91s/it]it/s]
Loading pipeline components...: 100%|██████████| 5/5 [00:18<00:00,  3.62s/it]
100%|██████████| 10/10 [02:58<00:00, 17.80s/it]
/usr/local/lib/python3.11/site-packages/torch/nn/modules/conv.py:720: UserWarning: cuDNN cannot be used for large non-batch-splittable convolutions if the V8 API is not enabled or before cuDNN version 9.3+. Consider upgrading cuDNN and/or enabling the V8 API for better efficiency. (Triggered internally at ../aten/src/ATen/native/Convolution.cpp:430.)
  return F.conv3d(
Traceback (most recent call last):
Stopping app - uncaught exception raised locally: OutOfMemoryError('CUDA out of memory. Tried to allocate 3.98 GiB. GPU 0 has a total capacity of 79.14 GiB of which 1.52 GiB is free. Process 3386712 has 77.61 GiB memory in use. Of the allocated memory 54.21 GiB is allocated by PyTorch, and 22.89 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)').
  File "/pkg/modal/_container_io_manager.py", line 508, in handle_input_exception
    yield
  File "/pkg/modal/_container_entrypoint.py", line 383, in run_input_sync
    res = finalized_function.callable(*local_input.args, **local_input.kwargs)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/CogVideo_1_5B_test.py", line 174, in inference
    return self._inference(
           ^^^^^^^^^^^^^^^^
  File "/root/CogVideo_1_5B_test.py", line 146, in _inference
    video = self.pipe(
            ^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/utils/_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/pipelines/cogvideo/pipeline_cogvideox.py", line 761, in __call__
    video = self.decode_latents(latents)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/pipelines/cogvideo/pipeline_cogvideox.py", line 350, in decode_latents
    frames = self.vae.decode(latents).sample
             ^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/utils/accelerate_utils.py", line 46, in wrapper
    return method(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/models/autoencoders/autoencoder_kl_cogvideox.py", line 1287, in decode
    decoded = self._decode(z).sample
              ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/models/autoencoders/autoencoder_kl_cogvideox.py", line 1258, in _decode
    z_intermediate, conv_cache = self.decoder(z_intermediate, conv_cache=conv_cache)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/models/autoencoders/autoencoder_kl_cogvideox.py", line 978, in forward
    hidden_states, new_conv_cache[conv_cache_key] = up_block(
                                                    ^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/models/autoencoders/autoencoder_kl_cogvideox.py", line 655, in forward
    hidden_states, new_conv_cache[conv_cache_key] = resnet(
                                                    ^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/models/autoencoders/autoencoder_kl_cogvideox.py", line 299, in forward
    hidden_states, new_conv_cache["norm1"] = self.norm1(hidden_states, zq, conv_cache=conv_cache.get("norm1"))
                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/diffusers/models/autoencoders/autoencoder_kl_cogvideox.py", line 194, in forward
    norm_f = self.norm_layer(f)
             ^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1736, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/module.py", line 1747, in _call_impl
    return forward_call(*args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/modules/normalization.py", line 313, in forward
    return F.group_norm(input, self.num_groups, self.weight, self.bias, self.eps)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/torch/nn/functional.py", line 2955, in group_norm
    return torch.group_norm(
           ^^^^^^^^^^^^^^^^^
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 3.98 GiB. GPU 0 has a total capacity of 79.14 GiB of which 1.52 GiB is free. Process 3386712 has 77.61 GiB memory in use. Of the allocated memory 54.21 GiB is allocated by PyTorch, and 22.89 GiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

Update : I managed to do the inference with the optimizations on a A100-80GB. I upgraded the cudnn to 9.5.1 but the error as mentioned earlier didn't go away. With the following optimizations enables it takes about a minute longer to complete.
pipe.enable_sequential_cpu_offload()
pipe.vae.enable_slicing()
pipe.vae.enable_tiling()

Is it possible to verify if the model runs without needing optimization on A100 80GB? Thanks!

Exactly the same as the problem I encountered. I agree that the use cases on the huggingface model homepage should emphasize the settings of these two parameters

After adding pipe.enable_sequential_cpu_offload(), the speed is significantly slower, which is normal, but I don't understand why removing it causes your A100 to run out of memory, with the normal usage being around 40G.

After adding pipe.enable_sequential_cpu_offload(), the speed is significantly slower, which is normal, but I don't understand why removing it causes your A100 to run out of memory, with the normal usage being around 40G.

I met the same memory issue, without enable_sequential_cpu_offload A100 80G is running out of memory:

torch2.5.1+cu121
diffusers master(The most recent version from the past 1 or 2days)
CogVideo1.5 T2I with argument (num_frames, width, height) = (81, 1360, 768)

it cost 30-40GB at most when DiT running, when VAE decoding it raised error about OOM

maybe we could ask some huggingface friends for help, @a-r-r-o-w

Hi, thanks for the ping about this issue.
enable_sequential_cpu_offload is indeed a very slow optimization for memory. This is because it only loads one underlying nn.Module at a time on the GPU, performs computation, and moves the module back to the CPU. This introduces a lot of cuda stream synchronizations and additional wait times where no computation happens. There is an internal discussion going on about how we could optimize this a bit using async stream transfer for modules and prefetching the next required layer - but this will take a long time to get integrated. The idea is well tested and inspired from this post: https://x.com/gaunernst/status/1859192060966011032 if you would like to give it a try.
Also, maybe you could try enable_model_cpu_offload instead and see if that meets the requirements of being fast without using too much memory? Also, slicing is useful only when you have a batch_size > 1. Tiling is done in small 240x360 spatial tiles at the moment, but you could try reducing it by referring to internal implementation details (here) to see see if it helps.

Ohhh, maybe AvisP and me ran out of memory but ZR said 'but I don't understand why removing it causes your A100 to run out of memory, with the normal usage being around 40G.' is because:
ZR tests with vae_slicing & vae_tiling is ON and AvisP and me turn them off.
Is that right brothers?
Renting a gpu for trainning and not having access to a h200 and the frustration.
The only thing i see is tencents version to the opensource version really cutting into sora, but hardly anymodel can run it effectly, cogx5 is impressive, but not there, impressive because you can access it via api calls in command line, when that happens for sora or tencent you can make api calls then omg will automation be crazy.

@townwish4git Apologies for the delayed response but I carried out some tests with turning things on and off and here is what I observed. I tried to generate a video with image of height 1360 and width 768 with 20 inference step with some prompt
With the following turned on, time taken 7:49
pipe.enable_sequential_cpu_offload()
pipe.vae.enable_slicing()
pipe.vae.enable_tiling()

With only pipe.enable_sequential_cpu_offload() it took about 7:47
With pipe.enable_model_cpu_offload() as mentioned by a-r-r-o-w it was indeed bit faster taking about 6:03
And with none of them applied and with pipe.to('cuda') I am still getting out of CUDA memory.


How To Use Custom Accept Headers ?

Hi
I'm going to use Filtered Stream, but i don't know how to add "Accept-Encoding: deflate, gzip" to accept headers. please help me ...

Hi,
I'm trying to use the data-api. It also requires the  "Accept-Encoding: deflate, gzip" header. Can you please tell me how you solved this problem?


Deprecate test-client-utils package and remove usage

This package is almost empty anyway - it's re-exporting InsecureUrlResolver from test-runtime-utils and a trivial helper.  No need to keep it around.

The docs in test-client-utils' README seem worth keeping. We can move them to test-runtime-utils' README?

Done in latest.


Requirement for specific region settings

Hi just wondering if there is any method to force the Language/Region that will be used for the date pickers?
Right now the way the Power Bi viewer is using the browser to choose the date/region settings is causing an issue for me where my "English (Ireland)" (Windows 10 PC) is showing an "English (United States)" (Somehow chosen by MS Edge...) format? The way I'm dealing with locale and i18n for the rest of the app is by using an value from the users data, which makes Power Bi an outlier right now where it pulls its locale info from the users browser, Is there any way to change this?

That is defined in the pbix itself, when a new file is being created the region and language configuration is set in its creation, the visual components such as the date pickers take the defined region configuration that the pbix have in that moment as other components of the report. These configurations are kept even when the pbix is updated. I have seen some ways to deal with the problem: Premium has its own features to deal with region configuration. Another way without acquiring premium is to make other reports sharing the same dataset was created in the base report in order or not duplicating information and hitting the performance. Based on the client configuration on the client-side you can call the report with the corresponding region configuration.


DLL load failed error

I got this error while following the install guide. Any suggestions? thanks in advance

Have you built the project following the README.md (https://github.com/Turoad/lanedet/blob/main/README.md).
By the way, please raise issue in https://github.com/Turoad/lanedet/issues, if ithe issue is related to that project.


Support for Retrolambda 2.0.0's default methods

Retrolambda 2.0.0 added a new parameter retrolambda.defaultMethods for enabling support for backporting default methods and static methods on interfaces. This is off by default because there are some limitations.
The Gradle plugin needs to be updated to allow enabling the default method support.
Retrolambda's default method support is incompatible with incremental compiling, so when default methods are enabled, incremental compiling must be disabled.

@orfjackal Quick question, are you ignoring includedFiles when defaultMethods is true since otherwise it wouldn't process all the class files? I could make it so that includedFiles is not set if defaultMethods is, but if you just ignore it, then I wouldn't have to change anything if you can somehow use that information in the future.

It's not ignoring includedFiles.

Added in 3.0.0


feature request: context parameter

Feature request
As a developer I want to have the option of specifying a context as a string when registering dependencies so that I can register multiple interface implementations or subclasses without having to autowire any classes.
Motivation
Using a context, all classes can be kept loosely coupled from Poodinis at all times. Also, the developer can structure the dependency tree in one place rather than having to modify classes to specify autowire attributes.
Technical requirement (suggestion)
Associate the field
Registration[][TypeInfo] registrations
inside the class DependencyContainer with a context string, ie:
Registration[][TypeInfo][string] registrations
and overload the register method with a string parameter that allows the client to specify a context string parameter. Not specifying a string will result in registering in the "default" array. Resolving dependencies will first try to resolve within their registered context before reverting to the default context.

Could you give me a usage example? This request confuses me because there's already context registration in Poodinis, see https://github.com/mbierlee/poodinis/blob/master/TUTORIAL.md "Application Contexts"
This in combination with constructor injection helps you set-up dependencies without having to modify the classes themselves.

Even though implementation would be fairly straightforward, for the sake of not over-complicating the design I am inclined to close this request as a "won't do". The same can be achieved by setting up multiple dependency containers.


Destroy tooltip if no control is hovered

Currently tooltips can get stuck if you move your mouse fast enough such that it doesnt hover any control after the tooltip has opened. This PR addresses the issue by always destroying the tooltip if no control is currently hovered

_update_mouse_over() already handles this. In what situations can it fail?

I had a user that was able to reproduce it no matter what, when he moved his mouse from a control with a tooltip back to an area with no controls at all.  But even then not quite as consistent. I do not exactly now why _update_mouse_over() does not trigger. All I can say is that this PR fixed the issue.

CC @Sauermann


Sony Visca Over IP control byte incorrect

Sony Visca over IP module sends \x80 as the first byte in the command packet. This does not work with Lumens PTZ camera which supports Visca over IP.
Based on information here https://pro.sony/s3/cms-static-content/uploadfile/59/1237493025759.pdf the first byte should be between \x81 and \x87. \x88 is a broadcast byte. This byte represents the camera ID. In fact it states BRC-H900 locks this to \x81, although lumens cameras allow for full addressing.
I have modified the module code enough to test that changing the first byte to \x81 fixes the issue for lumens cameras set to address 1.
It would be really useful to have the ability to enter the camera ID in a dropdown when setting up the instance.
I've attached my modifications of the index.js file here.
Visca Over IP Fix.zip
Desktop (please complete the following information):

OS: 10.14.6
Browser Safari
Version 2.0.0

This issue is transferred to a test Issue

This may be an issue with BRC-H900 firmware previous to version 2.0
The BRC-X1000 manual is nearly identical and the X1000 works fine
I will update in a while once we send the BRC-H900 in to Sony to get chipped

Firmware 2.10 for the BRC-H900 alleviates the aforementioned issue


Bluetooth: controller: Fix assert during DLE

Fix assert in controller checking ticker_id_prepare = 0 when
a scanner and connection are active, and the connection is
skipping events in order to resize Rx buffers.
Signed-off-by: Vinayak Kariappa Chettimada<EMAIL_ADDRESS>

@alexsven @joerchan this is a very obvious bug fix. Early code has LL_ASSERT in this if clause, now when making the events to skip till the pool is free for resizing needs the ticker_id_prepare to be reset. Please approve so that the PR is merged.
@aescolar please do the needful in the absence of @carlescufi


QUIC bridging stop reconnecting after being kicked out

QUIC client doesnt reconnect to remote broker if session take over happens.
Need to handle this case by shutdown connection manually

Fixed in https://github.com/nanomq/NanoNNG/pull/590


Update session token via command message

Currently, the session token will expire in one day,
It's very convenient for me to  update session token via command message

Currently, the session token will expire in one day, It's very convenient for me to update session token via command message

good idea


[HOLD for payment 2023-05-29] [HOLD for payment 2023-05-25] Deleting thread replies results in "0 Replies"

Upwork Automation - Do Not Edit

Upwork Job URL: https://www.upwork.com/jobs/~01e6f62bce1dabf496
Upwork Job ID:<PHONE_NUMBER>156986368
Last Price Increase: 2023-05-16

https://expensify.slack.com/archives/C049HHMV9SM/p1684252528337349
Create a thread
Post one message in the thread
Delete the message you created in 2
See an unexpected result (0 replies) on the original room

cc @chiragsalian childCommentorCount not updated when deleting

Kindly let me know once the PR is ready. Would be happy to jump in on the review.

@grgia I think this issue is updated wrongly. It was already deployment 5 days back and payment due on 25/5.
And could you kindly add label, so that a automatic BZ member is assigned to this issue?

@isabelastisser could you help with C+ internal review payment?

@isabelastisser  Gentle ping on the payment.

Hi @abdulrahuman5196 , I sent you the invite in Upwork. Please accept it and I will hire and process the payment asap. Thanks!

@isabelastisser  I have accepted the invite.

The payment was made, and we are all set!


Updated url-regex to accommodate space delimited list of URLs

And added a test to assert new behaviour for multiple URLs in the input string.
Change is basically in the url-regex where I removed two non-capturing groups that were looking for spaces before/after the URL pattern. After that I just updated the outputted template. With those two changes, the tests were unchanged and passing.
I didn't look into supporting commas because they are a valid character in a URL string, so I think that is a reasonable compromise.
Refs https://github.com/johnotander/ember-linkify/issues/17

Looks great, thanks for the PR! I'm going to bump this a major version just in case someone depends on the existing behavior. Appreciate all your hard work 💖

Published to npm as<EMAIL_ADDRESS>

Also, @kamikaz1k, I'm looking for co-maintainers so if you're interested please let me know. Thanks again!

@johnotander Glad I could help :)
And yes I would like to be a co-maintainer. Did you need anything from me to set it up?

Invite sent, when accepted you'll get commit access to this repo 🍻.


Non-blocking initial load

Hi,
as far as I can see someone is working on speeding up initial load time https://github.com/firebase/polymerfire/pull/230. Unfortunately, there are some use cases where we'd like to show some data even if not all records are available, for example in some infinite-scrolling lists. The current implementation in master branch blocks the thread until all data is loaded. We have a prototype of a fairly simple solution to this problem using setTimeout.
I'd like to assign one of my employees to work on production-ready solution with extended documentation and tests, but I'd like it to be merged to official Polymerfire repo so we won't need to maintain our own fork merging all new releases of Polymerfire, since we do our best to use most up to date tools and libraries.
The question is: do you see a reason behind such option and can you guarantee, that if we provide the highest-quality solution to this problem, it will be merged into the official Polymerfire repo? If so, I'd also like to sign the Google's CLA on behalf of my company, Codemachine. How can I do this? I'm a co-owner and a board member of the company.

@merlinnot What you can do is just fork and do your solution, then do a PR. I don't know what's the timeline for the team but I do believe they are working on merging PRs that are really good.
As for what you have said, I agree that the data loaded blocks the thread. The good thing with loading a hundred units simultaneously using on('value') is it doesn't call the function for on('child_added') a hundred times (which blocks the main thread longer). With that said, data shows up instantaneously for a shorter period of time.
As for doing what you have said, I feel that having a setTimeout on on('child_added') (to force it to only be called when the main thread is free) will make the user see that the data is being added one by one in the iron-list every time the user goes to that page (unless the iron-list has a different array to look at).
A better strategy though is to use either Polymer.async and also add a flag on firebase-query (like async I guess) to say that you want the data to be loaded asynchronously

FYI I chatted with one of the Firebase DB SDK authors and he said that in general while child_added events are fired one by one, typically they don't start firing until the entire node has synced down and into memory. That means that the only perf benefit to "as they show up" would be if there's extremely heavy render cost. I think you can probably mitigate that in other ways.

If that's the case, it can be easily done without any modifications to polymerfire. Thanks for the feedback.


Url hash is changing, but viewport not scrolled

Hi. I have 15 React and 3 React Router. Do you supported it?
"react": "^15.4.2",
"react-router": "^3.0.2",

I have this markup:

              Link 1

              Link 2

              Link 3

              Link 4

              Link 5

<ScrollableAnchor id={"link1"}>

.......

        </ScrollableAnchor>

So it's not working. No errors in console. Url hash is changing, but viewport not scrolled

@indapublic the same here, the component doesn't work also with RR v4.

I have ended up with my own solution:
import React from 'react';
import { withRouter } from 'react-router-dom';

class ScrollToAnchors extends React.Component {
    componentDidUpdate(prevProps) {
        if (this.props.location !== prevProps.location) {
            const element = document.querySelector(this.props.location.hash);

            if (element) {
                element.scrollIntoView({
                    behavior: 'smooth'
                });
            }
        }
    }

    render() {
        return this.props.children;
    }
}

export default withRouter(ScrollToAnchors);

Also, for supporting smooth-scroll in all browsers I have added a polyfill.

@JonatanSalas Thank, Jonatan! I will try it sometime later.

You're welcome. Here I leave the correct code snippet. I have modified react-router-dom import to react-router. In this way, this code should work with react-router v2, v3 and v4.
import React from 'react';
import jump from 'jump.js';
import { withRouter } from 'react-router';

@withRouter
export default class ScrollableAnchor extends React.Component {
    componentDidUpdate(prevProps) {
        if (this.props.location !== prevProps.location) {
            const element = document.querySelector(this.props.location.hash);

            if (element) {
                jump(element, {
                    duration: this.props.duration || 500,
                    offset: this.props.offset || 0,
                    callback: this.props.callback || undefined,
                    a11y: this.props.a11y || false
                });
            }
        }
    }

    render() {
        return this.props.children;
    }
}

I had the same problem. Do you have a fixed navigation and the content is overlapped, so it isn't visible - but shown under the navbar?
This worked for me:
import { configureAnchors } from 'react-scrollable-anchor'; configureAnchors({ offset: -64 });


Unclear example code: Changing ChainPolicy after calling Build()

In the current example code
ch.ChainPolicy.RevocationMode = X509RevocationMode.Online;
is called after
ch.Build (certificate);
is called.
It is not clear if the change in ChainPolicy will have an effect on the validation or not. I assume that validation is done during the call to Build(), so I assume that any subsequent changes to ChainPolicy have no effect.

Document Details
⚠ Do not edit this section. It is required for docs.microsoft.com ➟ GitHub issue linking.

ID: 2f0cd090-00b3-72b3-ab0f-4223aa850a08
Version Independent ID: 7ee213d4-f96b-dcd6-cee7-4d416a0965c0
Content: X509Chain Class (System.Security.Cryptography.X509Certificates)
Content Source: xml/System.Security.Cryptography.X509Certificates/X509Chain.xml
Service: unspecified
Product: .net
GitHub Login: @mairaw
Microsoft Alias: mairaw

@bartonjs can you help with this question?

I agree with the reporter.  Changing ChainPolicy after calling Build has no practical effect (other than it can change what the next call to Build does).
X509RevocationMode.Online is the default, so the easiest fix is probably just to remove that line.

Or moving the line to before the call to Build() 🙂. Most examples for the members of this class need improving.

I was going to remove the call but decided to just move it above the Build call given this sample was also used by the X509RevocationMode API.
PR to change that is here: https://github.com/dotnet/samples/pull/323