too many open files

I'm worried that Scalar is causing me to not be running git gc enough. Is there something I can do to check?
The symptom I'm seeing, is after a while, I get this failure when git pushing:
$ git push
...
ref <sha>:: open <path>git/objects/pack/pack-<sha>.pack: too many open files

Then if I run
$ git gc
Enumerating objects: 1395635, done.
Counting objects: 100% (1395635/1395635), done.
Delta compression using up to 12 threads
Compressing objects: 100% (325900/325900), done.
Writing objects: 100% (1395635/1395635), done.
Total 1395635 (delta 938477), reused 1390778 (delta 933690), pack-reused 0
Checking connectivity: 1395929, done.

It starts to work again.
I do see scalar running in my repo:
$ scalar list
/Users/paul.tarjan/robinhood/rh-staging
/Users/paul.tarjan/robinhood/rh

Hi @ptarjan. Thanks for pointing out this issue. If it happens again, could you run ls -al .git/objects/pack?
As reported elsewhere, there is some thought that on "small" repos, the 2-gigabyte batch-size in the PackfileMaintenanceStep is not repacking pack-files often enough. I will be updating this behavior to work better for repos of this size.

Here is the Git contribution I was thinking about.

Thanks for the response. In my case, my repo is our huge company monorepo. So 4GB .git directory, 100k files, 100k commits, so I doubt I'm hitting the small repo problem?
My ulimit is 256 (no idea why, maybe my company sets that default) maybe that's what's causing this?

Thanks for the clarification, @ptarjan. 4GB is on the low end of my "medium-size" scale, compared to repos that I'm used to. ;)
The "small repo" problem I'm talking about is that your incremental fetches are much smaller than 2 GB. I bet that if you list your pack-files (some time after your recent gc) you'll have one "big" pack-file and many smaller pack-files. Those smaller pack-files are too small to trigger the 2GB batch size of the git multi-pack-index repack command that Scalar uses.
Yes, a ulimit of 256 is incredibly low. It is typically 10x that.

Hey! Sorry for dropping the ball here. We're now deploying this to our whole org so we're actually getting more reports from our users about it.
It seems the default ulimit is 256? We tried on a personal vanilla OS X 10.15.6 and it was also 256.
If that is the case for mac, is there some other git command that Scalar can do which would help here? It seems git gc resolves the issue every time so should we just cron that onto people's machines? It seems that if Scalar is already trying to maintain the state of the repo, that this would be Scalar's job?

Hey! Sorry for dropping the ball here. We're now deploying this to our whole org so we're actually getting more reports from our users about it.
It seems the default ulimit is 256? We tried on a personal vanilla OS X 10.15.6 and it was also 256.

I'm hesitant to push for updating ulimit here, but that might be the best option for now.

If that is the case for mac, is there some other git command that Scalar can do which would help here? It seems git gc resolves the issue every time so should we just cron that onto people's machines? It seems that if Scalar is already trying to maintain the state of the repo, that this would be Scalar's job?

If you have the ability to do that, then that's a good short-term option. The next version of Git will include the update to git multi-pack-index repack (here it is as a commit in master), so Scalar's incremental repack strategy should suffice when we ship that version.
Thank you for your patience here! We appreciate the feedback.

This is still an issue for us
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This is still an issue for us

Have you upgraded to Git 2.29.0 or later? If you haven't, then please do.
 If you haven't, then run ls -al .git/objects/pack before and after. Then run it again. Let me know what you see.

Thanks for the advice. I'll get folks that complain about this to upgrade to git 2.29.0. I just did it myself to keep an eye on it.
Should I have to run scalar run pack-files regularly or is this an exceptional thing? I just ran it and it did remove a few files from that directory but there are still lots. Is that a problem?

Thanks for the advice. I'll get folks that complain about this to upgrade to git 2.29.0. I just did it myself to keep an eye on it.
Should I have to run scalar run pack-files regularly or is this an exceptional thing? I just ran it and it did remove a few files from that directory but there are still lots. Is that a problem?

The Scalar service runs the pack-files step about once a day. If you want to accelerate its behavior, you can run it a few times in a row. It runs daily to avoid over-taxing the user with CPU time in the background. Also, if concurrent foreground commands are running across two runs of the pack-files step, then those foreground commands could fail due to expecting a pack-file that was deleted out from under them. If you are in control and not simultaneously running Git commands, then repeated runs of scalar run pack-files should incrementally improve your .git/objects/pack directory until reaching a stable state.
If you are not reaching a stable state, or are otherwise unhappy with the end result, then I'd love to see the output of ls -al .git/objects/pack to understand the size of your pack-files and how that might be affecting our batch-size calculation.

Thanks for all the debugging help. I do have a instance of where a user had:
$ git --version
git version 2.29.2
$ ulimit -n
256

but was getting the symptom:
ref 8235f832bfb63026ab64c70bab1febb0c4b85b28:: open <path>/.git/objects/pack/pack-fe386ebacdbae3b584fe256738f8d90c11053b51.pack: too many open files

and git gc fixed it for them. Sadly I wasn't able to get them to try scalar run pack-files before they ran git gc.
So I don't think that git 2.29.0 is enough to mitigate this sadly. I'll keep pining anytime one of my users notices this.

Unfortunately, the feature I was hoping would land in 2.29.0 (git maintenance run --task=incremental-repack) did not actually land until 2.30.0. It is probably enabled in v2.29.0.vfs.0.0 or later.
As of the latest Scalar release on macOS, we have these two changes:

scalar run <task> essentially just runs git maintenance run --task=<task> (with some mapping from the Scalar names to the Git names, but the functionality is very similar). This should have been improved to prevent this "too many files" case, at least usually.

The Scalar.Service application is removed in favor of running git maintenance start. This takes a feature that only recently landed in git/git's master branch, so it will be in core Git in 2.31.0 but is not in 2.30.0.

Thanks for all the debugging help. I do have a instance of where a user had:
$ git --version
git version 2.29.2
$ ulimit -n
256

but was getting the symptom:
ref 8235f832bfb63026ab64c70bab1febb0c4b85b28:: open <path>/.git/objects/pack/pack-fe386ebacdbae3b584fe256738f8d90c11053b51.pack: too many open files

and git gc fixed it for them. Sadly I wasn't able to get them to try scalar run pack-files before they ran git gc.
So I don't think that git 2.29.0 is enough to mitigate this sadly. I'll keep pining anytime one of my users notices this.

Unfortunately, the feature I was hoping would land in 2.29.0 (git maintenance run --task=incremental-repack) did not actually land until 2.30.0. It is probably enabled in v2.29.0.vfs.0.0 or later.
As of the latest Scalar release on macOS, we have these two changes:

scalar run <task> essentially just runs git maintenance run --task=<task> (with some mapping from the Scalar names to the Git names, but the functionality is very similar). This should have been improved to prevent this "too many files" case, at least usually.

The Scalar.Service application is removed in favor of running git maintenance start. This takes a feature that only recently landed in git/git's master branch, so it will be in core Git in 2.31.0 but is not in 2.30.0.

This just happened to me personally. Then by running:
$ git maintenance run --task=incremental-repack
Enumerating objects: 89559, done.
Counting objects: 100% (89559/89559), done.
Delta compression using up to 12 threads
Compressing objects: 100% (63722/63722), done.
Writing objects: 100% (89559/89559), done.
Total 89559 (delta 23834), reused 83651 (delta 17987), pack-reused 0

it resolved it.
I have:
$ scalar --version
scalar <IP_ADDRESS>
$ git --version
git version 2.30.0

This just happened to me personally. Then by running:
$ git maintenance run --task=incremental-repack
Enumerating objects: 89559, done.
Counting objects: 100% (89559/89559), done.
Delta compression using up to 12 threads
Compressing objects: 100% (63722/63722), done.
Writing objects: 100% (89559/89559), done.
Total 89559 (delta 23834), reused 83651 (delta 17987), pack-reused 0

it resolved it.
I have:
$ scalar --version
scalar <IP_ADDRESS>
$ git --version
git version 2.30.0

Sadly I have to reopen this ticket. I rolled out the latest scalar version (<IP_ADDRESS>) to our fleet and now my users are reporting they are seeing Too many open files often. We all have git version 2.31.0.vfs.0.1. Is there some diagnostics I can collect for you when it happens to my users?

Why did this close?


[release-1.21] Fix a concurrent map write error

This is an automated cherry-pick of #49866

@istio-testing: The following test failed, say /retest to rerun all failed tests or /retest-required to rerun all mandatory failed tests:

Test name
Commit
Details
Required
Rerun command

unit-tests-arm64_istio_release-1.21
01d6cbf861555523a95ca9b146a76145d32cd7af
link
true
/test unit-tests-arm64

Instructions for interacting with me using PR comments are available here.  If you have questions or suggestions related to my behavior, please file an issue against the kubernetes/test-infra repository. I understand the commands that are listed here.

@istio-testing: The following tests failed, say /retest to rerun all failed tests or /retest-required to rerun all mandatory failed tests:

Test name
Commit
Details
Required
Rerun command

unit-tests-arm64_istio_release-1.21
01d6cbf861555523a95ca9b146a76145d32cd7af
link
true
/test unit-tests-arm64

integ-security-multicluster_istio_release-1.21
01d6cbf861555523a95ca9b146a76145d32cd7af
link
true
/test integ-security-multicluster

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/retest


NaNs in LensUI 2.19 instead of timings

Describe the Bug
There is a bug with trace rendering in LensUI 2.19. I see NaNs instead of timings and there are no spans displayed.

Steps to Reproduce
Upload trace https://gist.github.com/f0y/1fd8461bd52c522acd71061ebeff965e

Thank you for your report!
If timestamps are not set for some spans, it seems that UI cannot handle it well.
I'll fix this bug as soon as possible.

If timestamps are not set for some spans, it seems that UI cannot handle it well.

I agree it isn't good for the UI to fail to render entirely, but I'm wondering if there's an instrumentation bug or some other reason why some of the spans don't have a timestamp. From the API documentation on the timestamp field:

Epoch microseconds of the start of this span, possibly absent if
incomplete.
For example,<PHONE_NUMBER>000000 corresponds to 2017-08-15 09:00 UTC
This value should be set directly by instrumentation, using the most
precise value possible. For example, gettimeofday or multiplying epoch
millis by 1000.
There are three known edge-cases where this could be reported absent.

A span was allocated but never started (ex not yet received a timestamp)
The span’s start event was lost
Data about a completed span (ex tags) were sent after the fact

Maybe this is the type of situation we should give an indication in the UI that the data should be looked at to determine why it is missing generally expected elements.

Agree with Tommy. This is not normal situation, this could happen either in a bug in instrumentation or a misuse of the tracer (I have seen some instrumentation creating spans for things that should be logs). In either case we should warn the user.


The skip_path config should also be considered in flow control commands

Now, skip_path is designed only for bt command so that description says it's "UI" category.
I understand the motivation, if we skip on step command, should it be a Control category?

@ko1 I agree with that 👍 I've updated its category and added test case for the change.

skip_nosrc is already CONTROL option. wow.

oh I didn't notice that, good catch 👍 I've updated it too.


Error with cdnjs and jsDeliver

I get an error message when loading Holder.js from cdnjs and jsDeliver but it works fine with RawGit.

http://codepen.io/fpoirier1/pen/VLbKBY

http://www.jsdelivr.com/#!holder is the website, the actual file is https://cdn.jsdelivr.net/holder/2.8.0/holder.min.js

Here is the Codepen, updated with the correct JS source and src syntax:
http://codepen.io/anon/pen/doWOWO


Documentation of the esp-prog with esp-boards. (IDFGH-5767)

Is your feature request related to a problem?
No.
I was doing the set to debug the esp-wroom-32D with esp-prog for that I was searching the document on official esp document sites. But I did't found much documentation on this.
Request:
Can you add documentation to debug esp boards with esp-prog with pics. If possible add some videos for setup and example of debugs.
Regards,
Raghav Jha

Hi @Raghav3107, in case you did not find it already, a generic JTAG debugging documentation is available in:

Introduction to the ESP-Prog Board
JTAG Debugging

By "set to debug" do you mean wiring and configuration to debug or something else? By "esp-wroom-32D" do you mean set to debug a separate module or a developement board that contains this module?

@krzychb  thanks for the reply.

Introduction to the ESP-Prog Board
JTAG Debugging

I checked all this documents, i m able to configure the ESP-PROG with esp32.
But JTAG documents is little bit complicated and  esp-prog documentation have only the intro part.
It will be better if you add some example videos where you show how to configure the jtag and esp-prog with esp32.
Thanks for the help!!


Upgrade to WildFly Core 2.0.0.Beta1 and Build Tools 1.1.0.Beta2

Windows Build 2408 is now running using a merge of 196abd65ab0ccd38499ba016ddfaa7401def9525

Linux with security manager Build 2223 is now running using a merge of 196abd65ab0ccd38499ba016ddfaa7401def9525

Linux Build 7360 is now running using a merge of 196abd65ab0ccd38499ba016ddfaa7401def9525

Linux with security manager Build 2223 outcome was SUCCESS using a merge of 196abd65ab0ccd38499ba016ddfaa7401def9525
Summary: Tests passed: 889, ignored: 288 Build time: 0:08:31

Linux Build 7360 outcome was SUCCESS using a merge of 196abd65ab0ccd38499ba016ddfaa7401def9525
Summary: Tests passed: 3082, ignored: 368 Build time: 0:48:40

Windows Build 2408 outcome was SUCCESS using a merge of 196abd65ab0ccd38499ba016ddfaa7401def9525
Summary: Tests passed: 3082, ignored: 368 Build time: 0:50:58


Failed to connect to api.gcorelabs.com port 443 after 21233 ms: Timed out

nvm>node ./main.js
Command failed: curl https://api.gcorelabs.com/cdn/public-net-list
% Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
Dload  Upload   Total   Spent    Left  Speed
0     0    0     0    0     0      0      0 --:--:--  0:00:21 --:--:--     0
curl: (28) Failed to connect to api.gcorelabs.com port 443 after 21263 ms: Timed out

As you can see Timed out, it is obviously due to the network.
Try using your VPN on the terminal before running this script

this domain is blocked in China,  check out link below:
https://ping.chinaz.com/api.gcorelabs.com

In this commit :dfe75aaee51ea88a70e1aac44c2f24f929c17210, I try to use local IP ranges to address problem that is due to network.

In this commit :dfe75aaee51ea88a70e1aac44c2f24f929c17210, I try to use local IP ranges to address problem that is due to network.

I tried to update IP ranges again today. And I will use github actions to automatically update IP ranges.

schedule update task coming up in this PR:https://github.com/BruceWind/GcoreCDNIPSelector/pull/4


kubectl gs template cluster should support --context flag

The kubectl gs template cluster command, for some providers, relies on contact to a management cluster in order to retrieve details/defaults from the management API.
For example, for --provider gcp, there must be a GCP management cluster available.
In order to be able to run a kubectl-gs command without having to pre-select a context, we should make sure to support the --context flag to select a contect. Example:
kubectl gs template cluster --context gs-foobar --provider gcp ...

KaaS Sync:

@marians is going to talk with @giantswarm/team-rainbow to see if it can be globally implemented for all commands.

Done, related https://github.com/giantswarm/roadmap/issues/1230


jump to any file outside of the project root in win10

how to set the symlink in win10?
I have read this solution with linux,but no idea with win10, help me!
see the url: https://github.com/krassowski/jupyterlab-go-to-definition/blob/master/README.md#which-directories-to-symlink

Even if that registry bit is set on windows, the are so many sharp edges:
with the whole windows drive letter thing, and its other various flavors,
there isn't an easy answer to solving this correctly on windows with the
jupyter contents API, which is what the symlink approach relies on.
In the near term, the most repeatable approach I have found is to put a
virtual environment (conda or venv) inside the contents root under e.g
.venv, and not even bother with the symlink.
There is probably an opinionated part forward with e.g.
https://github.com/viaduct-ai/hybridcontents but it would take some
investigation... And unfortunately, in a vicious circle kind of way, the
contributors to this project are primarily interested in jupyterhub (or
otherwise Linux-adjacent) features.


Need secure and fast client downloads for China

As described by @btswildpig:

[12:20:03 AM] pig wild: Can you guys think of a solid and secure way of downloading the new wallets other than Github ?
[12:36:01 AM] Dan Notestein: what's wrong with github?
[12:37:21 AM] pig wild: the accessing speed from China is very slow due to the GFW or other network condition
[12:37:29 AM] Dan Notestein: ic
[12:37:43 AM] pig wild: may need HTTP download from bitshares.org
[12:38:08 AM] Dan Notestein: is the download from bitshares.org any faster?
[12:40:28 AM] pig wild: oh , not much now , it was fast before .
[12:41:07 AM] pig wild: I can only get 60KB/s from bitshares.org
[12:41:28 AM] pig wild: and the client on that site is not up-to-date as github

Torrents and bitshares.org server seem to be sufficient for now. We can revisit if there are complaints.


Coveralls is looking into gem dependencies' code and reports they're not covered...

I've made a small gem (SmsSafe), and it currently has 100% code coverage (according to SimpleCov).
However, according to Coveralls, it only has 41% coverage (report here).
The reason for that difference seems to be that coveralls is taking the code from my gem's dependencies as part of my code, and complaining that those aren't covered...
I haven't seen it do this in any other gems I've looked into, and I haven't seen any special coveralls configuration in those gems' codebases...
The way I'm calling coveralls is by having this in my Rakefile:
require 'coveralls/rake/task'
Coveralls::RakeTask.new
task :test_with_coveralls => ["test", "coveralls:push"]

and by having Travis evecute "test_with_coveralls":
script: bundle exec rake test_with_coveralls

Which is the right way of adding it according to their docs
Any ideas why this might be happening?

This is what I am actually looking for (look into gem's dependencies and show coverage on them)


Fix code formatting

Codecov Report

Merging #369 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master     #369   +/-   ##
=======================================
  Coverage   68.34%   68.34%
=======================================
  Files         124      124
  Lines        3456     3456
  Branches      233      233
=======================================
  Hits         2362     2362
  Misses        964      964
  Partials      130      130

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 9b4556f...1362ef0. Read the comment docs.

@spencergibb You were too fast! I was going to add another commit to this PR.
I'll have to open a new one...

haha. Caught me at the right moment :-)


Code organization

Some improvements can be made to organization of the code.

Working on it. Adding comments to clarify.


ModuleNotFoundError: No module named 'huicv.evaluation'

ModuleNotFoundError: No module named 'huicv.evaluation'
Hello, I don't know why I get this error when I run retinanet

Thanks for the feedback, it may be caused by the wrong URL for submoudle we given, We will fixed as soon as we can now.

Thanks for the feedback, it may be caused by the wrong URL for submoudle we given, We will fixed as soon as we can now.

Thanks, I ran retinanet 50, trained to 2000+ iterations, cls_loss is nan, and I didn't change all the parameters?

After downloading TOV_mmdetection, the huicv need to be downloaded to TOV_mmdetection/huicv.
git clone https://gitee.com/ucas-vg/TOV_mmdetection # git clone https://github.com/ucas-vg/TOV_mmdetection
cd TOV_mmdetection
# download code for evaluation
git clone https://gitee.com/ucas-vg/huicv # git clone https://github.com/yinglang/huicv/

The huicv project contains the evaluation code.

otherwise，in the Readme,md，this url ：https://github.com/ucas-vg/TOV_mmdetection/blob/main/exp/doc/code_modify.md can not visit，I would like to know what configuration needs to be changed to run on the original mmdetection， thanks

otherwise，in the Readme,md，this url ：https://github.com/ucas-vg/TOV_mmdetection/blob/main/exp/doc/code_modify.md can not visit，I would like to know what configuration needs to be changed to run on the original mmdetection， thanks

Thanks for the feedback, it may be caused by the wrong URL for submoudle we given, We will fixed as soon as we can now.

Thanks, I ran retinanet 50, trained to 2000+ iterations, cls_loss is nan, and I didn't change all the parameters?

For the unkown reason, the loss of training retinanet in TinyPerson with mmdetection is easy to get nan.  (maybe 9 times got nan if totoally running 10 times). Using this config with grad clip strategy instead the origin one, the loss come more stable.

otherwise，in the Readme,md，this url ：https://github.com/ucas-vg/TOV_mmdetection/blob/main/exp/doc/code_modify.md can not visit，I would like to know what configuration needs to be changed to run on the original mmdetection， thanks

Thanks for your reminding，the file has been added.

otherwise，in the Readme,md，this url ：https://github.com/ucas-vg/TOV_mmdetection/blob/main/exp/doc/code_modify.md can not visit，I would like to know what configuration needs to be changed to run on the original mmdetection， thanks

Thanks for your reminding，the file has been added.

Thank you so much!


Preprocessed data links no longer work

The preprocessed dataset links for subject 1 (https://dataset.ait.ethz.ch/downloads/IMavatar_data/data/yufeng.zip) and subject 2 (https://dataset.ait.ethz.ch/downloads/IMavatar_data/data/soubhik.zip) are not working. Could you please check/fix? Thanks!

find them from below link:
subject_1, subject_2

Hey, for these links the access is required, could you please provide it?


Fixed some broken links

Ah sorry, @prcr, that's a commit automatically by this app to compress the images in the repository, and it looks like I messed up the commit.
Because of that, I deleted your forked repository in my account and then forked it again, and now I've made changes to fix the broken link and opened this pr #77.


indexedfs: implement Rename for directories

https://github.com/tractordev/wanix/blob/2868431b7502be5c8c2b9b3594be0d698b950635/internal/indexedfs/indexedfs.go#L291
With current behavior, renaming a directory only moves the root directory file and not it's children.

We might want to change the schema from just a path to a name and a parent ID. This would make move/rename operations not need to change children. The tradeoff would be path lookups would be slower, but we can always cache them in memory. As long as we are careful to expire all the child paths on a move...


Use TextPainter.preferredLineHeight to estimate line height for Cupertino selection handles

Fixes https://github.com/flutter/flutter/issues/12046

Test?

done - PTAL

This LGTM as an incremental fix now to stop the crash, though I think it has the same concerns Ian had for #11353 which was more or less the same PR.

Meta: now also fixes #11261


Virtual Keyboard event binding problem

Hi I would like to use https://terminal.jcubic.pl/virtualKeyboard.html but if I press ENTER or TAB it does not do anything. According code, event should be send back to terminal, but it looks like somewhere it got broken.
Could you check it?

The virtual keyboard demo was created because the library was not working on mobile, and I've did't tested very much. but I'll check why tab is not working.

I've updated this old demo, new API require to invoke 3 events keydown keypress and keyup.

Thanks for the fix.


Test Issue created at Wed, 29 Dec 2021 02:22:11 GMT

Test issue body  Wed, 29 Dec 2021 02:22:11 GMT

Comment on issue at Wed, 29 Dec 2021 02:22:14 GMT


Multiple eval metrics, combination of default and custom

The following code is not working, where aucerr and aoeerr are custom evaluation metrics, it is working with just one eval_metric either aucerr or aoeerr
prtXGB.fit(trainData, targetVar, early_stopping_rounds=10,
eval_metric= [aucerr, aoeerr], eval_set=[(valData, valTarget)])

However, the following code with in-built evaluation metrics is working
prtXGB.fit(trainData, targetVar, early_stopping_rounds=10,
eval_metric= ['auc', 'logloss'], eval_set=[(valData, valTarget)])

Here are my custom functions
def aucerr(y_predicted, y_true):
    labels = y_true.get_label()
    auc1 = metrics.roc_auc_score(labels,y_predicted)
    return 'AUCerror', abs(1-auc1)

def aoeerr(y_predicted, y_true):
    labels = y_true.get_label()
    actuals = sum(labels)
    predicted = sum(y_predicted)
    ae = actuals/predicted
    return 'AOEerror', abs(1-ae)

From what I understand, it is not possible to supply multiple custom evaluation functions the way you do it. See #1125 for a workaround.


Verify that "Valea Mică" is listed in the dropdown menu when searched

Description:
"Valea Mică" should appear in the dropdown menu with correct spelling and locality information.
Preconditions:
The website is up and running.

Step 1
Type "Valea Mică" in the search bar.
Expected results:
The dropdown is listing "Valea Mică" as the first location in the dropdown menu.

Step 2
Observe the dropdown menu.
Expected results:
"Valea Mică" is displayed and selectable from the dropdown menu.


Export lz4 and zstd dependencies for mcap_vendor

Closes #55

Exporting dependencies from header files from lz4 and zstd libraries.
Note: It turns out that on my local machine include forzstd.h was taken from local usr/include/zstd.h instead of the  downloaded version specified in mcap_vendor package.
I have to export zstd header files the same way as lz4 since CI was failing.
It also will solve some potential hidden compilation errors in future if our dependent zstd library will diverge from installed by default with Linux distro.

@jhurliman @emersonknapp Can we come to some compromise solution?
I removed definition for MCAP_IMPLEMENTATION from mcap_vendor main.cpp.
Currently it's defined only in one place in mcap_storage.cpp.
If someone else will need to use mcap_vendor package outside of the rosbag2 they will need to make the same define for MCAP_IMPLEMENTATION in their code.
I recognize that it's a bit less straight forward solution rather then just include mcap_vendor as dependencies. I can add readme file with description about it. At the end it's no more than just like one more include. I mean those one who will be using mcap via mcap_vendor they will need to be aware what header file to include and it will be one more step to do to add those definition.
Currently no one using mcap_vendor package among us in Rosbag2 and it's not going to be hassle.
As regards to a potential issue if someone will start using mcap_vendor in some another project and will need zstd or lz4 with different version we can get back to this issue and either bump versions for those libs in mcap or will try to find some another workaround.
In worst case scenario we can revert this commit.

Note: It turns out that on my local machine include forzstd.h was taken from local usr/include/zstd.h instead of the downloaded version specified in mcap_vendor package.

I don't have all of the context here, but I do think MCAP should use the system zstd (and lz4) when they are available.  Not doing this can cause problems later on (mostly potentially nasty ABI issues).  It's the pattern we follow almost everywhere else, with a few minor exceptions.
So with that said, I think the fact that this vendor package pulls a few files from zstd and lz4 and compiles them is not the right way to go.  Instead, we should have proper vendor packages (and we don't even need one for zstd, we have that already).

Linking some prior discussion on vendor setup for reference:

https://github.com/ros-tooling/rosbag2_storage_mcap/pull/28#issuecomment-1112435006
https://github.com/ros/rosdistro/pull/32534#issuecomment-1086286672

One more point towards my proposed solution is that if someone will need to use mcap format in ROS2 ecosystem they will likely be using rosbag2_cpp API or rosbag2_storage_mcap plugin rather then mcap_vendor package directly.
Please note that mcap_vendor is internal sub package in rosbag2_storage_mcap package and was created to serve it.
@clalancette As regards that mcap should be using the system zstd and lz4 when they are available and from specific vendor packages.
We've tried to consider this opportunity on today's WG meeting and figured out that it's not possible currently at least for zstd.
Because mcap itself depends from zstd API available in version 1.5.2, but by default in Ubuntu 20.04 is 1.4.4 version. It means that users with Ubuntu 20.04 will not be able to compile mcap_vendor package if we will switch to the current zstd_vendor package and even if we will bump zstd version to the 1.5.2 in it.

After some consideration I tend to incline to close this PR and relevant issue as will not done.
The rationale for that is that it is not good to export lz4 and zstd dependencies since it could cause some ABI issues in future and in case if someone will start using mcap_vendor in some another project and will need zstd or lz4 with different version.
@clalancette I figured out how to compile mcap_vendor package with zstd_vendor package as dependencies without pulling zstd from git repo and compiling it from source. Perhaps we will be able to do the same with lz4.
Long story short it will require fix inside mcap cpp implementation and multiple adjustments in mcap_vendor cmake file.
There are one caveat that we will need to bump zstd version in zstd_vendor to the 1.5.2. This is the latest version of the zstd version and not available by default in Ubuntu 22.04.
We still can have the rule to use locally installed version without mandatory downloading it. But the problem is that it's going to cause downloading it since this 1.5.2 version is not available yet by default.
In my Ubuntu 22.04 installation zstd with version 1.4.8.
Is it ok to go with this approach and bump zstd version to 1.5.2?

What's the reason that mcap depends on such a new version of zstd? Can it be updated to support older versions?

What's the reason that mcap depends on such a new version of zstd? Can it be updated to support older versions?

We've been trying to reduce the number of vendored packages that we actually build[1] on our primary platform, Ubuntu 22.04.  This reduces compile times and integrates much more nicely with the base system.
Thus, if there is any way we can make mcap use zstd 0.4.4 (the version current in Ubuntu 22.04), that would be ideal.
[1] In the interest of full disclosure, we aren't there yet.  We unconditionally vendor at least OGRE and libyaml currently, but ideally we'd make both of those conditional as well.  Most of our other vendored packages are conditional.

@clalancette @amacneil I re-posted our discussion in newly created https://github.com/ros2/rosbag2/pull/1118#issuecomment-1273951249
Please continue discussion there.

Closing this PR as will not done for the sake that this is not very good to export lz4 and zstd dependencies since it could cause some ABI issues in future and in case if someone will start using mcap_vendor in some another project and will need zstd or lz4 with different version.


Addedd support for SAP Sql Anywhere database

Addedd compiler for SAP SqlAnywhere database

Really helpful!,
but sorry we are not accepting new compilers.
It would be greate if you create a separate package for this one


feat: Add support for Helia.

After the release of Helia, maintenance for js-ipfs is stopping so this PR adds support for Helia alongside the original ipfs-core interface.
This is done by using the underlying libp2p API where possible (since both ipfs-core and helia expose it) and checking which of the blockstore  or block properties are exposed.
This PR also refactors the tests to use the more lighter weight helia package instead of ipfs-core.

Helia requires a persistent block storage in order to work with OrbitDB, the default memory will not work unless the LevelStorage that stores the heads is cleared first, otherwise Helia looks for a block that is no longer there. An alternative way to fix this is remove the persistent storage of the heads created here.
Although this causes problems with Helia when using the default memory block store, it is not a problem with this fork per se since the same problem will happen with ipfs-core in the current implementation if the IPFS storage does not persist or is cleared.
This fork should be complete and functional but someone will need to take a look and figure out how to handle the situation if the blocks to the heads no longer exist.

Is there anything I could help with here, or is this purely awaiting maintainer review?

Is there anything I could help with here, or is this purely awaiting maintainer review?

Yeah, just waiting for the maintainers to have a look, they did tell me that they wanted time to look into Helia and it would be some time before they got to it.
I have been using it for a while and it does seem to work pretty good (other than the potential issue I describe in my last comment) but I should update this fork.

Looking forward to Helia integration with orbit-db-nextgen

Thanks for the effort, @saul-jb! Would love to see OrbitDB migrating over to Helia. That would rock!
Let me know if I may be of help to get it closer to completion, I can dedicate a couple of weeks to that

This is quite amazing. Tbh I don't really like js-ipfs and Helia seems like a much better ipfs implementation. I want to migrate the application I am writing for my degree thesis to Helia but since I use OrbitDB as an integral part of my application I am kind of waiting on this.
I have some questions regarding this fork: will this be a new separate orbitdb package for helia? or is this just a new fork to work on features to keep Orbitdb updated to the latest and when ready merged upstream ?
Another question, regarding when do you think this might be ready? I am somewhat on a schedule for the delivery of my thesis, hence it would be very much appreciated if there was any ETA on when we can expect this integrated upstream. No pressure sine I don't think that I will have time.
Thank you in advanced for this, I think it will be a huge step towards making OrbitDB more accesible and used with the upcoming of Helia.

Tbh I don't really like js-ipfs and Helia seems like a much better ipfs implementation.

I think a lot of us think this way.

I want to migrate the application I am writing for my degree thesis to Helia but since I use OrbitDB as an integral part of my application I am kind of waiting on this.

I made this changes to be backwards compatible so if the rest of your application works with both Helia and OrbitDB is should be trivial to change over. That being said I do not know if the owners would change this or not. What you could do in the meantime is wrap Helia in something that looks like js-ipfs (at least the small part of the API that actually gets used) and use it in place of it, if you really want to change over soon.

will this be a new separate orbitdb package for helia? or is this just a new fork to work on features to keep Orbitdb updated to the latest and when ready merged upstream ?

Last I talked to Haad it sounded as if it would get merged at some point but it was further down the priority list. I haven't been too worried about keeping it up to date until there is indication they are ready to merge it.

when do you think this might be ready?

I don't know myself but perhaps @haadcode could comment?

In orbit-db-nextgen adding events to a log is blazing fast at the beginning and starts to slow down rapidly, is this something that can be improved?

In the example above,
Events are strings "[:inc-counter]" (serialized EDN)
1k of these events been issued as eventdb.add("[:inc-counter]")
I turned on performance profiled (screenshot below) (that is when events stopped being processed for a couple of seconds in the gif above)

Have you run the same test on the current 'orbit-db' main to see if the performance has regressed? Just from reviewing the code, I know there are several instances where it reads and sort the entire log (in the current 'main' version). Your profile data makes it look like that might be part of the problem here.
Get Outlook for Androidhttps://aka.ms/AAb9ysg

From: Andrew Zhurov @.>
Sent: Friday, June 23, 2023 9:14:15 AM
To: orbitdb/orbit-db-nextgen @.>
Cc: justin0mcateer @.>; Comment @.>
Subject: Re: [orbitdb/orbit-db-nextgen] feat: Add support for Helia. (PR #62)
In orbit-db-nextgen adding events to a log is blazing fast at the beginning and starts to slow down rapidly, is this something that can be improved?
[record]https://user-images.githubusercontent.com/13056889/248290623-c326d99c-d51c-470b-9099-8d8ed022c532.gif
In the example above,
Events are strings "[:inc-counter]" (serialized EDN)
1k of these events been issued as eventdb.add("[:inc-counter]")
I turned on performance profiled (screenshot below) (that is when events stopped being processed for a couple of seconds in the gif above)
[image]https://user-images.githubusercontent.com/13056889/248290470-e549a4cb-c532-4589-b36c-b0b12bf54e99.png
—
Reply to this email directly, view it on GitHubhttps://github.com/orbitdb/orbit-db-nextgen/pull/62#issuecomment-1604345245, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AAT4Q7KMYOPG6WIBXETCDMDXMWQDPANCNFSM6AAAAAAWMTWYUY.
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Ran it on orbit-db v 0.29.0 (latest as of now)
It's not the exact same test though, configuration is slightly different

https://share.firefox.dev/3qY0JYI

And here's the run without GUI updates
https://github.com/orbitdb/orbit-db-nextgen/assets/13056889/ab01635f-f468-4ceb-94fd-8dd58cb6206b
https://share.firefox.dev/43MI2pr

I'm experiencing an interesting scenario, where two browser nodes A and B open the same database, node B adds a bunch of events to it, then they connect and exchange heads, node A receives only the head of that bunch of events, so only the last event made by node B gets propagated to it, the others do not. Is this intended? I'd expect all the events being propagated
record.mp4

You're correct, only the heads are replicated. To complete the replication process, you explicitly iterate over the recordset which will replicate all records. See https://github.com/orbitdb/orbit-db-nextgen/blob/main/docs/DATABASES.md#replicating-a-database-across-peers for an example.

Fetching entries ad-hoc, when needed, from the underlying IPFSBlockStore - damm, I love how elegant that is, thanks for the pointer!

Can it be that .iterator with lt or lte will not return entities that been added to log in parallel?
On example
AB1 <- A2 <- A3
  ^--- B2 <- B3

where AB1 is a commonly known entry by both peer A and peer B, and A2, A3, B2, B3 - novel entries, added by peers in parallel.
Then, when they sync up and try to iterate with lt or lte pointing to a novel entry (say A3), will iterator skip entries that's been added in parallel?
.iterator({lt: A3}) => [A2, AB1]
.iterator({lt: B3}) => [B2, AB1]

As it takes nexts from the supplied lt or lte and they don't contain entries that's been added in parallel (so A3 doesn't contain B2).
If so, is it intended?
Perhaps it is my out-of-design use-case where I'd like to get all entries lt than say A3, returning [A2, B2, AB1]
.iterator({lt: A3}) => [A2, B2, AB1]

This PR dropped the timeouts for IPFSBlockStorage.get() and IPFSBlockStorage.put().
These can be added with a simple call to 'AbortSignal.timeout' as shown below:
const block = ipfs.blockstore ? await ipfs.blockstore.get(cid, { signal: AbortSignal.timeout(timeout) }) : await ipfs.block.get(cid, { timeout })

Hey there,
Helia maintainer here, just checking in to see if there's anything you need from us in Helia that would make use of it easier.
Also, please feel free to open any issues regarding bugs/feature requests at github.com/ipfs/helia or discussions at https://discuss.ipfs.tech/c/help/helia/40

Are there any updates here?

By the sounds of things this fork has fallen to far behind and they are not prioritizing Helia. I think a new fork would need to be done.

Thanks everyone for following up on this. As the code from this repo has been merged to main orbitdb repo, this repo is indeed inactive. That however doesn't mean Helia is not a priority, rather it's been moved to helia branch in the main repo and it's actively been worked on.
Closing this PR but contributions are welcome in the main repo!


Unspecified requirement during installation

Hi there,
It seems scipy is not really an optional dependency. When I run a fresh install and tried to import dit. I got the following error:

import dit
Traceback (most recent call last):
File "", line 1, in
File "/home/hcwu/python_virtual/dit_test/lib/python2.7/site-packages/dit/init.py", line 29, in
from .algorithms import pruned_samplespace, expanded_samplespace
File "/home/hcwu/python_virtual/dit_test/lib/python2.7/site-packages/dit/algorithms/init.py", line 12, in
from .scipy_optimizers import *
File "/home/hcwu/python_virtual/dit_test/lib/python2.7/site-packages/dit/algorithms/scipy_optimizers.py", line 16, in
from scipy.optimize import basinhopping, minimize
ImportError: No module named scipy.optimize

made scipy a requirement.


Update did, did-imp, did-method-peer to 0.1.0-M5 in main

About this PR
📦 Updates

app.fmgp:did
app.fmgp:did-imp
app.fmgp:did-method-peer

from 0.1.0-M4 to 0.1.0-M5
📜 GitHub Release Notes - Version Diff
Usage
✅ Please merge!
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

⚙ Adjust future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "app.fmgp" } ]

Or, add this to slow down future updates of this dependency:
dependencyOverrides = [{
  pullRequests = { frequency = "30 days" },
  dependency = { groupId = "app.fmgp" }
}]

labels: library-update, early-semver-pre-release, semver-spec-pre-release, version-scheme:early-semver, commit-count:1

I already did this Steward


Love the obfuscation ...

Can MSFT ever keep up with their own products? Why does it take two years for a name change like AAD -> Entra ID to finally arrive in the documentation? Is it tail (devs) wagging the dog (docs)?
[Enter feedback here]

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

ID: be1e6c9a-9644-6d86-3962-d36bf1efd656
Version Independent ID: 96142d6c-71de-6ea9-0361-dbec82647b15
Content: Set up multifactor authentication for users - Microsoft 365 admin
Content Source: microsoft-365/admin/security-and-compliance/set-up-multi-factor-authentication.md
Service: microsoft-365-business
GitHub Login: @kwekuako
Microsoft Alias: kwekua

@Amondale Thank you for your feedback. We are extremely sorry about the delay in updating the docs. We will ensure such delays don't happen again in the future.
Hope this helps!
Thanks
Sri


Fixed typos in MeshDataTool documentation

Fixup of https://github.com/godotengine/godot/pull/56201
Supersedes and closes https://github.com/godotengine/godot/pull/56201

Cherry-picked for 3.5.

Cherry-picked for 3.4.3.


Get icon by filetype

The icons are classified by filename and/or extension. It would be nice to be able to get an icon by filetype.
Eg vim's help files have the help filetype, but their extension is still .txt.

i guess so, but a filetype is associated to a buffer, so you would need to load the buffer, assign it a file, then get the filetype. For a few files it would be ok, but for most use case it would be desatruously slow. Maybe providing a function geticonfromft would work

Yes that is exactly what I mean. I want to pass the filetype not the file.

well, you could add a PR i wouldn't be against it, but depending on your use case, wouldn't it be easier to just map filetypes to file extensions ? so you could only map those you would need (for instance, if your filetype is help, you can map to .vim, but otherwise it will load with the default extension)

I think icons should be classified by filetype, not by extensions. And there should be a map from file extension to filetype. The reason is that filetype is more primordial than extension, because different extensions can point to the same filetype (C++: cpp, cxx, cc). Entries in the current icon table are repeated rigth now and that's wasted memory. I''m also mentionning because I've been having trouble with the get_icon function sometimes, I've seen a few stack overflows. I'm not sure where the icons memory lives, I would have expected on the heap, but anyway it's good to reduce memory usage. It will also be easier to maintain.

i agree it would be better if it were classified by filetype.
Although i've never experienced stack overflows (and i believe lua, as a high level garbage collected language, stores everything in the heap ? I'm not sure about that tough). Is a 100 entry table really that big in memory ?
Is there a way to get the filetype from a filename in the neovim api ? I'm not aware of such function, although i've looked up documentation as well as i could :)
Also some filename would not match any filetypes i believe, so that could also potentially be another issue and we would still need to add an extension based table.

The filetype doesn't necessarily depend on the name. Sometimes plugins will set the filetype on buffers just to get the syntax highlighting. Passing the filetype as an extra param or having a different function to get the icon by filetype would solve that issue. Separate function would be cleaner I think.
About memory, I would have expected lua to be fine but I have a lot of lua running currently (treesitter and a few plugins) and when I have lots of buffers open I often see a Lua: can't grow stack past 4002... error messages when calling get_icon. Can't say who is at fault but anyway less repetition is better.

i believe your stack issue is related to vim <> lua code transfer. I can take a look to see if it happens on my machine with your barbar plugin, but i believe this is an issue for neovim.
Anyway make a Pr ill merge it :)

I'd like to second an api to find by filetype. It would simplify things greatly.

closed in #125


Chocolatey vscode.portable package is not updated since 1.53.2

Issue Type: Bug
Last approved Chocolatey package is 1.53.2. Two newer versions are "waiting for maintainer":
https://chocolatey.org/packages/vscode.portable#versionhistory
VS Code version: Code 1.53.2 (622cb03f7e070a9670c94bae1a45d78d7181fbd4, 2021-02-11T11:48:04.245Z)
OS version: Windows_NT x64 10.0.18363

System Info

Item
Value

CPUs
Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz (8 x 2808)

GPU Status
2d_canvas: enabledgpu_compositing: enabledmultiple_raster_threads: enabled_onoop_rasterization: enabledopengl: enabled_onprotected_video_decode: enabledrasterization: enabledskia_renderer: enabled_onvideo_decode: enabledvulkan: disabled_offwebgl: enabledwebgl2: enabled

Load (avg)
undefined

Memory (System)
15.89GB (9.98GB free)

Process Argv

Screen Reader
no

VM
50%

Extensions (7)

Extension
Author (truncated)
Version

gitlens
eam
11.2.1

python
ms-
2021.2.633441544

jupyter
ms-
2021.2.603412351

remote-wsl
ms-
0.53.4

cpptools
ms-
1.2.2

rust
rus
0.7.8

tabnine-vscode
Tab
3.2.8

As it says on that page:

Welcome to the Chocolatey Community Package Repository! The packages found in this section of the site are provided, maintained, and moderated by the community.

We do not publish this package.

Sorry, my bad. Seems to be resolved by now anyway.
čt 18. 3. 2021 v 20:14 odesílatel João Moreno @.***>
napsal:

As it says on that page:
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in this section of the site are provided, maintained, and moderated by the
community.
We do not publish this package.
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Not recognizing children sizes

Hello, thanks for your plugin, it seems that is not respecting the size of the component children, i have the Spruce component and his children is a button with height:20 and here is the result

any fix for this?

@prscX i found the issue in Spruce.js file in line 44 you must remove the inline style, right now it has flex:1
thanks


Update box-shadow Property

I was not happy with the box-shadow property of "ci-features-box" (on our home page) that appears when we hover and finally I've had time to change that. I believe those boxes will seem much better now when we hover on them.

Thanks team!


Improve matrix_assembly_data performance

We could make the performance of matrix_assembly_data much better by building a row-wise flat hash map ourselves. For that we only need an upper bound for the number of columns for each row (either individual or a global upper bound). The access could be implemented in a thread-safe fashion (atomicCAS on the column indices, atomicAdd on the values) or single-threaded fashion (non-atomic access to the column indices)
If we wanted to build an unbounded hash map, we could collect elements exceeding the size bounds in a global "overflow" hash map, but that would probably be harder to do in a thread-safe fashion.

I believe we might be talking about different concepts of matrix assembly here. The documentation you attached seems to be focused more on assembling the sparsity pattern (with the values being set once, no duplicates), while our concept is more about collecting values (with multiple values being added together). Once the sparsity pattern is assembled, we can use something like csr_lookup or a matrix representation of the sum_duplicates operation to implement the actual assembly.


bug: v9.0.0 does not support iOS

About this issue

Briefly describe the issue
I'm working on a KMM project. I can't run the iosApp if I use v9.0.0 of markdown-renderer, while v0.7.2 works fine. It seems because the iOS target was deleted accidentally when upgraded to compose 1.5.4

> Could not resolve com.mikepenz:multiplatform-markdown-renderer:0.9.0.
     Required by:
         project :shared
      > No matching variant of com.mikepenz:multiplatform-markdown-renderer:0.9.0 was found. The consumer was configured to find a library for use during 'kotlin-metadata', preferably optimized for non-jvm, as well as attribute 'org.jetbrains.kotlin.platform.type' with value 'native', attribute 'org.jetbrains.kotlin.native.target' with value 'ios_x64' but:
          - Variant 'iosSimulatorArm64ApiElements-published' capability com.mikepenz:multiplatform-markdown-renderer:0.9.0 declares a library for use during 'kotlin-api', as well as attribute 'org.jetbrains.kotlin.platform.type' with value 'native':
              - Incompatible because this component declares a component, as well as attribute 'org.jetbrains.kotlin.native.target' with value 'ios_simulator_arm64' and the consumer needed a component, as well as attribute 'org.jetbrains.kotlin.native.target' with value 'ios_x64'
              - Other compatible attribute:
                  - Doesn't say anything about its target Java environment (preferred optimized for non-jvm)

Details

[ 9.0.0 ] Used library version

The iOS target should come from the default hiararchy 🤔 :
https://github.com/mikepenz/multiplatform-markdown-renderer/commit/3f02042c32a3094fc2983000b018f4892707916a#diff-4d1366c1d930d53bf81d4ba1b86de7928596f427413946f76ddae7db25ca4de4R56
That said. you are right, they miss from maven central
https://repo1.maven.org/maven2/com/mikepenz/multiplatform-markdown-renderer-iosx64/
https://repo1.maven.org/maven2/com/mikepenz/multiplatform-markdown-renderer-iosarm64/
Will look into it


setNonBlockIfNeeded

Documentation of mkSocket advises that a call to setNonBlockIfNeeded might be neccessary on some systems and that is it not harmful on systems where it is not.
I have observed usecases that were previously broken because of this (specifically all semi-recent versions of Warp).

Thanks for the PR

Uploaded on hackage https://hackage.haskell.org/package/systemd


Atom

Click on Messenger tab in menubar reveals "About Atom" and "Quit Atom" buttons. Should replace this with "Messenger."

fixed in v0.2.1


optimize commit hook : unit test

make commit hook to selective test.  the selection base on below logic

[x] changed files' package default behavior
[x] configurable, this behavior can be changed by flags

Fix in as part of #52


Syntax highlight system restrained

Hi, I would like to share my thoughts about Micro's syntax highlight system.
I think it is too much restrictive.
For example here is a Nano configuration file to express it:
## Syntax highlighting for Python.

syntax python "\.py$"
header "^#!.*python"
magic "Python script"
comment "#"

# Alternative linter: pylint --exit-zero
linter pyflakes

# Function definitions.
color brightblue "def [0-9A-Za-z_]+"
# Keywords.
color brightcyan "\<(and|as|assert|async|await|break|class|continue)\>"
color brightcyan "\<(def|del|elif|else|except|finally|for|from)\>"
color brightcyan "\<(global|if|import|in|is|lambda|nonlocal|not|or)\>"
color brightcyan "\<(pass|raise|return|try|while|with|yield)\>"
...

With this approach we have an unlimited(?) way to express ourself.
Another alternative without changing all the system could be to have way more rules like this configuration.
But currently Micro has too few rules and no way to bypass them.
Micro lover here ❤ who wish to enjoy it even more.

I think it is too much restrictive.

Why?

But currently Micro has too few rules and no way to bypass them.

Too few? For python alone we've already two different rule sets:

python2.yaml
python3.yaml

Every user can override the default rules by using his own per language/extension syntax configuration YAML and place it under e.g.: ~/.config/micro/syntax/python.yaml (documented here: README.md#micro-syntax-highlighting-files)
So from my perspective that's an easy way to play around and maybe improve the rules currently provided.
If you've already concrete ideas to improve the actual python handling then please feel free to change the rules accordingly, test them and suggest them here, because we need the support from the user interested in improving micro.


feat: Import account modal with wallet-selector [WEP-217]

Description
This PR contains initial implementation of setupImportModal, to be used for migrating near accounts to listed wallet.
Currently only MNW and Near Wallet will show following steps. (Full migration won't work yet, still requires some work need to be done on wallets to be able to fully import accounts)
Example React page:

Import Modal UI:

Future roadmap after this PR:

Create PR for encryption/decryption.
Reach out to third party wallet teams to make import readily available on their end. (Should initiate this step when UI is fully ready on wallet-selector side)
Create a dedicated readme.md/doc for showing how to use setupImportModal

Checklist:

[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have made corresponding changes to the documentation
[x] My changes generate no new warnings

Type of change.

[ ] FIX - a PR of this type patches a bug.
[x] FEATURE - a PR of this type introduces a new feature.
[ ] BUILD - a PR of this type introduces build changes.
[ ] CI - a PR of this type introduces CI changes.
[ ] DOCS - a PR of this type introduces DOCS improvement.
[ ] STYLE - a PR of this type introduces style changes.
[ ] REFACTOR - a PR of this type introduces refactoring.
[ ] PERFORMANCE - a PR of this type introduces performance changes.
[ ] TEST - a PR of this type adds more tests.
[ ] CHORE - a PR introduces other changes than the specified above.

General comments:

My apologies for making this big PR, initially I wanted to keep them small but also, I wanted to make the PR so a presentable and playable state. With accomodating latest design changes, it ended up this big.
Implementations are kept inside modal-ui project because I wanted to reuse existing themes/styles/components/conventions but also keep up with custom designs that are different to existing modal-ui look.
I wanted to make sure this is testable/playable on example react without making major changes on existing implementation, so I ended up making slight modification (switch button) but please let me know this is not ideal and/or if there is any better approach to do.

Closing this PR as we decided to shift implementation logic to a seperate project instead of modal-ui


[demo] Automate doctr demo update via CI job

This PR:

Add required files to auto update the hf demo via CI
Add corresponding CI job - allow also manual action trigger for testing or manual refresh

Any feedback is welcome :hugs:
@odulcy-mindee HF_TOKEN needs to be added as secret :)
To much overhead with the cron job ? :sweat_smile:

I added the token. Hopefully, it should have enough rights to update the space. Thank you for automating that.

Let's see that it works as expected i did the same for OnnxTR so hopefuly fine (https://github.com/felixdittrich92/OnnxTR/commit/497ae2db7690ce1a310d93b916da7cf3d0e963c1)


Add note about ffdhe2048

Optional to merge.
Only to clarify things.

In my opinion, mentioning ffdhe2048 like we currently do should be enough for anyone willing to use a search engine.
Of course further explanations could be added if concerned people become a recurring issue, but let's see.


Automation to simplify Parent and Child relationship

Problem description
Currently, we need to manually assign all the permissions to child block as permissions of Parent block. We need to automate this process in order to avoid errors and simplify the Policy creation process.
Requirements
We need to automate the process of assigning the same permissions to the Child Block as the Parent Block. In addition to permissions, all the other parameters needs to be assigned in the same way as mentioned above.
Definition of done
Automating process of assigning permissions and other parameters to the child block as parent block.
Acceptance criteria
Automation as above mentioned process.

Maybe we need to improve "Undo"/"Redo" buttons behaviour in the future. At the moment there could be freezes, when undo/redo action applies to a lot of fields (in case of assigning permissions to all children of parent block)


OMP: Error #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized.

For bugs or installation issues, please provide the following information.
The more information you provide, the more easily we will be able to offer
help and advice.
Environment info
Operating System: Mac OSX Sierra 10.12.1
Compiler:
Package used (python):
xgboost version used: xgboost 0.6a2
If you are using python package, please provide

The python version and distribution:
Pythong 2.7.12
The command to install xgboost if you are not installing from source
pip install xgboost

Steps to reproduce

from xgboost import XGBClassifier
import numpy as np
import matplotlib.pyplot as plt
x = np.array([[1,2],[3,4]])
y = np.array([0,1])
clf = XGBClassifier(base_score = 0.005)
clf.fit(x,y)
plt.hist(clf.feature_importances_)

What have you tried?
See the error message:
"OMP: Error #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized.
OMP: Hint: This means that multiple copies of the OpenMP runtime have been linked into the program. That is dangerous, since it can degrade performance or cause incorrect results. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, e.g. by avoiding static linking of the OpenMP runtime in any library. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results. For more information, please see http://www.intel.com/software/products/support/."
I tried:
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'
It can do the job for me. But it is kind of ugly.

I know it might be not the problem of xgboost, but I'm pretty sure this problem happened after I upgrade xgboost using 'pip install xgboost'.    I post the issue here to see if someone had the same problem as me.  I have very little knowledge about OpenMP.  Please help!
Thanks in advance!

I'm having the same issue when I try to use both xgboost and matplotlib.
OS X 10.10.5
Python 2.7.12
xgboost 0.6
matplotlib 1.5.1

I've encountered the same problem with xgboost and matplotlib.  Same symptom...kernel dies with the same error message as reported by @symPhysics
Mac OS X 10.12.3
Python 3.5.2 |Anaconda custom (x86_64)| (default, Jul  2 2016, 17:52:12)
[GCC 4.2.1 Compatible Apple LLVM 4.2 (clang-425.0.28)] on darwin
xgboost 0.6a2
matplotlib 2.0.0

FWIW...this seems to be a MacOS specific problem.  I was not able to recreate the problem on a CentOS Linux VM.

At least for Mac,
brew uninstall libiomp clang-omp
as long as u got gcc v5 from brew it come with openmp
follow steps in:
https://github.com/dmlc/xgboost/tree/master/python-package

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

For me the issue (on a Mac) was fixed with
pip uninstall xgboost
followed by
pip install xgboost

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

thanks, it works!!!

I had the same error on my Mac with a python program using numpy, keras, and matplotlib.  I solved it with 'conda install nomkl'.

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

thanks a lot, it works.

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

Thanks too, it works for me too.

@gpetty  You sir are a true hero. Thank you!

@gpetty It works! THANKSSS :))

Strangely conda install nomkl didn't work for me (don't have libiomp clang-omp installed on Brew either), only
os.environ['KMP_DUPLICATE_LIB_OK']='True'

could work

brew uninstall libiomp clang-omp

Error: No such keg: /usr/local/Cellar/libiomp

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

thanks a lot, even though i dont know what is nomkl. It confused me a few days when i run a CNN-RNN model using tensorflow.When i used os.environ['KMP_DUPLICATE_LIB_OK']='True' , it worked, but the program run so slow.You got the right ans.

My issues were completely unrelated to xgboost, but I got here via google so that I'd share for the sake of others.
I am using keras and matplotlib installed via conda. Setting KMP_DUPLICATE_LIB_OK just changed my experience from a warning to an exception/crash.  Install nomkl didn't change anything for me. Eventually I downgraded my version of matplotlib and that fixed things for me
conda install matplotlib=2.2.3

For people googling this error, the best solution that I found is listed here.
The site lists two method. I prefer method 1, which is to go into your anaconda3/lib directory and remove the old libiomp5.dylib file. Nice and simple.

For people googling this error, the best solution that I found is listed here.
The site lists two method. I prefer method 1, which is to go into your anaconda3/lib directory and remove the old libiomp5.dylib file. Nice and simple.

Please be really careful if you want to try method 1. Everything crashed after I deleted the file and I have to reinstall openmp. Same problem reported in the original csdn link (in Chinese).

Thanks!!
For me on MAC:
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

Had the same problem after switching from homebrew/virtualenv installed numpy/keras/matplotlib/tensorflow to miniconda installed. Solved by running conda install nomkl though I reckon keras (and numpy) wont run as fast as they could if they don't make use of Intel's Math Kernel Lib but at least my code still run so ¯_(ツ)_/¯

conda install nomkl worked for me.
Can anyone explain what this does and why it fixes the problem?

@georgeu2000, I'm wondering about the same. It did also fix the problem for me. I'm using Numpy, Matplotlib, Keras and Tensorflow as backend. I don't seem to understand what that package does. Anyone could explain?
Thanks a lot.

I saw some benchmarks between openblas and mkl before, mkl is not superior.  Is there any reason for using mkl over openblas?  Explaining something without the source code at hand is not very motivating.

conda install nomkl
works but it has to downgrade:

  mkl_fft                             1.0.10-py36h5e564d8_0 --> 1.0.1-py36h917ab60_0
  mkl_random                           1.0.2-py36h27c97d8_0 --> 1.0.1-py36h78cc56f_0
  numexpr                              2.6.9-py36h7413580_0 --> 2.6.9-py36hafae301_0
  numpy                               1.15.4-py36hacdab7b_0 --> 1.15.4-py36h926163e_0
  numpy-base                          1.15.4-py36h6575580_0 --> 1.15.4-py36ha711998_0
  scikit-learn                        0.20.2-py36h27c97d8_0 --> 0.20.2-py36hebd9d1a_0
  scipy                                1.2.1-py36h1410ff5_0 --> 1.2.1-py36h1a1e112_0

My issues were completely unrelated to xgboost, but I got here via google so that I'd share for the sake of others.
I am using keras and matplotlib installed via conda. Setting KMP_DUPLICATE_LIB_OK just changed my experience from a warning to an exception/crash. Install nomkl didn't change anything for me.  Solved by running conda install nomkl though I reckon keras (and numpy) wont run as fast as they could if they don't make use of Intel's Math Kernel Lib but at least my code still run so ¯_(ツ)_/¯

^^^^   This is what did the trick for me. Thanks!

Thanks!!
For me on MAC:
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

WORKS FOR ME THANKS

In my conda lib, I have multiple libgomp:
I got the expected error:
OMP: Error #15: Initializing libiomp5.dylib, but found libomp.dylib already initialized.
OMP: Hint This means that multiple copies of the OpenMP runtime have been linked into the program. That is dangerous, since it can degrade performance or cause incorrect results. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, e.g. by avoiding static linking of the OpenMP runtime in any library. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results. For more information, please see http://www.intel.com/software/products/support/.

This definitely helps:
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

Here are all of my versions:
(µ_env) jespinozlt-osx:lib jespinoz$ ls -lhtr | grep "omp"
-rwxr-xr-x    1 jespinoz  tigr    62K Oct 28  2016 libgomp.1.dylib
-rwxr-xr-x    1 jespinoz  tigr   110K Aug 11  2017 libiompstubs5.dylib
-rwxr-xr-x    1 jespinoz  tigr   1.3M Aug 11  2017 libiomp5.dylib
lrwxr-xr-x    1 jespinoz  tigr    15B Feb 23  2018 libgomp.dylib -> libgomp.1.dylib

Should I just remove one of them? If so, should I keep libiomp5.dylib instead of libgomp.1.dylib and just symlink?

OMP: Error #15: Initializing libiomp5.dylib, but found libiomp5.dylib already initialized.
OMP: Hint: This means that multiple copies of the OpenMP runtime have been linked into the program. That is dangerous, since it can degrade performance or cause incorrect results. The best thing to do is to ensure that only a single OpenMP runtime is linked into the process, e.g. by avoiding static linking of the OpenMP runtime in any library. As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results. For more information, please see http://www.intel.com/software/products/support/.

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

Does fix the problem. Thanks

I ran into this problem on a fresh install of anaconda on an a brand new Mac book pro in Anaconda trying to use tensor-flow and keras. I used. 'conda update --all' and it fixed the problem.

brew uninstall libiomp clang-omp

Error: No such keg: /usr/local/Cellar/libiomp

i have the same error how did you solve it , and conda insatll nomkl is not working either
its giving the error
UnavailableInvalidChannel: The channel is not accessible or is invalid.
channel name: torch
channel url: https://conda.anaconda.org/torch
error code: 404
You will need to adjust your conda configuration to proceed.
Use conda config --show channels to view your configuration's current state,
and use conda config --show-sources to view config file locations.

I ran into the same problem and I used keras, numpy and tf 1.14.
conda install nomkl dose solve my problem! Thank you.

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

I ran into the same problem and I use keras, numpy and tensorflow 1.14.
conda install nomkl does solve my problem! Thank you @gpetty

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with
'conda install nomkl'.

This worked for me as well. I was getting error while running LightGBM package, it was erroring out after a certain number of rows or certain number of features.
I'm guessing it has something to do with memory usage or parallelising process. it would be great if someone can explain what exactly 'libomp' does and why 'nomkl' solves it. Thanks.

Strangely conda install nomkl didn't work for me (don't have libiomp clang-omp installed on Brew either), only
os.environ['KMP_DUPLICATE_LIB_OK']='True'

could work

Hello
Same for me but
conda install -c anaconda nomkl
worked for me
Hope it helps

Hey all,
although using os.environ['KMP_DUPLICATE_LIB_OK']='True' is absolutely frowned upon, but eventually, I had to use it cause conda install -c anaconda nomkl didn't work for me. Any other ideas?

use the os.environ['KMP_DUPLICATE_LIB_OK']='True' works but was not recommended. use Conda install nomkl looks running endless, has to kill it. use conda update -n base Conda works and it updated the lib

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

Thank you very much! It works for me!

import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'
it  works for me,thank you .

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

Thanks Bro！ It worked for me!

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

Thanks Bro！ It worked for me!

I just test tensorflow object_detection API  and run the object_detection_tutorial.ipynb file

i'm on a 2010 MBP, running the python(3.7) file on anaconda; so I guess it was something to do with my 'old' system - i have no clue on what territories i'm treading here - tried uninstalling xgboost, realised it's not installed, tried installing it, it just got stuck;  tried conda install nomkl, and then my python script itself wouldn't run (illegal instruction: 4); uninstalled nomkl; finally worked when i used
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

i still don't know how and why it worked, but hey, it works now

We can close this issue now.

LMAO

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

it works for me thx

For me, this combination worked:
brew uninstall libiomp clamp-omp
conda uninstall intel-openmp -n base
conda install -c intel openmp -n myenv
conda install nomkl -n myenv

The primary conflict came from the brew libiomp but then later conflicts with the conda base env and my python 3.7 env over openmp sent me in circles until i sorted out the dependency chain/fallback. The channel source distinction made a huge difference.

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

It works for me too

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

Thanks! It works for me as of today! Can anyone explain why this works?

We now provide a binary wheel for Mac OSX, which links to /usr/local/lib/libomp.dylib. Install XGBoost by running
python -m pip install xgboost

Thank you this solved my case. My Mac did not have libiomp and clamp-omp, and I did not install nomkl.
So I only do these two steps.
conda uninstall intel-openmp
conda install -c intel openmp

For me, this combination worked:
brew uninstall libiomp clamp-omp
conda uninstall intel-openmp -n base
conda install -c intel openmp -n myenv
conda install nomkl -n myenv

The primary conflict came from the brew libiomp but then later conflicts with the conda base env and my python 3.7 env over openmp sent me in circles until i sorted out the dependency chain/fallback. The channel source distinction made a huge difference.

(macOS Catalina 10.15.5)
Going through the installed package in my env, I noticed that there was an update for mkl.
So I was able to solve my case by updating mkl.
conda install -c intel mkl

you can do ``conda install nomkl`

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

What is the magic behind this?

I had the same error on my window10.

os.environ['KMP_DUPLICATE_LIB_OK']='True', I tried this command and the problem solve thanks to @Toooodd

I found an alternative solution to this problem here, which is to preload the OpenMP runtime using the LD_PRELOAD variable:
LD_PRELOAD=<path_to_libiomp5.so> <path_to your_executable>

This eliminates multiple loadings of libiomp, and makes all the components use this specific version of OpenMP.

import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'
Followed by

conda install nomkl

Worked for me. Thanks!

(macOS Catalina 10.15.5)
Going through the installed package in my env, I noticed that there was an update for mkl.
So I was able to solve my case by updating mkl.
conda install -c intel mkl

This works for me (macOS Big Sur)

For people googling this error, the best solution that I found is listed here.
The site lists two method. I prefer method 1, which is to go into your anaconda3/lib directory and remove the old libiomp5.dylib file. Nice and simple.

For me, it works! But the file I removed is a little different from yours which is libiomp5md.dll in the path  of C:\Users\***\Anaconda3\Library\bin. I think it may caused by installing full package of pytorch by me after installing anaconda. So the better way is to use miniconda or install pytorch by conda install torch torchvision torchaudio

I had the same error on my Mac with a python program using numpy, keras, and matplotlib. I solved it with 'conda install nomkl'.

Legend!

On Mac M1, conda install nomkl works.
But if it doesn't work for the first time, you should uninstall and install that command again.

This works for me. Thanks!.

On Mac M1, conda install nomkl works. But if it doesn't work for the first time, you should uninstall and install that command again.
Above didn't fix my issue after update mac os version ❌
these 2 works:
conda uninstall intel-openmp
conda install -c intel openmp

This works for my intel-Mac too!. Thanks alot!

Uninstalling and Reinstalling intel-openmp within the Conda Env solved the issue on my Intel Based MacBook

Thanks

WissenY

it works, thank u

Umm, because the conda install nomkl doesn't work on M1 for me, is the correct full process on M1:
'conda uninstall intel-openmp
conda install -c intel openmp
conda install nomkl'
?
Actually I ran all those 3 and now nothing works. :) I'm actually trying to run AutoGPT on M1, when all the original libiomp5.dylib problem came up.

On Mac M1, conda install nomkl works. But if it doesn't work for the first time, you should uninstall and install that command again.
Above didn't fix my issue after update mac os version ❌
these 2 works:
conda uninstall intel-openmp
conda install -c intel openmp

This works for my intel-Mac!. Thanks alot!

My solution is
conda uninstall intel-openmp
conda install nomkl

It seems to work well!
Due to package conflicts, I did not do conda install -c intel openmp.  My mbp is intel-mac with os 13.3.1.

I met the same error(not with xgboost though), and I fix it by change
import numpy
import torch

to
import torch
import numpy

it seems that import numpy later would solve this problem. But I don't understand why this bug would be fixed in this way .

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

it doesnt seem to help for macOS

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

It work. Thank You.

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

[MacOS]
This was program termination due to segmentation fault.
Through conda I reinstalled pytorch and then also reinstalled torchvision this fixed the issue for me.

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

[MacOS] This was program termination due to segmentation fault. Through conda I reinstalled pytorch and then also reinstalled torchvision this fixed the issue for me.

This worked for me!

Have people got problems with this solution?

I tried this and the error stopped !
import os
os.environ['KMP_DUPLICATE_LIB_OK']='True'

It is quite explicitly not recommended
From the original post:
"As an unsafe, unsupported, undocumented workaround you can set the environment variable KMP_DUPLICATE_LIB_OK=TRUE to allow the program to continue to execute, but that may cause crashes or silently produce incorrect results."


Global permissions are higher in priority

I have a permission 'worldguard. * true' in global when I take away this permission on the Auth server, it doesn't take

How are you taking it away?

/lp group default permission set worldguard. * false auth

Cannot reproduce. Seems to be working as intended.
> lp verbose on minecraft.command.ban
[13:10:45 INFO]: [LP] Verbose logging enabled for checks matching minecraft.command.ban.
[13:10:53 INFO]: UUID of player Luck is c1d60c50-70b5-4722-8057-87767557e50d
[13:10:53 INFO]: Luck[/<IP_ADDRESS>:62746] logged in with entity id 120 at ([world]92.7284247907261, 81.0,<PHONE_NUMBER>8496753)
[13:10:58 INFO]: Luck issued server command: /ban
[13:10:58 INFO]: [LP] VB > [C] luck - minecraft.command.ban - undefined
> lp user Luck p set minecraft.command.* true
[13:11:13 INFO]: [LP] Set minecraft.command.* to true for luck in context global.
[13:11:16 INFO]: Luck issued server command: /ban
[13:11:16 INFO]: [LP] VB > [C] luck - minecraft.command.ban - true
[13:11:16 INFO]: [LP] VB > [C] luck - minecraft.command.ban - true
> lp user Luck p set minecraft.command.* false survival
[13:11:26 INFO]: [LP] Set minecraft.command.* to false for luck in context server=survival.
[13:11:29 INFO]: Luck issued server command: /ban
[13:11:29 INFO]: [LP] VB > [C] luck - minecraft.command.ban - false

in config
server: auth
include-global: true

same.
# The name of the server, used for server specific permissions. Set to 'global' to disable.
server: survival

# If users on this server should have their global permissions applied.
# If set to false, only server specific permissions will apply for users on this server
include-global: true

You're either mistaken, or there's another issue with your setup somewhere.
Remember that non-wildcard permissions will still override the false wildcard.


installation instuctions outdated

I stumbled upon this repo while trying to get lufa working on a leonardo board and decided to give it a shot.
with the 1.6.12 version of arduino studio, the files mentioned in the installation section changed:
HID.cpp doesn't exist anymore
the line numbers in Arduino.h and main.cpp are off
the lines meant for main.cpp are already there
Platform.h doesn't exist anymore
I'm not sure what route I'll go from here to get lufa working, if it is relevant to this repo, there will be a pull request, if you or anyone else knows how to do it now before that that'd be even better.

the main idea is to disable USB specific code in the core, to avoid LUFA and Arduino USB stuff messing each others.
just look around the source files, and comment out according lines, you're good to go.

If some stumbles upon this:
I got it working in 1.8.2.
As @Palatis said, you simply have to remove everything that is related to USB from the files in the core directory.

Delete all files from 4. to 9. (HID.cpp won't exist, so you don't have to delete it)
The 'changes' in 11. mean, that you have to delete those lines. The numbers are off, but you can find the lines by searching for "USB".
Paltform.h does not exist anymore, so you don't have to change anything there

Additional steps, i did to get it working:

I deleted the files "PluggableUSB.cpp" and "PluggableUSB.h"
Sketchbook/libraries/LUFA/LUFA.h includes  Platform.h which doesn't exist, so the include has to be removed
you will need to add an include of <Arduino.h> to Sketchbook/libraries/LUFA/LUFA.h or some scripts will complain that they can't find the "delay"-funcion

For clarification, Lufa.h should look like this when you are done:
#define F_USB F_CPU
#include <Arduino.h>
#include <LUFA/Drivers/USB/USB.h>
#endif

That's all to get it working. The example is outdated as well, but the only change you have to do is:
in Descriptors.c, replace all VERSION_BCD(01.10) with VERSION_BCD(1,1,0)  and VERSION_BCD(00.01)with VERSION_BCD(0,0,1)
After this, i successfully uploaded the example to my Arduino Micro 👍

Thanks for the details, @Dakor91, I shifted onto other stuff and didn't really visit this repo for a long time.
However I might come back to this one since I recently have another (paid) project involving a small USB device.
Happy Arduinoing! 👍

btw, I do accept PR :-D

I currently don't have much time, so I didn't want to create one. But I found a few spare minutes (procrastination at its best) 😀
https://github.com/Palatis/Arduino-Lufa/pull/2


Remove Referrer (and associated) table

Questions
Answers

Description?
Removed Referrer (and associated) table

Type?
improvement

BC breaks?
no

Deprecations?
no

Fixed ticket?
Relative to PrestaShop/PrestaShop#27064

How to test?
N/A

Possible impacts?
Upgrade to 8.0

Thank you @Progi1984


Support expiry duration in days

    With the current implementation, we yet don't support `d` (e.g. `30d` ).

Originally posted by @shizhMSFT in https://github.com/notaryproject/notation/pull/417#discussion_r1009073464
notation sign command supports an optional expiry flag for user to specify a "best by use" time for the artifact. The duration can be specified in minutes(m) or/and hours(h). The intention of this issue is to support duration in days, for example, 30d, 1d3h20m.

Tracking it in https://github.com/notaryproject/notation/issues/129


Moar opCodes

Goal is to add the other opcodes, or a portion, with tests.
What's new

Increased test coverage
Added jumpTrue, jumpFalse
Added eq, gt
Added add, mult, mod
Added and, or, not
Added set, push, pop
Added rmem, wmem, call, ret
Added in
Created a program struct to track index, memory, and handle getting values

Codecov Report

:exclamation: No coverage uploaded for pull request base (master@519bcee). Click here to learn what that means.
The diff coverage is n/a.

@@            Coverage Diff            @@
##             master       #2   +/-   ##
=========================================
  Coverage          ?   69.09%
=========================================
  Files             ?        2
  Lines             ?       55
  Branches          ?        0
=========================================
  Hits              ?       38
  Misses            ?       15
  Partials          ?        2

Continue to review full report at Codecov.

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Not sure best way to test the getChars() implementation, leaving unautomated for now.


Transmit playlist audio

Maybe I am just too stupid (again), but it seems that when I add the Stream View browser source to OBS, music that is played is not transmitted, at least I see no audio level for this in OBS.
Is this intentional? And if so, could this be added as an optional function?

Stream View doesn't do anything special with music/audio. After logging in, you may need to Interact with the browser source and click the canvas once to activate audio - this is a browser limitation, same thing is required for your players.


Updating categories allows the id to be changed

The code should be updated to follow the following steps:

Try to pull the item from the database
If the item does not exist do nothing or create a new item (this can be decided during the work)
Update only the updatable properties
save the item

Don't forget to update/add tests accordingly

Is this issue still up for grabs?

yup!
If you have any questions about the code or getting things setup, just ask


IMN-792 Add events service v2 in agreement-platformstate-writer

[To be merged after #967]
This pull request is for implementing the v2 consumer service in agreement-platformstate-writer.

We should be able to cover all of them by setting the INACTIVE state.
In theory in this case other descriptor details (eg audience) should be left blank. Is it feasible in your opinion?

I think the easiest solution is ignoring the updates on the descriptor fields if catalog entry is undefined. I am not sure if this covers all the cases.


add code to ops

:tada: This PR is included in version 3.3.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:


mention ownership in access document

for @ehsalazar

Hi Ernie, I just found these issues--it looks like Ashley made a quick note here. If you remember what this was, let me know!


Support OpenLayers ES2015 modules ?

With the latest release, OL is now available through ES6 modules.
https://github.com/openlayers/openlayers/releases/tag/v4.0.0
https://www.npmjs.com/package/ol/
Is there any plan to support this ?
This would prevent bundler user from including OL globally to use AOD.

Awesome :+1:. We should provide support to ES2015, definitely. I'd wait till the official release is out, tho.


Update zone api

/zones is deprecated and updated with v3/zones. There are also some changes with the pagination model. Api now returns cursorinfo instead of resultinfo. Follow below link for more details on the change
https://docs.ultradns.neustar/Content/REST API/Content/REST API/Zone API/Zone API.htm

/approve


Gave Peter a Nose Job

Gave Peter a Nose Job
Description
Resized icon's dimensions to be a square because the previous icon was stretched.
Video of changes
Screenshots
Before

After

Steps to verify/test this change:

Start the development environment and verify that the favicon is changed.

Todos:

None

Fantastic work Patrick!


Attributes for "realizing" and "realized" are missing for capellacommon:State

In Capella a state can be realized by another state (of a higher level). We are missing ability to check that realization attribute  in the current API.

This is how Capella meta-model looks like around states:


[BUG] webdriver issue

tried running the script and got hit with this
Traceback (most recent call last):
File "C:\Users\JIJAT\Downloads\Microsoft-Rewards-Farmer-master\Microsoft-Rewards-Farmer-master\ms_rewards_farmer.py", line 773, in
login(browser, account['username'], account['password'])
File "C:\Users\JIJAT\Downloads\Microsoft-Rewards-Farmer-master\Microsoft-Rewards-Farmer-master\ms_rewards_farmer.py", line 46, in login
browser.find_element_by_name("loginfmt").send_keys(email)
AttributeError: 'WebDriver' object has no attribute 'find_element_by_name'

Hey, i'm not an expert, but it looks like you're running some older version of the script. You can try downloading the script by click the green button that says "Code" and "Download ZIP", here. If that doesn't work, you can also try forks of this repository especially because this one is no longer updated regularly. I personally also have my own version that I created, which relies on some of this code base but overall, a bit different, not sure if it will work for you.

tried running the script and got hit with this
Traceback (most recent call last): File "C:\Users\JIJAT\Downloads\Microsoft-Rewards-Farmer-master\Microsoft-Rewards-Farmer-master\ms_rewards_farmer.py", line 773, in login(browser, account['username'], account['password']) File "C:\Users\JIJAT\Downloads\Microsoft-Rewards-Farmer-master\Microsoft-Rewards-Farmer-master\ms_rewards_farmer.py", line 46, in login browser.find_element_by_name("loginfmt").send_keys(email) AttributeError: 'WebDriver' object has no attribute 'find_element_by_name'

Make sure you have manually logged into your bing rewards account and clicked join microsoft rewards to show you the "Microsoft Bing Dashboard".
If that doesnt work, comment out the following lines of code around line 31 and 32 to disable headless mode and watch the script work.
if headless_mode : #comment out to disable headless mode (makes window visable)
options.add_argument("--headless")
If THAT doesnt work uninstall everything and reinstall using this README.
How to Install:
-Install zip from GitHub: https://github.com/charlesbel/Microsoft-Rewards-Farmer
-Install Python https://www.python.org/downloads/
Select custom installation, change nothing hit yes until installed.
-Open Microsoft-Rewards-Farmer-master, move requirements.txt to C:\Users\Alex
Open command prompt. win + R>CMD, then type (without quotes): 'pip install -r requirements.txt' 	Press enter
Intall Google Chrome.
Install ChromeDriver from https://chromedriver.chromium.org/downloads
Place the file in X:\Windows (X as your Windows disk letter)
Edit the accounts.json.sample with your accounts credentials and rename it by removing .sample at the end
If you want to add more than one account, the syntax is the following :
[
{
"username": "Your Email",
"password": "Your Password"
},
{
"username": "Your Email",
"password": "Your Password"
}
]
How to Fix Mobile:
Comment out around line 134-138 with double quotes above and below
""
# Refresh page
browser.get('https://bing.com/')
# Wait 5 seconds
time.sleep(10)
#Update Counter
""
How to run Script:
Run the script by double clicking on ms_rewards_farmer.py


Cargo build reports functions annotated with #[cfg(OS)] as unused, even when they are used

Problem

When using the annotation #[cfg(OS)] on a module or function, that function/functions (and consts too) inside that module always get marked as unused, even if they are used.
Steps

Create a function annotated with e.g #[cfg(windows)]
Make sure that function is called somewhere
Observer that cargo build will tell you about the function being unused, even if it's not

Possible Solution(s)

Notes
Example code:
fn empty() -> FILETIME {
    FILETIME {
        dwLowDateTime: 0,
        dwHighDateTime: 0,
    }
}

fn filetime_to_u64(f: FILETIME) -> u64 {
    (f.dwHighDateTime as u64) << 32 | (f.dwLowDateTime as u64)
}

fn get_system_times() -> io::Result<(u64, u64)> {
    let mut idle_ticks = empty();
    let mut user_ticks = empty();
    let mut kernel_ticks = empty();

    if unsafe { GetSystemTimes(&mut idle_ticks, &mut kernel_ticks, &mut user_ticks) } == 0 {
        return Err(io::Error::new(io::ErrorKind::Other, "GetSystemTimes() failed"));
    }

    let idle_ticks = filetime_to_u64(idle_ticks);
    let total_ticks = filetime_to_u64(kernel_ticks) + filetime_to_u64(user_ticks);

    Ok((idle_ticks, total_ticks))
}

The functions filetime_to_u64 and empty get marked as unused. This entire module is marked as:
#[cfg(windows)]
mod windows;

Cargo output:
warning: constant is never used: `WINDOWS_SAMPLE_TIME_MILIS`
 --> src\metrics\cpu\windows.rs:6:1
  |
6 | const WINDOWS_SAMPLE_TIME_MILIS: u64 = 500;
  | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  |
  = note: `#[warn(dead_code)]` on by default

warning: function is never used: `empty`
 --> src\metrics\cpu\windows.rs:8:4
  |
8 | fn empty() -> FILETIME {
  |    ^^^^^

warning: function is never used: `filetime_to_u64`
  --> src\metrics\cpu\windows.rs:15:4
   |
15 | fn filetime_to_u64(f: FILETIME) -> u64 {
   |    ^^^^^^^^^^^^^^^

cargo build is ran here on Windows. But the same applies to compiling on Linux when it is annotated with #[cfg(unix)]
Output of cargo version: cargo 1.50.0 (f04e7fab7 2021-02-04)

OS: Windows 10 64 bit 20H2
Arch: x86_64
Target Toolchain:
Ive tried it on the following toolchains:

stable-x86_64-pc-windows-msvc
stable-x86_64-pc-windows-gnu
stable-x86_64-unknown-linux-gnu

Compiling on Windows or Linux makes no difference.

Err, when you dont call the function that is using the functions (here get_system_times), the functions that that function calls (get_system_times here) get marked as unused too.
When I do call the 'parent' function (get_system_times) the warns go away :)


Upgraded from 6.4.5 to 6.4.14
Expected Behavior
EXPLAIN WHAT IS TO BE EXPECTED, HERE.
Since the update, I get a
Uncaught DOMException: Failed to execute 'remove' on 'DOMTokenList': The token provided must not be empty.
Actual Behavior
Should not throw error

Would be great to see minimal live demo with the issue

My application is HUGE. I just updated from 6.4.5 to 6.4.15 and this issue did appear. I have multiple sliders on my page, I will try to isolate the issue.

@nolimits4web Reverting to 6.4.5 fixed the issue for me so far. I have very limited time to isolate the issue right now, I guess a DOM7 commit had a regression

@nolimits4web I did a downgrade from 6.4.14 back to 6.4.5 and the issue is gone. Since the error is happening in DOM7, I guess some changes there introduced the regression

There were no any changes to Dom7 since then. Still need to see live example (Fiddle/CodeSandbox/...) to see know where it comes frmo

@nolimits4web the issue is not traceable locally on my development setup but once I deploy in production, it happens. I did few more tests, and even 6.4.12 is working perfectly. The error appears as soon as I upgrade to 6.4.14. It should be easy to trace the differences between the releases to get a clue what has been changed

@nolimits4web I got the reason now:
I have a ResizeObserver which destroys the swiper if a resize on the container is detected and reinitialize it. And this is breaking since 6.4.14.
  _registerObserver() {
    const ro = new ResizeObserver(() => {
      // this operation is pretty heavy but
      // the recalculation is heavy so we need to reinit
      this.swiper.destroy()
      this._initCarousel()
    })
    ro.observe(this._element.querySelector('.swiper-container'))
  }

Looks like you were faster than me :D

Thanks, just got the same issue.


Breaking down moderation into smaller tickets

User story
As the digital team, I would like to break the moderation work down into smaller tickets so that Norma/others can flesh them out for developer review.
Details
Nick's first draft
Process in wireframes

As suggested by @warrensearle, I'm going to start writing tickets for relevant tasks such as this.

I updated the Process in wireframes board and would suggest that any of the screens containing a green sticky note have work required so should each have a ticket.
Over to you @NormaJAC  :smile:

@warrensearle I'm closing this as job done :-)