add some search paths to the loading script.

please tell me what you think, nuget folders don't need to be named "packages", but we can kind of assume we are in the right folder...

I actually think we could drop the paths with packages completely. Doing just e.g. ../FSharp.Compiler.Service... should always work, or not?
Also, I think this change might break the version-update script in the build file: https://github.com/tpetricek/FSharp.Formatting/blob/master/build.fsx#L82. Could you check that?

I actually think we could drop the paths with packages completely. Doing just e.g. ./FSharp.Compiler.Service... should always work, or not?

I have projects where I use both (nuget and paket) to restore packages. It makes sense to have both in this case. It's the question if you want to support such strange environments or only focus on paket within FSharp.Formatting (everything else is the problem of the user).
I think you are right and we should focus (This doesn't really hit anyone as long as all packages belonging to FSharp.Formatting are in either paket or nuget)

Also, I think this change might break the version-update script in the build file: https://github.com/tpetricek/FSharp.Formatting/blob/master/build.fsx#L82. Could you check that?

Nice catch, I didn't notice that there is such a thing :). It should work now.

Do you want me to update RELEASE_NOTES.md here as well? There will be a merge conflict with my other pull request if I do that...

That's why I do this myself in my projects...
2015-03-03 16:04 GMT+01:00 matthid<EMAIL_ADDRESS>
Do you want me to update RELEASE_NOTES.md here as well? There will be a
merge conflict with my other pull request if I do that...
—
Reply to this email directly or view it on GitHub
https://github.com/tpetricek/FSharp.Formatting/pull/268#issuecomment-76961778
.

Thanks, looks good now! I'll update the release notes.

Perfect! Released in 2.7.5.


Remove @deprecated methods for v7.x

The next release is a MAJOR release (7.x) - it is probably time to remove some (all?) of the @deprecated methods and classes that have been kept around for backward compatibility.

Removed all deprecated functionality except for LogstashMarker.with.  I'm going to leave that since it could be prevalent in business logic, making upgrades difficult.  The removed deprecated functionality was mainly isolated to logging configuration, which should only affect small portions of codebases.


Just one addon car has default sirens

I have like 5 addon vehicles with sirens and only 1 of them does not follow the script.
What should I do?

What do you mean?

One addon car has default controls. No J K L, just E.

That means the car isn't an emergency vehicle

Ambulance is not an emergency vehicle?

The only vehicles that work are emergency vehicles, which is defined by the vehicle class

So the vehicles.meta of that vehicle is probably wrong

How am I supposed to change vehicles.meta of a vanilla vehicle?

You can re-stream it, but the vanilla vehicles should work though, let me check

The addon vehicle was in fact set improperly, to sedan.

The default ambulance in the game does have the emergency vehicle class

Are you sure you're not using an addon vehicle instead or the vehicles.meta of it is re-streamed?

I'm sure I'm not using an addon vehicle. I'm using a vehicle of which spawn code is ambulance.

It's weird. When I spawn an ambulance it's working fine, but if I use the one in hospital's garage it does not work.

So the issue is resolved. Thanks for telling me about the class.

Then that vehicle may be another model with the wrong vehicle class

Then that vehicle may be another model with the wrong vehicle class

I don't think so. I know what addon vehicles I got on my server.
Probably the way the ambulance got stored is messed up.

Probably the way the ambulance got stored is messed up.

Could be, I don't really know, if I come across this issue again, I'll do an investigation on it


Integration with HACS

HACS (https://hacs.xyz/) is a powerful addition for HA to download and update custom/3rd party components. It would be much easier to use it instead of downloading and manually updating your code at each release, especially in this beta phase when updates will be more frequent I guess.

Update: I tried to directly register this github repo as a custom repository into HACS but I get this error:
<Integration tronity/homeassistant> Repository structure for main is not compliant
You should really look at integrating into HACS, otherwise upgrading each time the code manually will be a pain.

@dellock6, I think the structure is this way so eventually can be popped into home assistant core

Fixed repository structure. Integration should now be available in HACS for easier downloading and updating!

Hi, I can confirm I was now able to add the integration via HACS custom repository, by pointing at the root folder in git!


Selecting text closes a job posting

If I expand a job posting on the home page and select some text from it, the detailed text collapses again.
This also happens when you click just outside of the "link" or "Apply" buttons, by the way. In general, I find the entire UX of "click anywhere in the text for an action" a bit confusing to be honest.
Firefox 70 on Linux

Closing this one as it's related to #3 - Let's continue the discussion around job expand/collapse on that issue.


[Project Dashboard] Add Global Project level settings to the Project Dashboard page

Motivation
If current Project/Domain doesn't have it's own uniques project level settings than we hide whole Domain Settings sections.
It can lead to a wrong assumption that none of the fields are used in this case, or that there is no setup possible.
However when default Project/Domain setting is empty we always use Global/Domain settings instead. They should be shown in the app to ensure that users know what they are working with.
Goal
Show globall Project/Domain settings
Provide Amount of Workflows / Executions / Tasks without need to request their details

Blockers
We need an API from BackEnd to access such settings. It is covered by: https://github.com/flyteorg/flyte/issues/2322
Ideally we would also want an API to get total number of workflows / executions per period / tasks to show this numbers in the header.
Currently we are requesting a whole list of Workflows and Tasks with 1000 limit, and count amount of items inside

Blocker:
API to retrieve Global Project domain is still needed.


Open Source : 6.97 Explain everything related to Nextcloud

Description 📜
Open Source : 6.97 Explain everything related to Nextcloud
NOTE 👇
Please put your doc 6.Popular_Projects with the name 6.97_Nextcloud.md

Domain
Open Source
Type of Contribution
Documentation
Code of Conduct

[X] I follow Contributing Guidelines & Code of conduct of this project.

Any updates on this ? @astelrastogi

/assign

@Binita-tech  Sure, Go ahead

can i work on this


Shows nothing in location list windows under Neovim in Windows

Expected behavior
Showing up proper content in the location list window.
Steps to reproduce
I'm using Neovim on Windows.
After running :Neomake in a .py file it pops up a cmd window and the window closed right after.
It shows nothing in the location list window.
Everything looks fine in the log file.

There is no log information about any output.
Does running cmd.exe /c pycodestyle "C:\Users\hankelbao\Workspace\test\test.py" manually work / produce output?
Which Neovim version are you using?
Can you try it with Vim?

Yes, it produces correct output.
I'm using Neovim 0.2.2.
I've just tried with GVim and it works fine.

it pops up a cmd window and the window closed right after

Does this also happen with GVim?
I think this should be avoided.
There are fixes regarding Windows in Neovim master (to become 0.3.0), maybe that helps here?!
You could try it using the pre-release via https://github.com/neovim/neovim/wiki/Installing-Neovim#windows.
Apart from that I've tried fixing args handling in https://github.com/neomake/neomake/pull/1896, but got blocked by setting up AppVeyor to really test it (https://github.com/neomake/neomake/pull/1575).

No, it doesn't happen in GVim.
I tried and Neovim 0.3.0-dev solved my problem.
Thank you!

Cool!
I guess it's related to https://github.com/neomake/neomake/blob/e106e2d552e6d72f1ffbda7b1821e743fd682825/autoload/neomake.vim#L413-L416 then.

can you try commenting those lines?  Does it work in Neovim 0.2.2 and 0.3 then?
can you try changing those lines to just let opts.pty = 1, and then try it with both Neovim 0.2.2 and 0.3 again?

If I comment those lines,
In both version, there are contents in the location list and they both work correctly.(seems problem solves)
If I change those lines to let opts.pty = 1,
In Neovim 0.2.2, there are lines of information in the location list but they are incomplete(can only display several words per line) and there are some strange characters like ^[[0m^[[0K
In Neovim 0.3.0, it works correctly.

Thanks for the detailed information.
Should be fixed now.

I can confirm that this DOES NOT fix the issue.
The problem still is the same.
https://github.com/neomake/neomake/blob/8e72d2e6c9a68ee0487eec703848e6bd7acdc41e/autoload/neomake.vim#L413-L418
Changing line 418 to:
        let opts.detach = 0

fixes the issue for nvim 0.2.2 and also works with nvim 0.3.0

@DahliaSR
Thanks for the report, should be fixed now really - the logic was wrong.

@blueyed
Confirmed - Now it works as expected for me.
Thx.


I asked him to add me a matrix animation. He doesn't understand it what I'm saying.

Describe the bug
Every time I ask for a prompt, he doesn't understand it. There's a lot of issues with the application.
Link to the Bolt URL that caused the error
https://bolt.new/~/sb1-b26fqd
Steps to reproduce
hh
Expected behavior
He's supposed to understand when I ask him to auto matrix animation
Screen Recording / Screenshot
jhjh
Platform
Browser name = Chrome
Full version = <IP_ADDRESS>
Major version = 130
navigator.appName = Netscape
navigator.userAgent = Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/<IP_ADDRESS> Safari/537.36
performance.memory = {
  "totalJSHeapSize": 131272257,
  "usedJSHeapSize": 105475949,
  "jsHeapSizeLimit":<PHONE_NUMBER>
}
Username = Rober2092
Chat ID = d7feead6de3e

Additional context
Did you guys need to order more on this model? It's gray I've been using a lot.

At times, there are programming challenges that are too complex for the AI to solve and manual intervention is required. This page here has more insights on using Bolt most effectively while maximizing token usage. Hope this helps!


Examples for replaceReducer and document how to use Redux in a code-split app

I haven't been able to find any meaningful examples or documentation on how to add reducers progressively in an app with code-splitting. I understand this is the job of http://redux.js.org/docs/api/Store.html#replaceReducer - it would help to have official examples + better documentation (maybe an "advanced" recipe) to show how to use redux with progressive enhancement.
Would be happy to work on it since I'm doing that for the day job anyway!

Check out https://github.com/mxstbr/react-boilerplate , I believe it does that.

Yep.  It generally comes down to calling combineReducers again with the new bunch of slice reducers, and then calling store.replaceReducer() with that result.
@neeharv , if you wanted to add a recipe that discusses code splitting and hot reloading, that would be great!  I do have an example of using the "plain" HMR API to hot reload reducers at http://blog.isquaredsoftware.com/2016/11/practical-redux-part-3-project-planning-and-setup/ , and a few more under https://github.com/markerikson/react-redux-links/blob/master/webpack-advanced-techniques.md#hot-module-replacement .


Documentation link returns a page not found error

Describe the bug
Some links are broken
To Reproduce
Steps to reproduce the behavior:

Go to https://docs.accordproject.org/docs/model-decorators.html
Click on the Decorators Reference hyperlink
A page not found is returned

Expected behavior
The link should redrect to the according page
Desktop (please complete the following information):

OS: windows
Browser chrome
Version 87.0.4280.66

@irmerk , similar to #329 the "Decorators Reference hyperlink" is broken, I think it should point to this

@irmerk , similar to #329 the "Decorators Reference hyperlink" is broken, I think it should point to this

@irmerk May I add this change in #343 ?

@Aniruddha-Shriwant sure just add them both to the same PR that's open.

Okay :)

This is resolved by #337


Create unittest for testing from client-side

For the moment, all the endpoints have to be tested using Python unittest and requests. For both the drone and the central server.
For example:
import unittest

import requests

class TestDroneRequests(unittest.TestCase):
    def test_request_vocab(self):
        r = requests.get(VOCAB_URL + '/droneapi/vocab')
        ...
       assert r.status_code == 200

Add testing for checking that PUT and POST methods actually operate the right changes in the db

Can you explain this one a bit? What do you mean by right changes in the db?

Test case pseudo-code:
request = requests.put('/some_class/<id>', some_data)
query = Database.get('<id>')

assert some_data == query

Implemented


Dated permalinks always use UTC instead of site timezone

Issue Summary
If you use dated permalinks in your routes.yaml file for a collection (permalink: /{year}/{month/{day}/{slug}/) and you have your site timezone set to something other than UTC then the date in the url may not match the publish date.
To Reproduce

Modify your routes.yaml to use dated permalinks
Set your timezone to non-UTC (a large timezone difference makes this easier to test)
Publish a post with a publish date that would result in a different date when converted to UTC (eg, if you've chosen UTC+8 as your site timezone, publish a post with a time between 00:00 and 08:00 to see a URL one day earlier than expected)
Examine the URL that is given to the post to see that it's +/- 1 day from the expected date

Technical details:
This bug was introduced in https://github.com/TryGhost/Ghost/pull/10787 where our url-utils package was extracted. The problem arises because the replacePermalink() method expects a third argument which is the site's timezone (defaulting to UTC when not present) but the UrlGenerator code which calls that method does not pass any argument.
Problems with a fix
Implementing a straightforward fix would introduce a breaking change for any site using dated permalinks and non-UTC timezones. Any of the site's posts with an "incorrect" date in the url would immediately get a new URL after the upgrade meaning that external links to the post would result in a 404. With the fix in place, changing the site's timezone would also modify post's URLs so we should make this clearer in the admin UI.
The bug has been in place for ~16 months so that's potentially quite a big unexpected breaking change for some sites.
There aren't too many options to work around the problem whilst keeping dated permalinks. If dated permalinks are dropped then it's possible to set up generic redirects using the {slug} value that is still present in the URL. If dated permalinks want to be kept then it would be necessary to work out which posts would receive a different URL and manually create a redirect for them.

Going to close this - it's still tracked as a potential change to make with 5.0 and will fit more when we look at reworking our routing layer. We haven't had any complaints, so I don't think anyone is seriously impacted.

Going to close this - it's still tracked as a potential change to make with 5.0 and will fit more when we look at reworking our routing layer. We haven't had any complaints, so I don't think anyone is seriously impacted.


Recognize syn::verbatim! as special case in ToTokens for macros

I am not totally sold on this idea but it would be a neat way to deal with new Rust syntax that is added between syn releases. Basically anywhere a macro is printed, if the macro path is syn::verbatim! then only whatever tokens are inside of the macro are printed.
// AST contains this
syn::verbatim! {
    impl Send for .. {}
}

// printed by ToTokens
impl Send for .. {}

Why not have a dedicated type for this in the AST rather than using a macro type? We could have TypeVerbatim, ExprVerbatim and ItemVerbatim as escape hatches. Each would just hold a TokenStream internally and when ToTokens-ed would dump it out. We'd never parse them but if you wanted to build them into your AST you could.

That sounds good to me. Would you prefer separate types like ExprVerbatim and ItemVerbatim that may even contain a Vec<Attribute> as well as tokens, or go for the less consistent but simpler way of holding a TokenStream directly?
  pub enum Item {
      ExternCrate(ItemExternCrate),
      ...
      Macro(ItemMacro),
+     Verbatim(TokenStream),
  }

I think that either approach is OK, but I do like the fact that the more consistent ExprVerbatim and ItemVerbatim types would let Fold/Visitor implementations visit these particular items/expressions explicitly.

That is a great point. Let's do it that way.

Added in 2ae520adce62e30e9f7be5280d08080ad0360028.


Chore: Update pk6parse to version 0.10.3 🚀

beep boop I'm not actually greenkeeperio-bot

You forgot the 🌴. I can't accept this


Feature settings

Add an option to have standard-settings in the project.
Makes it easy to work with different settings for each developer on a project.
I did

[x] add a question to add settings or not
[x] implement standard-settings
[x] check that it works in dev and production
[x] write a documentation about it
[x] update semaphore tests

I did want to add some tests to see if settings are properly loaded, but it uses remote.global and karma-electron does not allow custom global (see https://github.com/twolfson/karma-electron/issues/12).
So it can only be tested on the main side, I could add a setting that change the window size and test that in test/e2e/specs/Launch.spec.js. Let me know what you think about this.
Best,
Emmanuel

Hey @emmanuelgeoffray
Thank you for the generous contribution; it is surely planned out thoroughly. As wonderful and useful as this feature is, this becomes a rather large separation of concern for electron-vue. This boilerplate does its best not to force any particular structure, with the exception of common practices, for the end developer building their application.
The usage of standard-settings should be a choice the developer adds to their project. Now yes, I can see you added a vue-cli option to opt in for this new proposed feature, but then how does this differ from using config which aims to to solve the same need (or even electron-config for the more minimal approach)? What would stop the boilerplate from needing to support those other solutions? At that point, this is no longer a concern electron-vue should be focused on. This is ultimately a choice or preference on how the developer wants to solve this need.
I really wish you would had proposed this feature within an issue at first before working on this so you wouldn't have had to go as far as covering all tests and documentation. I truly mean all this is honestly and generosity, but for reasons described above I won't be merging this request.

Hi @SimulatedGREG,
Thank you for your kind reply.
I understand your point.
Don't worry about the time I spent adding this feature, as I do neet it within Soixante circuits, where we start many new projects needing this feature.
So I will keep this feature available in soixantecircuits/electron-vue and update our fork often with your changes on SimulatedGREG/electron-vue.
Thank you for your work on electron-vue.
Best,
Emmanuel


Question about Interaction to Next Paint (INP) implementation

Hello!
Do you have a plans for Interaction to Next Paint (INP) metric implementation?
Looks like implementation can be non-trivial, according to web-vitals package implementation.
I am interested in your opinion on this metric, as it will affect the size of the package badly, but it seems that this metric still have to start collecting in the future.

@Zizzamia hello! What do you think?

Ciao @SuperOleg39, thank you for the ping and sorry for the late reply.
Something I am been thinking for quite a while if it's time to make Perfume.js a superset of the Web Vitals package, by importing the package into Perfume and add some extra functionality on top of it.
This will help stay always align with Google updates, and also keep the extra features that Perfume wants to experiment and offers.
What's your thoughts on this?

Hi! Thanks for the answer)
I see only one problem about web-vitals integration - result package size, because at this moment web-vitals have 2.5kb gzip size, аnd perfume.js is 2.3kb gzip (Bundlephobia info).
What do you think to size-limit integration before?

@Zizzamia another reason to add web-vitals - https://github.com/GoogleChrome/web-vitals/blob/main/CHANGELOG.md#v300-2022-08-24
"Report TTFB after a bfcache restore" and new "attribution build" looks like very important and useful.

Yeah, I think Perfume.js is better suited to be a superset of web-vitals going forward. Going to make the change pretty soon. Just need to find a few hours to make the switch.
Recently I got distracted on building a Performance library for React Native. But now I am back with more coding time on my hands.

Alright, now Perfume.js is a super set of Web Vitals, starting from v8.0.0.
Please, if you see anything that is not working let me know and I will take care of it.

Thank you! Will try to integrate soon.

Only one problem, now perfume is 5kb gzip.
But I think than lazy loading solves this problem partially.

Looks like First Paint is unsupported in web-vitals

About Cumulative Layout Shift, there is a big change, when CLS fired after page visibility changed to hidden.
It is mean than we can send this metrics only when user leave page twice.
Maybe reportAllChanges  for CLS will be a good default? https://github.com/GoogleChrome/web-vitals/pull/283

About Cumulative Layout Shift, there is a big change, when CLS fired after page visibility changed to hidden.

The same behaviour with Total Blocking Time
For now it is impossible to collect this metrics when user closing page, if batching is used https://github.com/GoogleChrome/web-vitals#batch-multiple-reports-together

@Zizzamia maybe we start with this changes - https://github.com/Zizzamia/perfume.js/pull/208/files
About TBT, looks like it fired 10+ seconds after FID (expect 5 second because of https://zizzamia.github.io/perfume/#/total-blocking-time/) - so nothing to change here)

You right! The fact Perfume does not handle on his on Change Visibility, it does introduce a regression. Which is not good, and makes the data quite unuseful.
I am going to introduce back some fo the code related to Change Visibility that we used to have, and release a new version by the end of the year.
Thank you for keep trying Perfume.js!!!!
Making Perfume.js a superset of web-vitals will require some extra love to make it right. ✨

Will waiting for https://github.com/GoogleChrome/web-vitals/issues/180#issuecomment-1344720373

@SuperOleg39 your work in testing both libraries is just the best OSS Christmas present. Thank you man.
I reverted some of the changes I initially made, and trying to recover the initial value of Perfume.js but still keeping the library as superset of web vitals.
https://github.com/Zizzamia/perfume.js/releases/tag/v8.1.6
Let me know if looks better on your side, and love your testing in making Perfume.js better. I will make sure to prioritize your advice going forward.

Thank you for all this work!)
Test https://github.com/GoogleChrome/web-vitals/issues/180 PR with<EMAIL_ADDRESS>and reportAllChanges for CLS and INP - this metrics works perfect for my case!
Have only trouble with TBT - looks like this metric stop reported?

Looks like TBT not reported, when:

page loaded
some action, FID is reported
immediately leave page (not wait for 10 second for TBT report)
back to the page again
TBT will never be reported

Found this code https://github.com/Zizzamia/perfume.js/blob/master/src/log.ts#L42

Yeah the case you described is expected!
That's because the reporting to be accurate Perfume needs to wait the 10s to be over.
Glad Perfume, now works well for you.
Please let me know if there is anything I can help you with more.

Thanks for the explanation)


ESP.reset() - looping

Who can explain why after executing ESP.reset () there is a loop on the execution of the last command?
I use this code:
void loop() {
  TBMessage msg;
  if (bot.getNewMessage(msg) ) {
    String msgText = msg.text;
    Serial.print("msgText = ");
    Serial.println(msgText);
    if (msgText.equals("/rst")) {
      bot.sendMessage(msg, "reset");
      Serial.println("reset"); Serial.println();
      ESP.reset();
    }
  }
}

The module receives a command, executes it, reboots and ... again receives the same command. And so it goes on indefinitely. Only uploading the same code with the commented-out ESP.reset() line helps.
Here is what I get in Serial
Test Telegram connection... OK
msgText = /rst
reset

?)⸮
⸮⸮!H⸮.......
Test Telegram connection... OK
msgText = /rst
reset

?⸮⸮⸮1⸮D×⸮⸮⸮......
Test Telegram connection... OK
msgText = /rst
reset

<EMAIL_ADDRESS>Test Telegram connection... OK
msgText = /rst
2dO,4⸮hl,⸮xd>x⸮⸮⸮⸮R⸮......⸮EO|t.......
Test Telegram connection... OK
msgText = /rst
reset

The last received message after a reboot is again perceived as a new one? What is it connected with?

This is the same as https://github.com/cotestatnt/AsyncTelegram2/issues/62
You have to wait that message is fully handled before restart ESP.
Check this example
    if (msgText.equals("/rst")) {
      bot.sendMessage(msg, "reset");
      Serial.println("reset"); Serial.println();

      // Wait until bot synced with telegram to prevent cyclic reboot
      while (!myBot.noNewMessage()) {
        Serial.print(".");
        delay(50);
      }
      ESP.reset();
    }

Yes, it works. But now I would like to understand why this happens. Why doesn't regular delay() before ESP.reset() help? When is a received command considered processed? Does the module send some kind of confirmation to the bot?

When you send a request of update to Telegram server, it will reply with a list of last unreaded messages with specific message ID.
In order to get last message marked as readed, the next update request have to request for the last message ID + 1 otherwise Telegram server will reply again with last one unreaded.
This is the reason why you need to wait for noNewMessage() in you sketch.


Add mutex to prevent running same test in parallel

I don't like how it will "bloat" the reported test time when it's actually waiting for the test to start. Will see if I can find a way to avoid that.

I tried moving the mutex to setup/teardown in the hope that those would not be included in the test duration, but without success. I'm open to suggestions, otherwise this is ready for review.

I have no better ideas. I was only wondering whether the name of the mutex should be in the "Global" namespace but I don't know the CI configuration and how it manages test runs.

I was only wondering whether the name of the mutex should be in the "Global" namespace

I also have no idea. :smile: I guess the worst case scenario we get some test failures due to resource contention.


The class table only covers half the screen

so, i love this so far, it is my first time using it, and its amazing, but the class table is only covering half the screen, not the whole thing like its supposed to. is there a way i can fix this?
Additional Details
Share Link :
or
Brew code to reproduce : Click to expand
PASTE BREW CODE HERE

Looks like you might have forgotten to paste your share link so we can see what you mean. Could you go back and edit your post to include that? Thanks!

I'm having the same issue.
http://homebrewery.naturalcrit.com/share/Hk-Y5XqFkX
I believe this is an issue with Firefox. Seems like it might not support "-moz-column-span :all" used in  ".phb .wide". Looks like we'll need to grab a different browser for full functionality unfortunately.

https://bugzilla.mozilla.org/show_bug.cgi?id=616436
Firefox does not support column-span or -prefix variants.

Yep grabbed Opera and it's working perfectly.

Closing since there hasn't been a reply from the user for a while and it is assumed the problem was solved.
If you are still experiencing this issue, feel free to reopen and provide information, @Splintr1322


CFE does not emit CheckLibraryIsLoaded for redirecting factories.

See tests/language/deferred/redirecting_factory_test.dart which fails on all backends.
We might also decide to change specification instead.
/cc @johnniwinther @eernstg

In this case I actually think it would make sense to implement the error: If deferred loading means anything anywhere then I think the error must occur with any particular configuration where loading is actually deferred. It seems inconsistent if there is no error for this in some cases (where it is technically possible to run the ultimate redirectee of the given factory, e.g., because every deferred library is loaded eagerly anyway).

I think it should be a compile-time error when a deferred type is used in an extends, implements, with, or on clause (the latter: in a mixin declaration, and also in a try/catch statement). This is already specified, and it seems consistent to implement this error as specified.
For redirecting factory constructors the consistent treatment, as I see it, would be to incur a dynamic error in the case where the redirecting factory constructor is invoked, and this gives rise to an invocation of the redirectee constructor, which is declared in a deferred library that hasn't yet been loaded.


Tasks can be stored locally.

Hey @Abbhiishek,
I have come with an idea/feature that if we can store the user tasks locally, then it will allow the users to check their previous completed tasks.
Assign me, if it sounds good to you..
#12

That's a great feature @ChandanP007
Well how you are planning to implement that?

Ah, we can use the localStorage and sessionStorage. So, there will be two options for the user, whether the user wants the task to be saved in the local storage or just for that session only.


ARM support

Feature request
Version 0.15 has a release for arm  and arm64, but later versions have dropped the arm releases.
Are there any plans for arm releases to be reinstated as I wish to run headscale on my Raspberry Pi 3
Thanks,
Peter

You can compile it for armhf, but at this moment we do not plan to add support for it.

You can compile it for armhf, but at this moment we do not plan to add support for it.

Hello
Would you please point me in the right direction for compiling this for armhf?
I used
make
in the headscale directory, but I get this error:
pi@raspi:~/hs/headscale $ make
nix build
make: nix: No such file or directory
make: *** [makefile:22: build] Error 127

There are good cloud instances on arm, I hope you can reconsider.

@Ondjultomte https://github.com/juanfont/headscale/releases/tag/v0.23.0-alpha3
We are now supporting arm64 and armv5, armv6 and armv7.


[Backport 2.x] Adding task cancellation timestamp in task API

Description
Backports - https://github.com/opensearch-project/OpenSearch/pull/7445
Related Issues
https://github.com/opensearch-project/OpenSearch/pull/7445
Check List

[ ] New functionality includes testing.

[ ] All tests pass

[ ] New functionality has been documented.

[ ] New functionality has javadoc added

[ ] Commits are signed per the DCO using --signoff
[ ] Commit changes are listed out in CHANGELOG.md file (See: Changelog)

By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
For more information on following Developer Certificate of Origin and signing off your commits, please check here.

@andrross Can you review this? And cancel the duplicate/stale one - https://github.com/opensearch-project/OpenSearch/pull/7704?

@dblock Can you review this backport PR?


Doesn't Compile

Not sure for how long, but this doesn't compile anymore.  It's not in active development, but anyone can feel free to contribute for some good vibes.
I would like to see this transition to cmake as it is just a more elegant solution overall.
Tasks:

[x] Remove all references to automake
[x] Write a CMakeLists.txt file
[x] Verify that the code compiles (it won't run though, that will be a separate bug)

I have a simple makefile which will compile the code as of 6e54b5a76fc7613dd8f154386bcaad593e5a6315
CMakeLists.txt file will be added soon.

I've completed compiling with the CMake build system as of e1f49de9e89829f8d05028508678f46070116b89 (although it's not the cleanest implementation)


[BUG] Builtin order limit do NOT works

Expected Behaviour
The order limiter placed on "settings" should allow you to limit orders for each time slot
Actual behaviour
After setting an order limit for each time slot, this doesn't work
Reproduce steps
From the settings menu, I set a limit of 1 order per interval

However, I was able to normally place a higher number of orders from the site for the same timeslot

I also tried to change the status of these orders to "pending", or "preparation", but the 9:30 pm slot was still generated and it was possible to place orders for this time

Version
v.3.0.4-beta.26

@sampoyigi I think this has thrown off the max orders extension as well, so it looks like the event isnt being fired any more. Would the recent changes to working schedule have affected something?

@sampoyigi I think this has thrown off the max orders extension as well, so it looks like the event isnt being fired any more. Would the recent changes to working schedule have affected something?

@ryanmitchell you're spot on! Passed the currentTime instead of the timeslot to igniter.workingSchedule.timeslotValid event.. 😅

@ryanmitchell you're spot on! Passed the currentTime instead of the timeslot to igniter.workingSchedule.timeslotValid event.. 😅

@BreakSecurity can you confirm this is fixed for you and close it?

@BreakSecurity can you confirm this is fixed for you and close it?

So it works... but (there is always a but...) it make two timeslots unavailable and NOT one.

The order is placed at 1 o clock that is at the END of the timeslot 00:40, 01:00 but also at the BEGINNING of 01:00 01:20
Maybe this can help to understand why it makes TWO timeslots unavailable.
To confirm

I changed the interval to 40 mins

The order now is not between two timeslot but inside one timeslot
And, in fact, only one is removed this time. Right now an order invalidate two timeslot and not one.

So it works... but (there is always a but...) it make two timeslots unavailable and NOT one.

The order is placed at 1 o clock that is at the END of the timeslot 00:40, 01:00 but also at the BEGINNING of 01:00 01:20
Maybe this can help to understand why it makes TWO timeslots unavailable.
To confirm

I changed the interval to 40 mins

The order now is not between two timeslot but inside one timeslot
And, in fact, only one is removed this time. Right now an order invalidate two timeslot and not one.

@sampoyigi

@sampoyigi

Its working as expected for me on our installs. Im not able to replicate your issue.

Its working as expected for me on our installs. Im not able to replicate your issue.

I'm closing this as fixed! The other issue mentioned by @BreakSecurity is similar to this one #698


[dev] syntax error: unexpected T_STRING at line 5

Found a problem with the following code using the dev branch:
<?php

declare(strict_types=1);

$a = "JSON_MERGE('{\"vat\"}')";

results in:
syntax error: unexpected T_STRING at line 5

More examples:
<?php $a = "{\"";
# s`syntax error: unexpected '"' at line 1`,

<?php $a = "{\"\"}";
# s"syntax error: unexpected T_NS_SEPARATOR at line 1",

<?php $a = "{\"}";
// panic: runtime error: index out of range [0] with length 0 [recovered]

Thanks, it's working now!


Pre-built binary for ARM

Would it be possible build binaries for ARM (Linux)? I would be happy to submit a patch if this would be welcome.

Hi! ARM binaries would absolutely be welcome. You can use https://github.com/sunshowers/test-binary-release as a playground if you need to.

Released this as part of cargo-nextest 0.9.29 -- binaries will be available in the next 20 minutes.


update iresearch

Please note that for legal reasons we require you to sign the
Contributor Agreement
before we can accept your pull requests.

http://jenkins01.arangodb.biz:8080/view/PR/job/arangodb-matrix-pr/1795/


Does AEXML.swift works exactly as Element.swift?

Does the file AEXML.swift (https://github.com/tadija/AEXML/blob/973a1f5fd40abba5d4457e2b54f587a0d7d4cd0d/Source/AEXML.swift) works exactly as the Element.swift(https://github.com/tadija/AEXML/blob/master/Sources/Element.swift)?
Or is there some other file which works same as AEXML.swift?

In some update AEXML was refactored into multiple source files, before that everything was in AEXML.swift, but after all that same code was migrated to separate sources (all of them).


load_image_dataset  not found

Following the instructions of https://autokeras.com/start/
I've found this error
Loading load_image_dataset with
from autokeras.image_classifier import load_image_dataset
rise an error " No module named 'autokeras.image_classifier'"
checking the script in the
rise the error from different module "from autokeras.classifier import load_image_dataset"
I've found the function in the module image_supervised.py

@ankapale Would you please help change it in the start.md file?
Thanks.

I don't mind changing this if needed.

@ManuelLevi Thank you so much!
Please change it.
Appreciate your help.
@ankapale you can focus on the other issues.
Thanks.


Add python-dateutil as dependency

The MyPyllantAPI uses dateutil.tz but dateutil was not installed as a dependency. This line should fix this.

Thanks, I merged it.


Running traefik-kop on the same host running traefik

Hi,
When traefik-kop is running on the same host running traefik, sometimes it works and sometimes it doesn't. The services are successfully discovered, but they are, with the routers, duplicated because they are provided both by the Docker provider and the Redis providers. When I want to access a service and the router used is the one from Docker, it doesn't work because the router routes to the IP of the container (and I don't want the service container to belong to the traefik network so the gateway timeout error is expected). Else, it works. Is there any way to give a higher priority to the Redis routers, or is there any other workaround?
For context, I'm using Ansible to deploy my applications on several nodes. But I don't want the docker compose files to be dependent on the node where the corresponding containers are hosted, which happens without traefik-kop because I have to modify the docker compose files of the node running traefik to connect the containers to the traefik network, which is what I'm doing for now and it works, but it is not what I want. Ideally, I just want to deploy traefik-kop on all the nodes, included the one running traefik, and don't have to modify the docker compose files of the node running traefik. I could use a VM just for traefik, but I think it's a bit overkill and not very convenient.

Sounds like you may be better served leveraging docker contexts and managing all of the deployment from a single node? That's what I'm doing and I switch contexts from my primary Traefik node and Traefik-kop is installed on all secondary nodes.

I just tried and it's fine this way. Thanks!


missing_observer

how to use observer methods like added,updated, removed  with this library

Hi, it is not possible right now, but I might be adding this very soon.
PRs are welcome too ;)

Done :)
See release 0.6.0


Unable to add element intervideosink

Hi there,
I have built the latest source of brave and performed simple test,

installed: GStreamer 1.14.3, python3.6 and all other preliminaries including libraries.
simple test pipeline: a video input -> mixer -> output(rtmp)

However it doesn't work at adding input to mixer.
I think 'intersink' has not been created properly.
Does anyone know how t solve it?
debug log
[2021-03-25 13:01:29 +0900] [45497] [INFO] Goin' Fast @ http://<IP_ADDRESS>:5000
INFO: [   output1] RTMP output now configured to send to rtmp://[test_rtmpserver_ip_addr]/live/livestream
ERROR: [    input1] Unable to add element intervideosink
ERROR: [    input1] Unable to add element queue
Traceback (most recent call last):
File "brave.py", line 71, in
start_brave()
File "brave.py", line 61, in start_brave
session.start()
File "/home/bkim/git/brave/brave/session.py", line 36, in start
self._setup_initial_inputs_outputs_mixers_and_overlays()
File "/home/bkim/git/brave/brave/session.py", line 89, in _setup_initial_inputs_outputs_mixers_and_overlays
mixer.setup_sources()
File "/home/bkim/git/brave/brave/mixers/mixer.py", line 94, in setup_sources
connection.add_to_mix(details)
File "/home/bkim/git/brave/brave/connections/connection_to_mixer.py", line 47, in add_to_mix
self._ensure_elements_are_created()
File "/home/bkim/git/brave/brave/connections/connection_to_mixer.py", line 186, in _ensure_elements_are_created
self._create_video_elements()
File "/home/bkim/git/brave/brave/connections/connection_to_mixer.py", line 212, in _create_video_elements
intervideosrc, intervideosink = self._create_inter_elements('video')
File "/home/bkim/git/brave/brave/connections/connection.py", line 99, in _create_inter_elements
intersink.set_property('channel', channel_name)
AttributeError: 'NoneType' object has no attribute 'set_property'
yaml configuration
enable_video: true
enable_audio: true
default_mixer_width: 640
default_mixer_height: 360
inputs:
- id: 1
type: test_video
pattern: 18
outputs:
- type: rtmp
uri: rtmp://[test_rtmpserver_ip_addr]/live/livestream
source: mixer1
mixers:
- sources:
- uid: input1
zorder: 2
width: 160
height: 90

This has been resolved with reinstalling latest gstreamer, 1.19.0,  on Ubuntu 20.04.


Refactor code and models to support TF 2.x and tf.keras

At some point in the somewhat near future, we should establish support for TF 2.x and tf.keras. The main reasons for this are:

To remain compatible with new releases of TF and Keras (the official version of which is now tf.keras) and make use of bug fixes, etc. some regression issues. As we have found (#42, #43), installing with newer versions of either package break installation and usage.
To address multiple vulnerabilities contained in tensorflow < 1.15.2.
To simplify the installation process; since TF 2.x now includes support for both CPU and GPU, we can now directly include tensorflow in the project dependencies, (as brought up in #39).

A priori, it seems like the main things to do are:

Updating the dependencies in setup.py to include tensorflow
Modifying the model definitions to be tf.keras compatible
Porting the model files to a format that can be loaded by tf.keras with TF 2.x

The main concern that comes to mind is the regression tests. We have already seen that tensorflow > 1.13 causes regression tests to fail. I imagine that this will only worsen as we introduce not only a new major release to TF, but also a divergence in Keras with tf.keras. @justinsalamon, what are your thoughts?

Generally I totally support this move. My main concern as you've identified is the move from keras to tf.keras. As an example, I believe @jongwook tried to migrate CREPE from Keras to tf.keras and gave up on it because of incompatibilities and changes to the behavior of the model.
If we can make all of these changes while maintaining model performance (and hence regression tests), I think it's a no brainer. If the tests fail, then it'd probably be worth re-training the openl3 models against the new model implementation, ensuring the resulting embeddings are equally competitive on at least one downstream (e.g. US8K) and then releasing that.
Thoughts?

p.s - we might be able to get away without re-training the models if we can at least show that the weights we have right now, coupled with the new implementation, still produce comparable downstream results. Then we'd just have to update the regression data for the regression tests.
So I guess my proposed steps would be:

Update to tf.keras - if regression tests pass, we're done.
If the regression tests fails, evaluate the resulting embeddings on downstream tasks. If they are equally competitive, update the regression test using the new implementation.
If the modified embeddings aren't competitive, then we'd have to re-train against the new implementation.

As an example, I believe @jongwook tried to migrate CREPE from Keras to tf.keras and gave up on it because of incompatibilities and changes to the behavior of the model.

This happened once when tf.keras was in the very early stage in the development, but CREPE is currently using tf.keras without causing disaster AFAIK. (and yes I am responsible for not writing real regression tests there)

Ah cool, thanks for the info @jongwook. So it sounds like we should be able to at least give it a try, but yeah, we gotta be solid on performance and regression.

@justinsalamon That plan sounds good to me. I'll see about looking into this in the near future.

Hi, first of all thank you for sharing the code and model! I had a go at the TF2 support (branch tf2 in my fork) and it turns out that the regression tests fail after switching to tf.keras. So the new embeddings would need to be evaluated on any downstream tasks.

Hi, we are working with a sound recognizer currently based on vggish.  Our recognizer runs on an edge device and stretches the small CPU's to the limit. Too much heat and too much power usage.  So we want to try out tensorflow-lite, perhaps in combination with a Coral co-processor.  Unfortunately is only supported on TF2.  For vggish there are now some TF2 ports available and we have an evaluation of the port on our roadmap.
But we also very much would like to evaluate  openl3 for our application. But not if this would lock us to TF1.x again.
The last post for this issue was almost 4 months ago.  What are your current plans/goals regarding the TF2 port?

@gmos we definitely plan to add TF 2.x support, but since this is a "side gig" for all of us, it is hard to provide concrete plans/estimates. We'll do our best to discuss in the near future and come up with an estimate, which we'll post here. Thanks!

@gmos When you say it's "only supported on TF2", do you mean vggish, tensorflow-lite, or the coral coprocessor?  I am considering using the coral coprocessor to run the openl3 model on TF 1.x.  Is that possible?

@gmos When you say it's "only supported on TF2", do you mean vggish, tensorflow-lite, or the coral coprocessor?  I am considering using the coral coprocessor to run the openl3 model on TF 1.x.  Is that possible?

Nope. Last time when I looked at it, Coral required TF-Lite which only exists on TF2.
From: Daniel Austin<EMAIL_ADDRESS>Sent: Wednesday, 13 January 2021 22:53
To: marl/openl3<EMAIL_ADDRESS>Cc: Gijs Mos<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [marl/openl3] Refactor code and models to support TF 2.x and tf.keras (#46)
@gmoshttps://github.com/gmos When you say it's "only supported on TF2", do you mean vggish, tensorflow-lite, or the coral coprocessor? I am considering using the coral coprocessor to run the openl3 model on TF 1.x. Is that possible?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHubhttps://github.com/marl/openl3/issues/46#issuecomment-759761975, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AALUWEG3XJCRTPP4ZXDK6JTSZYI4RANCNFSM4LAUOORQ.

Nope. Last time when I looked at it, Coral required TF-Lite which only exists on TF2.
From: Daniel Austin<EMAIL_ADDRESS>Sent: Wednesday, 13 January 2021 22:53
To: marl/openl3<EMAIL_ADDRESS>Cc: Gijs Mos<EMAIL_ADDRESS>Mention<EMAIL_ADDRESS>Subject: Re: [marl/openl3] Refactor code and models to support TF 2.x and tf.keras (#46)
@gmoshttps://github.com/gmos When you say it's "only supported on TF2", do you mean vggish, tensorflow-lite, or the coral coprocessor? I am considering using the coral coprocessor to run the openl3 model on TF 1.x. Is that possible?
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You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHubhttps://github.com/marl/openl3/issues/46#issuecomment-759761975, or unsubscribehttps://github.com/notifications/unsubscribe-auth/AALUWEG3XJCRTPP4ZXDK6JTSZYI4RANCNFSM4LAUOORQ.

I was able to compile and run the openl3 model using tflite with tensorflow 1.x on google colab.  Here is the code to compile to tf-lite with %tensorflow_version 1.x.  I have to use colab because I don't have an Nvidia card and I could not get tflite to compile the openl3 model without it (after lots of attempts).  I can, however, run the openl3 models on my desktop machine, albeit very slowly.
import tensorflow as tf
import openl3

ctype = "env"
itype = "mel256"
esize = 512 # I'm only interested in 512 model, so don't change this

model = openl3.models.load_audio_embedding_model(
      content_type=ctype, embedding_size=esize, input_repr=itype)

# Note: getting all this working was tough to do.  tensorflow-gpu is essential
# and variables must be initialized.  Saving the model and/or loading the weights
# doesn't work.
with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())

    bn = f"ol3_{ctype}_{itype}"
    converter = tf.compat.v1.lite.TFLiteConverter.from_session(
            sess, model.inputs, model.outputs)
    tflite_model = converter.convert()

    # Save the model.
    with open(f'{bn}.tflite', 'wb') as f:
      f.write(tflite_model)

I was able to download the tflite model file and then run it on my Desktop PC, which does not have CUDA or an Nvidia card, so it's running CPU only.  This code will run the tflite file.  I compared the output to the npz values generated with openl3 process_audio_file, and they don't agree at all, so there's either a bug or I am not preprocessing the data for tflite the same way process_audio_file does for keras.
import numpy as np
import tensorflow as tf
import soundfile as sf
import time

# Note: inputs data better be 48000 samples!
audio, sr = sf.read("1second.wav",
        dtype='float32') # dtype must match tflite model expectation

# Load the TFLite model and allocate tensors.
interpreter = tf.lite.Interpreter(model_path="ol3_env_mel256.tflite")
interpreter.allocate_tensors()

# Get input and output tensors.
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()

# Test the model on random input data.
input_shape = input_details[0]['shape']
print(input_shape)
audio = audio.reshape(1, 1, audio.shape[-1])

t = time.time()
input_data = audio
interpreter.set_tensor(input_details[0]['index'], input_data)
interpreter.invoke()

# The function `get_tensor()` returns a copy of the tensor data.
# Use `tensor()` in order to get a pointer to the tensor.
output_data = interpreter.get_tensor(output_details[0]['index'])
print(f"Time {time.time() - t} seconds")
print(output_data)

ol3_output = np.load("1second.npz")
ol3_embedding = ol3_output['embedding']
print(ol3_embedding)

I want to explore some more with getting TF lite to agree with the canned openl3 models as well as change the compile options for tf lite to use more integers.  It seems silly to require the audio input as float32 in my example when it's natively 16 bit signed audio.

I was able to compile and run the openl3 model using tflite with tensorflow 1.x on google colab.  Here is the code to compile to tf-lite with %tensorflow_version 1.x.  I have to use colab because I don't have an Nvidia card and I could not get tflite to compile the openl3 model without it (after lots of attempts).  I can, however, run the openl3 models on my desktop machine, albeit very slowly.
import tensorflow as tf
import openl3

ctype = "env"
itype = "mel256"
esize = 512 # I'm only interested in 512 model, so don't change this

model = openl3.models.load_audio_embedding_model(
      content_type=ctype, embedding_size=esize, input_repr=itype)

# Note: getting all this working was tough to do.  tensorflow-gpu is essential
# and variables must be initialized.  Saving the model and/or loading the weights
# doesn't work.
with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())

    bn = f"ol3_{ctype}_{itype}"
    converter = tf.compat.v1.lite.TFLiteConverter.from_session(
            sess, model.inputs, model.outputs)
    tflite_model = converter.convert()

    # Save the model.
    with open(f'{bn}.tflite', 'wb') as f:
      f.write(tflite_model)

I was able to download the tflite model file and then run it on my Desktop PC, which does not have CUDA or an Nvidia card, so it's running CPU only.  This code will run the tflite file.  I compared the output to the npz values generated with openl3 process_audio_file, and they don't agree at all, so there's either a bug or I am not preprocessing the data for tflite the same way process_audio_file does for keras.
import numpy as np
import tensorflow as tf
import soundfile as sf
import time

# Note: inputs data better be 48000 samples!
audio, sr = sf.read("1second.wav",
        dtype='float32') # dtype must match tflite model expectation

# Load the TFLite model and allocate tensors.
interpreter = tf.lite.Interpreter(model_path="ol3_env_mel256.tflite")
interpreter.allocate_tensors()

# Get input and output tensors.
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()

# Test the model on random input data.
input_shape = input_details[0]['shape']
print(input_shape)
audio = audio.reshape(1, 1, audio.shape[-1])

t = time.time()
input_data = audio
interpreter.set_tensor(input_details[0]['index'], input_data)
interpreter.invoke()

# The function `get_tensor()` returns a copy of the tensor data.
# Use `tensor()` in order to get a pointer to the tensor.
output_data = interpreter.get_tensor(output_details[0]['index'])
print(f"Time {time.time() - t} seconds")
print(output_data)

ol3_output = np.load("1second.npz")
ol3_embedding = ol3_output['embedding']
print(ol3_embedding)

I want to explore some more with getting TF lite to agree with the canned openl3 models as well as change the compile options for tf lite to use more integers.  It seems silly to require the audio input as float32 in my example when it's natively 16 bit signed audio.

I have edited my previous comment to include code that successfully compiles openl3 to TFLite in tensorflow 1.x on google colab.  TFlite model is faster and produces resulting audio embeddings that agree with vanilla openl3.

I have edited my previous comment to include code that successfully compiles openl3 to TFLite in tensorflow 1.x on google colab.  TFlite model is faster and produces resulting audio embeddings that agree with vanilla openl3.

Thanks @fluffynukeit !
We're hoping to port openl3 to TF 2.x, it's just a question of when we're able to allocate the cycles to it.

Thanks @fluffynukeit !
We're hoping to port openl3 to TF 2.x, it's just a question of when we're able to allocate the cycles to it.

@justinsalamon  Thank you for providing openl3!  It saved me so, so much time.  I don't have proper ML hardware or ecosystem knowledge, so having models that largely "just work" out of the box for audio classification is great.  I threw random forest at the embeddings as suggested in another issue here and was able to iterate on tuning it instead of messing with the NN models.

@justinsalamon  Thank you for providing openl3!  It saved me so, so much time.  I don't have proper ML hardware or ecosystem knowledge, so having models that largely "just work" out of the box for audio classification is great.  I threw random forest at the embeddings as suggested in another issue here and was able to iterate on tuning it instead of messing with the NN models.

Since May this year and merge request #62 it looks like TF2 is supported. So when 0.4.0 is released maybe this issue can be closed?

Closed by #62


Remove background debugging print statement

This PR removes a debugging print statement that was left behind, solving #258.
@mattersoflight brought up a potential concern that "local_fit" background corrections were being applied to phase reconstructions, but I have reread the code closely and found that this is not the case. Background corrections are only being applied to polarization acquisition.

I found this behavior confusing too. Also when initializing the reconstructor for phase from BF, maybe we can explicitly pass in None for the bg_correction keyword argument (which defaults to "local_fit") here:
https://github.com/mehta-lab/recOrder/blob/23f6edd864eafbc16be6b07f9c231f0abe1be178/recOrder/acq/acquisition_workers.py#L230-L247

Agreed. Changing the keyword argument to "None" is much cleaner. Thanks!

Codecov Report

Merging #261 (c4b7ad5) into main (ecca6ff) will increase coverage by 0.01%.
The diff coverage is 0.00%.

@@           Coverage Diff            @@
##            main    #261      +/-   ##
========================================
+ Coverage   4.37%   4.38%   +0.01%
========================================
  Files         22      22
  Lines       4986    4971      -15
========================================
  Hits         218     218
+ Misses      4768    4753      -15

Impacted Files
Coverage Δ

recOrder/compute/qlipp_compute.py
0.00% <ø> (ø)

recOrder/plugin/main_widget.py
0.00% <0.00%> (ø)

recOrder/plugin/gui.py
0.00% <0.00%> (ø)

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⚠ Bofrost.de has degraded performance

In 6a7fd53, Bofrost.de (https://www.bofrost.de) experienced degraded performance:

HTTP code: 200
Response time: 946 ms

Resolved: Bofrost.de performance has improved in dab7911.


Entry point :Add condition issues

Change to sentence case.
Comparison of storybook to Button Figma asset:
a. Looking closely at the button in the storybook, it seems that the text and icon aren’t aligned to the center of the button’s frame.
b. Seems like the icon isn’t aligned to the text.
c. Not sure, but, it seems like the icon is smaller than the original 8px icon. Are we employing custom code on this button?
d. Color token for Ghost - Label should match $link-primary
e. Color token for Ghost - Label:hover should match $link-primary-hover

issue 2 is the carbon button behaviour.


Replace data file with resource when reporting on the publishing page

@peterdesmet I guess it would make more sense? Otherwise we can leave it as it is

Yeah, resource is more correct, but can clash with an IPT resource ( = dataset). Maybe you can opt to use the full names Data Package (title case) and Data Resource (title case). And then also use "creating" over "writing"

Data Package generation started for version #1.0
Metadata added
Start creating Data Resource deployments
Data Resource deployments created with 1539 records and 24 columns

Processing record 365999 for Date Resource media

Deployed to UAT


Please invite me to the Community Organization

Name
Ogundipe Orobola Roland
Discord Username (if applicable) E.g John#412
Oga_rolly#4510
Questions & suggestions?
No response

Welcome to Communitypro. @rolandexplore93 🙌🏾🤩


Add cell cycle analysis

New

Adds sceu.ipynb to evaluate the performance of veloVI and scVelo's EM model on the scEU-seq cell cycle data.
Adds fucci.ipynb to evaluate the performance of veloVI and scVelo's EM model on a FUCCI cell cycle dataset.

Anything that I missed, @adamgayoso?

just need to add the files to the toc so they get rendered by jupyter book


Type guards in array find

TypeScript Version:  3.9.2

Search Terms:
Expected behavior: No error
Actual behavior: Error Type 'string | null | undefined' is not assignable to type 'string | undefined'. Typescript doesn't take into account the type guard in find arrow function.

 It's a function that returns boolean. A type could would return v is string.
You can fix it by adding a type annotation to make it a type guard: find((v): v is string => v !== null)
Alternative just add a comfort function:
function isNotNull<T>(value: T | null): value is T { return value !== null; }

find(isNotNull)

Also your playground link does not work.

v !== null is a type guard, no ?
Typescript should do the same assumption on find result than inside a if (res !== null) { ... }
Ideally a developer should not have to do anything special for this code to work. Don't you agree ?
But your code works fine thanks !
As for the playground link I used the "Export->Report GitHub issue on TypeScript" menu of typescript Playground...

v !== null is a type guard, no ?
Typescript should do the same assumption on find result than inside a if (res !== null) { ... }
Ideally a developer should not have to do anything special for this code to work. Don't you agree ?
But your code works fine thanks !
As for the playground link I used the "Export->Report GitHub issue on TypeScript" menu of typescript Playground...

no, v !== null is an expression which typescript can use to infer a more restricte type, but it's not an actualy type guard.
The problem is that typescript can't really return guard-like expressions from a function without explicitly stating that the function is a guard. I've wrote the #37868 issue in an attempt to address that situation; hopefully someone more knowledgable than me can work that into the language.


Feature: Support unix domain socket directory configuration

Issues associated with this PR
mosn's reconfig.sock path is fixed,  to support hot upgrade between two containers, reconfigure unix domain socket path needs to be configurable.
Solutions
add "uds_dir" filed, which is used to store *.sock files

需要考虑如果热升级时 路径配置一样的行为是什么


adding "where" param

lets us do first or last (default is "last")
part of
#207

Note that this is not reflected in the legend ordering right now. I am not very familiar with that. So if we like this, we should create an issue to also include first or last in the way we append the legend contents for auto legends

Coverage increased (+0.1%) to 77.001% when pulling c0a924b06943fc44f8d0b19c8e453952d9dc6b38 on jread-usgs:master into 539e9d263d43f73e87be1d1b49d9fb99e7d46fa3 on USGS-R:master.

Coverage increased (+0.1%) to 77.001% when pulling c0a924b06943fc44f8d0b19c8e453952d9dc6b38 on jread-usgs:master into 539e9d263d43f73e87be1d1b49d9fb99e7d46fa3 on USGS-R:master.

added the legend re-ordering
gs = gsplot() %>% points(1:2,2:3, cex=c(2.5,1), pch=0, lwd=3, legend.name=c('points.1','points.2'), bg='cyan', xlim=c(0.5, 2.5), ylim=c(1.5,3.5)) %>%
    points(1,2, pch=17, col='green', cex=4, where='first', legend.name='points.3', bg='dodgerblue') %>% legend()
gs

I tried a bunch of different combos of things, and it seems things are operating as expected.

Coverage increased (+0.9%) to 77.717% when pulling 9eb474c2b431af05f6e8ac2bcdad5b8becfe558c on jread-usgs:master into 539e9d263d43f73e87be1d1b49d9fb99e7d46fa3 on USGS-R:master.


Parallelize commit rebased

Guide to this PR:

Created a class SafeDatasetCommit. Refactored a lot of the commit logic from JobContext to this class.
JobContext creates an IteratorExecutor to execute dataset commits in parallel.
Added a isThreadSafe method to DataPublisher. If this is false (default), Gobblin will automatically fall back to serial commit even if user choses parallel commit.
Added a unit test to ensure JobContext handles publisher failure semantics correctly.

@pcadabam @ydai1124 can you review?

Overall looks good. A few comments.

Changes Unknown when pulling b3a61bdef795f14b0f53981acc5d5cb0336a128f on ibuenros:parallelize-commit-rebased into ** on linkedin:master**.

@ydai1124 addressed comments.

LGTM

Coverage increased (+0.2%) to 45.925% when pulling 9f156d910de5e8e6a0e5acdda7c451c2cff23c41 on ibuenros:parallelize-commit-rebased into f8303a7f1c97e12b42b8d181c17bf74122980f2b on linkedin:master.

LGTM. I have created ETL-4633 as a follow-up for the above code re-factorings.


changing bootstrap.servers list as a failover mechanism

Affects Version(s): 2.3.7
by now we change bootstrap.servers list as a failover mechanism and reuse a bean which contains a kafkaTemplate object by doing these:
1. call flush() of the kafkaTemplate object
2. call reset() of the kafkaTemplate's producerFactory
3. set accessibe attribute of the kafkaTemplate's producerFactory to true (by reflecting)
4. set kafkaTemplate's producerFactory to a new producerFactory using a changed bootstrap.servers list

but we are concerned that it might cause compatible problems. why such failover mechanism is not be provided officially?

GitHub issues are for reporting bugs, not asking questions. Use Stack Overflow or GitHub discussions to ask questions.
The framework provides an ABSwitchCluster class to toggle between 2 brokers. See the documentation and this answer on Stack Overflow.
In addition, starting with version 2.5.10, the ProducerFactory now has this method.
/**
* Update the producer configuration map; useful for situations such as
* credential rotation.
* @param updates the configuration properties to update.
* @since 2.5.10
*/
default void updateConfigs(Map<String, Object> updates) {
}


won't work

Issue Type: Bug
fix it!!
Extension version: 1.0.1245
VS Code version: Code 1.40.1 (8795a9889db74563ddd43eb0a897a2384129a619, 2019-11-13T16:49:35.976Z)
OS version: Windows_NT x64 10.0.18362
Remote OS version: Linux x64 4.4.0-18362-Microsoft

@ahmadkhaleel96 , Can you give us more details about your scenario? Also, your logs may provide us with helpful information. You can access them via the Live Share: Export Logs command from the command palette (ctrl + shift + p) and attach them to this issue.

Closing this due to inactivity. Please reopen it if you’re still encountering the issue. Thanks!


ffmpeg error during infer, audio file path seems fine

I get the following error when trying to infer
however my file path for the audio file is "C:\Users\lolfa\Downloads\scatman2", which seems fine to me, and the filename is vocalscatman.wav, which also seems fine
Traceback (most recent call last):
File "C:\Users\lolfa\Downloads\RVC-beta\my_utils.py", line 14, in load_audio
ffmpeg.input(file, threads=0)
File "C:\Users\lolfa\Downloads\RVC-beta\runtime\lib\site-packages\ffmpeg_run.py", line 325, in run
raise Error('ffmpeg', out, err)
ffmpeg._run.Error: ffmpeg error (see stderr output for detail)
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "C:\Users\lolfa\Downloads\RVC-beta\infer-web.py", line 160, in vc_single
audio = load_audio(input_audio_path, 16000)
File "C:\Users\lolfa\Downloads\RVC-beta\my_utils.py", line 19, in load_audio
raise RuntimeError(f"Failed to load audio: {e}")
RuntimeError: Failed to load audio: ffmpeg error (see stderr output for detail)
Traceback (most recent call last):
File "C:\Users\lolfa\Downloads\RVC-beta\runtime\lib\site-packages\gradio\routes.py", line 321, in run_predict
output = await app.blocks.process_api(
File "C:\Users\lolfa\Downloads\RVC-beta\runtime\lib\site-packages\gradio\blocks.py", line 1007, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "C:\Users\lolfa\Downloads\RVC-beta\runtime\lib\site-packages\gradio\blocks.py", line 953, in postprocess_data
prediction_value = block.postprocess(prediction_value)
File "C:\Users\lolfa\Downloads\RVC-beta\runtime\lib\site-packages\gradio\components.py", line 2076, in postprocess
processing_utils.audio_to_file(sample_rate, data, file.name)
File "C:\Users\lolfa\Downloads\RVC-beta\runtime\lib\site-packages\gradio\processing_utils.py", line 206, in audio_to_file
data = convert_to_16_bit_wav(data)
File "C:\Users\lolfa\Downloads\RVC-beta\runtime\lib\site-packages\gradio\processing_utils.py", line 219, in convert_to_16_bit_wav
if data.dtype in [np.float64, np.float32, np.float16]:
AttributeError: 'NoneType' object has no attribute 'dtype'

im having this problem as well, can anyone help

Is it only this path and file giving you the error? Also try running it under the batch conversion by uploading only that audio file and see if it still spits out the error.

try using batch conversion it works.

Make sure your path (folder names) do not contain any spaces, "_", "-", "()", "[]", "{}" etc. Just plain normal names.

try using batch conversion it works.

How would I do that?

@archangel012 did u resolve this issue? I've same problem here


Support AWS resource: aws_s3_bucket_public_access_block

Description
Add AWS support for aws_s3_bucket_public_access_block (TF)

This issue has been referenced in the v0.28.0 release.


[stable/traefik] Extra ACME options for Traefik chart

Is this a BUG REPORT or FEATURE REQUEST?

Version of Helm and Kubernetes:
Helm: v2.7.2
Kubernetes: v1.9.1
Traefik: 1.5.0
Which chart:
/stable/traefik/
What happened:
Let's Encrypt throws a error when getting the certs for my domains. The error is:
Error getting ACME certificates [lb.ikbendirk.nl] : cannot obtain certificates map[lb.ikbendirk.nl:[lb.ikbendirk.nl] acme: Could not determine solvers]

This is described in issue #2681 of Traefik.
What you expected to happen:
The solution to this problem, that is caused by a change by Let's Encrypt, is described in PR #2701 in the Traefik repo. To make auto certificates via Let's Encrypt work again, we need to set a setting in the .toml config file that is generated by Helm.
[acme.httpChallenge]
entryPoint = "http"

This option is not settable with the current option that the chart provides
How to reproduce it (as minimally and precisely as possible):
Using the versions as describe above, and setting the ACME options to true in de values.yml used by helm to deploy traefik.
Anything else we need to know:

See https://github.com/kubernetes/charts/pull/3347


[SUPPORT] CoW table data size increasing x times the original data size for x number of runs

Tips before filing an issue

Have you gone through our FAQs?

Join the mailing list to engage in conversations and get faster support at<EMAIL_ADDRESS>

If you have triaged this as a bug, then file an issue directly.

Describe the problem you faced
Existing data architecture in datalake:

A snapshot of data is carried over for every incremental run onto a new partition
IDL        = 15.6 GB
IDL + 1 = 15.9 GB
IDL + 2 = 16.2 GB
Total = 47.7 GB
I'm working on a PoC for Hudi to decrease snapshotting data for every run and using a CoW table for upserts. Although my count matches between the CoW table and the latest snapshot of my datalake table, the size difference is huge.
The size of latest snapshot in datalake is 47.7 GB
Hudi IDL = 17.6 GB
IDL + 1 = 36.5 GB
IDL + 2 = 54.4 GB
The size of the Hudi table is 54.4 GB

It defeats the purpose of migrating to Hudi tables from storage perspective. The compute time also increased by nearly 50% for the 3rd run.
A clear and concise description of the problem.
To Reproduce
Steps to reproduce the behavior:

Load sample data into an external table on s3 and check the size
Upsert the table with a few records and check the size
Check if the size in s3 is doubled

Expected behavior
Size to not increase X times for X number of runs
A clear and concise description of what you expected to happen.
Environment Description

Hudi version :  0.7.0 installed in EMR 5.33

Spark version : 2.4.7

Hive version : 2.3.7

Hadoop version : Amazon 2.10.1

Storage (HDFS/S3/GCS..) : s3

Running on Docker? (yes/no) : No

Additional context
Add any other context about the problem here.
Datalake data size:

Hudi data size for the same partitions:

The data count matches for both datalake and Hudi table.
Stacktrace
Add the stacktrace of the error.

Yes, COW will make a copy(of existing data) and merge incoming records and write a new data file. So, if you have configured to retain lets say 10 commits, 10 copies of 1 data file w/ some iterative additions will part of hudi table. If you are interested in just the latest, you can set the commits to retain config to just 1.
hoodie.cleaner.commits.retained
So, this will maintain just 1 version of data file in hudi.

Thanks for the information. I have a couple of questions.

If cleaner.commits.retained=1, then is rollback to previous versions possible?
Still, data size for 1 commit is greater than the original data size. original is 15.6 GB and hudi size is 17.6 GB. Is it possible to reduce this?

yes, may not be possible.
yes. hoodie adds some meta fields like to store the computed record key, partition path, commit time , etc for every record. to support incremental queries, and to avoid recomputing record keys during merges etc, these are unavoidable. But we recently added support for virtual keys with which this overhead can be avoided, but you might have to give up on incremental query and few other limitations.

@nsivabalan  I tested this scenario with >400 GB data with a few incremental loads. Following the order of the loads and data size.
Datalake is snapshot into another partition and Hudi is upsert

Original data size = 414 GB and Hudi data size = 424 GB
After 4 incremental loads, original came around 2100 GB with Snapshot data in each partition and Hudi data size was 547 GB

I tested for another scenario with >1.5 TB with the same process as above

Original = 1.6 TB, Hudi 1.3 TB
After 1 incremental, orig = 2.9 TB and Hudi 2.5 TB

The same data in partition actually doubled for the bigger dataset while it remained the same for the 500 GB dataset. In both case, cleaner.commit: 5.
Hudi works differently for different size of datasets. I initially thought increase in data size would be only for smaller sized tables. Is there anything I'm missing here?
Another thing I noted was for 1.5 TB, bulk_insert into Hudi had only 878 GB for the same number of records while insert overwrite had 1.3 TB. I couldn't figure out the why there was a huge difference in data size. Another observation, after doing bulk_insert, I was not able to perform delete operation on the table.
This is my config.
hudi_upsert_options = {
'hoodie.table.name': 'f_claim_phcy_hudi_cow',
'hoodie.datasource.write.recordkey.field': 'yr_mth,claim_id',
'hoodie.datasource.write.partitionpath.field': 'yr_mth',
'hoodie.datasource.write.table.Type': 'COPY_ON_WRITE',
'hoodie.datasource.write.table.name': 'f_claim_phcy_hudi_cow',
'hoodie.combine.before.upsert': 'true',
'hoodie.datasource.hive_sync.enable': 'true',
'hoodie.datasource.hive_sync.table': 'f_claim_phcy_hudi_cow',
'hoodie.datasource.hive_sync.partition_fields': 'src_sys_nm,yr_mth',
'hoodie.datasource.hive_sync.partition_extractor_class': 'org.apache.hudi.hive.MultiPartKeysValueExtractor',
'hoodie.datasource.write.hive_style_partitioning': 'true',
'hoodie.datasource.hive_sync.database': 'us_commercial_datalake_app_commons_dev',
'hoodie.datasource.hive_sync.support_timestamp': 'true',
'hoodie.datasource.hive_sync.auto_create_db':'false',
'hoodie.datasource.write.keygenerator.class': 'org.apache.hudi.keygen.ComplexKeyGenerator',
'hoodie.datasource.write.row.writer.enable': 'true',
'hoodie.parquet.small.file.limit': '500000000',
'hoodie.parquet.max.file.size': '900000000',
'hoodie.upsert.shuffle.parallelism': '2000',
'hoodie.insert.shuffle.parallelism': '2000',
'hoodie.bulkinsert.shuffle.parallelism': '2000',
'hoodie.delete.shuffle.parallelism': '2000',
'hoodie.bulkinsert.shuffle.parallelism': '2000',
'hoodie.bulkinsert.sort.mode': 'GLOBAL_SORT',
'hoodie.bulkinsert.sort.mode': 'GLOBAL_SORT',
'hoodie.copyonwrite.record.size.estimate': '100',
'hoodie.clean.automatic': 'false',
'hoodie.cleaner.commits.retained': 6,
'hoodie.index.type': 'SIMPLE',
'hoodie.simple.index.update.partition.path':'true',
'hoodie.simple.index.use.caching': 'true',
'hoodie.metadata.enable': 'true'
}
@vinothchandar @n3nash @bvaradar @codope

@mkk1490 : sorry for late turn around. been busy with work.
Few clarifying questions.

What do you mean by incremental loads?

Original data size = 414 GB and Hudi data size = 424 GB
After 4 incremental loads, original came around 2100 GB with Snapshot data in each partition and Hudi data size was 547 GB
I tested for another scenario with >1.5 TB with the same process as above

In this, does incremental load mean, you took your original dataset and made some updates to some of the records and did an upsert to hudi? Or without doing any updates, you ingested into hudi?
Also, is 2100Gb = (414 Gb * 5) i.e one version of original and 4 incremental copies?

also, by Hudi data size, you mean on disk size? (which includes all versions of data) or just the snapshot data size?

Original = 1.6 TB, Hudi 1.3 TB
After 1 incremental, orig = 2.9 TB and Hudi 2.5 TB

This confuses me as to whats incremental. In previous example, I thought you took entire original data and made another copy w/ some updates. but here i see only 1.3Tb added to 1.6Tb. Or in general, incremental means, updates to some records from original snapshot.
Once I get a clarification on these, will respond to your questions.
@codope : will look into the delete issue w/ bulk_insert.

Answers to your questions:

Incremental loads are upsert records. I get a new batch of records to insert as well as some updates to the existing data. In the 400 GB dataset, I have nearly 10 volition records.
for each incremental I would get around 750 mn as new inserts and around 600 mn updates.
Hudi data size  indicates the objects size on s3. That includes are versions of data. 6 commits
Original is the data size of an external table which is currently in use. I’m trying to replicate the existing scenario on a hudi table.
Existing data Size on s3  after IDL: 1.6 TB
Same data size on hudi table after IDL: 1.3 TB

Existing data size on s3 after upsert. The existing process copies the entire data + new data into another partition. Now the total size on disk becomes IDL data size + (IDL +1). This is data replication . This comes to a total of 2.9 TB.
For hudi, I don’t need to replicate the data. I just upsert the incoming records from new batch. This comes to a total of 2.5 TB on s3.  I expected 1.3 TB of IDL data size plus new data size of 500 GB to a total of < 2TB.

ok. let me try to go over how COW works and it might help you understand the increase in data size.
Let's say on first ingest, these are the data files created within hudi. for simplicity, lets assume just 1 partition.
df1_v1: 1Gb
df2_v1: 1Gb
df3_v1: 1Gb
3 data files are created with version 1 and each is 1Gb size.
Now, lets say we we do an incremental load, (inserts + updates). Update records belong just to df1 and df3.
with COW, hudi created newer version for each data file touched. So, final state would be
// old data file versions.
df1_v1
df2_v1
df3_v1
// newer version of existing data files
df1_v2
df3_v2
// new data files for new inserts
df4_v1
Now total size = (df1_v1 + df2_v1, df3_v1, df1_v2, df3_v2, df4_v1).
So, total disk size occupied by hudi is kind of dependent on how updates are applied. For instance, if there are updates to all data files (df1, df2, df3), every new commit will result in 2X the size. But if you have 1000s of data files, only some may get updated. And depending on whether you have small file handling enabled or not, inserts could get bin packed into existing data files or routed to new data files.
Wrt difference between insert_overwrite and bulk_insert w/ save mode as Overwrite is, hudi does cleaning async of the invalid files w/ insert_overwrite. in other words, files are not deleted synchronously.

@mkk1490 I am able to delete after doing bulk insert. Please check this gist where I am deleting 2 records after bulk inserting 10 records: https://gist.github.com/codope/45c8b839fecb4576a563784d3fbe8480
Did you get any error while deleting?

@codope I'm getting a null pointer exception. But i'm able to delete with the same code when I do an insert overwrite. I'm trying to delete all data in 3 partitions from the 60 available partitions with each having 26 GB on disk.
This is my code:
yr_mth_list = [202105, 202103, 202104]
df_l2_rx = spark.read.format("hudi").load(f"{s3_path}/src_sys_nm={src_sys_nm}/")
df_l2_rx is the snapshot data of the table
df_l2_rx_del = df_l2_rx.filter(F.col("yr_mth").isin(yr_mth_list))
df_l2_rx_del .write.format("org.apache.hudi"). options(**hudi_delete_options).
option('hoodie.datasource.write.operation', 'delete').
mode("append").save(f"{s3_path}")
I don't know if it's because of the data size.

I doubt it's because of data size. Are you hitting NPE cnsistently? Can you please share the hudi_delete_options and stacktrace?
I would suggest to close this issue if the main query regarding CoW table size is addressed, and open another issue for delete failure.

I will open a new issue for delete and will share the details there. As for NPE, I did a bulk insert 3 times and got NPE all 3 times. Every time I followed it with insert and didn't get NPE.

@mkk1490 : is there any more info/clarification you need wrt data size in hudi. (based on my response earlier)

@nsivabalan Thanks for the information on how CoW works. I was investigating the updates in my table. I found that updates are spread across all partitions and few million records are getting updated in each of the partition.
I have enabled small file handling and the average size of each part file is 800 MB and I can see for every commit, there is an increase in size.
I also checked the other table where there was no major increase in total size on disk. The reason being updates were not spread  across multiple partitions and were concentrated on a few partitions.
Thanks for all the information. This can be closed.


Visualizations of the results

Hello, thank you for your great work!
I see that in this repository, there are comparisons in terms of visualization. Could you provide the visualization tutorials or scipt on this? Thank you!

Hi,
We leveraged standard matplotlib pyplot for the visualizations based on the results dict to generate the plots, and unfortunately this was done on a notebook file that has since been deleted, so you'd have to leverage pyplot's documentation. I hope this helps.


Add timestamp to restore-dbadatabase output

Request at SQLGrillen - Add the start and end times (or duration) to the restore output
Should be easy enough to add to https://github.com/sqlcollaborative/dbatools/blob/development/functions/Restore-DbaDatabase.ps1#L581

Somewhere around here would be better
https://github.com/sqlcollaborative/dbatools/blob/development/functions/Invoke-DbaAdvancedRestore.ps1#L316
Rob's link is just for WITH RECOVERY ;)
remember that you've often gotten > 1 restores per db, so you'd need to
work out what you actually want to return when (ie; for each restore (full,
diff, log), or adding a wrapper container around all the restores for each
database).
On Thu, 21 Jun 2018 at 12:51 Rob Sewell<EMAIL_ADDRESS>wrote:

Request at SQLGrillen - Add the start and end times (or duration) to the
restore output
Should be easy enough to add to
https://github.com/sqlcollaborative/dbatools/blob/development/functions/Restore-DbaDatabase.ps1#L581
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Tab complete doesn't work with relative paths

When I try to tab complete on a relative path, zsh inserts the full path of the relative path. Examples:
cd ~/
# press tab
cd ~//Users/pzuraq/

cd ../../
# press tab
cd ../..//Users/pzuraq/

It works fine here. I cannot reproduce.

Completely removed prezto and reinstalled, same issue. Any idea how I can troubleshoot?

Issue solved, the home directory was improperly set. It was set to /users/pzuraq instead of /Users/pzuraq and the mismatch between the casing was causing the bug.


feat: Big header <-> Default header transition

resolves #128, #17

Android react-native with react-navigation turns to be a blocker of this feature. I'll check if I can submit a fix on these repos.

Great, I was looking for this, I will see the code

Great, I was looking for this, I will see the code


CFS提供Java的API吗

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
Describe the solution you'd like
A clear and concise description of what you want to happen.
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
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@BelieverDZG
Currently only provide POSIX-compatible file system interface (via mountable FUSE client) and S3 compatible object storage interface (provided by ObjectNode).
We currently have no plans to provide APIs specific to certain development languages like HDFS. Because such APIs are less versatile and do not conform to POSIX semantics.

I found cfsclient (https://github.com/chengyu-l/cfsclient)， it use grpc protocol to connect server.you can also use chubaofs client as local file system ,

@BelieverDZG do you want to use chubaofs by java sdk? it's already supported in latest version


No response in Xamarin.Android

I have a solution with a Xamarin.iOS and a Xamarin.Android project. Both of them have a reference to Hasseware.Net.TMDb.  The class that uses the .Net.TMDb library is in a shared project, which both the iOS and the Droid project also have a reference to.
This work fine in the iOS app, but when I run the Android app (whose functionality is identical to the iOS app), I do not get any response back when I call this function (or any other .Net.TMDb function, for that matter):
public async Task GetMoviesAsync(string query)
{
var movies = await this._client.Movies.SearchAsync(query, "en", true, null, true, 1, new CancellationToken());
return movies;
}
Any idea what can be the problem?

@hrafnl are you using the Nuget package or this repository? what happens exactly (do you get an exception)? can you check if the http call is made (by watching the debug output or using fiddler)?

I was using the NuGet package.  I did not get an exception - the SearchAsync call just "awaited" and in debug mode I never hit a breakpoint on the statement "return movies".
I'm sorry I cannot help with finding out what the problem is.  Tomorrow, I'm starting teaching a class on app development using Xamarin and I have too much to prepare!  I was going to use your library in connection with students' projects, but I found another movie wrapper that works ok for me.


the thing that is supposed to have a providers element isn't defined

TypeError: Cannot read property 'providers' of undefined
at stratify (/Users/erichoffman/Eve/build/src/runtime/builder.js:703:51)
at buildStrata (/Users/erichoffman/Eve/build/src/runtime/builder.js:764:18)
at buildBlock (/Users/erichoffman/Eve/build/src/runtime/builder.js:772:14)
at Object.buildDoc (/Users/erichoffman/Eve/build/src/runtime/builder.js:804:18)
at HTTPRuntimeClient.RuntimeClient.makeEvaluation (/Users/erichoffman/Eve/build/src/runtime/runtimeClient.js:38:29)
at HTTPRuntimeClient.RuntimeClient.load (/Users/erichoffman/Eve/build/src/runtime/runtimeClient.js:28:14)
at /Users/erichoffman/Eve/build/src/runtime/server.js:112:20
at Layer.handle [as handle_request] (/Users/erichoffman/Eve/node_modules/express/lib/router/layer.js:95:5)
at next (/Users/erichoffman/Eve/node_modules/express/lib/router/route.js:131:13)
at Route.dispatch (/Users/erichoffman/Eve/node_modules/express/lib/router/route.js:112:3)

fixed on master


siggraph2016_colorization TORCH7

when i was using the usage of ImageNet Model i got  some errors and i dont know how to solve this problem
/siggraph2016_colorization$ th colorize.lua ansel_colorado_1941.png output_image.png colornet_imagenet.t7
/home/dipendra/torch/install/bin/luajit: /home/dipendra/torch/install/share/lua/5.1/image/init.lua:177: [write_png_file] File output_image.png could not be opened for writing
stack traceback:
[C]: in function 'save'
/home/dipendra/torch/install/share/lua/5.1/image/init.lua:177: in function 'saver'
/home/dipendra/torch/install/share/lua/5.1/image/init.lua:457: in function 'save'
colorize.lua:48: in main chunk
[C]: in function 'dofile'
...ndra/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:150: in main chunk
[C]: at 0x56354bc79560

Are you sure you posted to the right project. I don't find anything called colorize.lua here.

I have downloaded all the file and as well as ImageNet model when
Usage is:
th colorize.lua <input_image> <output_image> colornet_imagenet.t7
and i got this errors
dipendra@dipendra-VirtualBox:~/siggraph2016_colorization$ th colorize.lua ansel_colorado_1941.png output_image.png colornet_imagenet.t7
/home/dipendra/torch/install/bin/luajit: /home/dipendra/torch/install/share/lua/5.1/image/init.lua:177: [write_png_file] File output_image.png could not be opened for writing
stack traceback:
[C]: in function 'save'
/home/dipendra/torch/install/share/lua/5.1/image/init.lua:177: in function 'saver'
/home/dipendra/torch/install/share/lua/5.1/image/init.lua:457: in function 'save'
colorize.lua:48: in main chunk
[C]: in function 'dofile'
...ndra/torch/install/lib/luarocks/rocks/trepl/scm-1/bin/th:150: in main chunk
[C]: at 0x56354bc79560

But this is not siggraph2016_colorization, this is neural_style.


Use consistent-env instead of consistent-path

We will not just be figuring out the PATH but all the tokens of keys or configurations the user might have set for applications in their rc files

LGTM, pending build success :wink:.


Provide a way to link a tutorial from the index

When building, I had tried adding @{tutorial tutorialName} into the index.md file. However, it was not process into a link to the tutorial.
Can I get that implemented? Thanks.

I believe this is already implemented. The correct syntax is {@tutorial tutorialName}.


Add Authentication with JWTs

Coverage decreased (-0.4%) to 92.424% when pulling e7500ed11d6a0e9a903c75758bb41c83bc7cc2f4 on authentication into 265cea0f4ebe88e3e41dab9c0852c4c7940d5754 on master.

Coverage decreased (-2.07%) to 90.789% when pulling 72efe8c1e75c313a10e038c6a71b6add765a0fb9 on authentication into 265cea0f4ebe88e3e41dab9c0852c4c7940d5754 on master.

Coverage decreased (-2.9%) to 90.0% when pulling 6d30a884f63489e284193fb381dc69d38cb9071f on authentication into 265cea0f4ebe88e3e41dab9c0852c4c7940d5754 on master.