replace redirect with case-insensitive routing

👋 Loving this project so far!
I'm switching an app over to it to see how it goes and I noticed that Bud normalizes paths to lowercase. This is a problem for my app because it uses base64-encoded digests to route to content-addressed objects. I could switch to a case-insensitive database lookup, but that introduces the admittedly low possibility of collisions.
I've seen other websites in the wild that use case sensitive routes, for example url shorteners, so I don't think this is too unusual.
This PR removes the redirect and instead changes the router to use a case-insensitive match, since I figure the goal is for URLs to be case-insensitive. I'm not too opinionated here, just wanted to get a PR out to spark discussion. :)
Another option could be to convert casing for only the static portions of the path based on the route, but that's a bigger lift.
Thanks for making Bud!

Thrilled to hear Alex! It's so cool seeing Bass Loop using Bud. Bass also looks awesome. Looks like you're bringing the simplicity of functional programming to deploying infrastructure!

This is a problem for my app because it uses base64-encoded digests to route to content-addressed objects. I could switch to a case-insensitive database lookup, but that introduces the admittedly low possibility of collisions.

Ah, I can totally see the problem. Something like: TUlUIExpY2Vuc2UKCkNvcHl gets redirected to tuluiexpy2vuc2ukcknvchl.

This PR removes the redirect and instead changes the router to use a case-insensitive match, since I figure the goal is for URLs to be case-insensitive. I'm not too opinionated here, just wanted to get a PR out to spark discussion. :)

Thanks for opening this PR! I originally did this intentionally for SEO purposes, so https://github.com/livebud/bud and https://github.com/livebud/BUD wouldn't be treated as different routes in your analytics dashboards.
I had a look at what Github does and I think I like their approach:

They are case-insensitive, so curl https://github.com/livebud/bud and curl https://github.com/livebud/BUD render the same HTML.
Both HTML responses include <link rel="canonical" href="https://github.com/livebud/bud" /> in their <head> to say that the lowercase version is the canonical route.

So I think your PR makes sense once the tests pass!
If you feel like adding 2., you can adjust the default layout in this file. I'm not sure we're passing enough context to the views yet to provide a full URL like that, so this could be a follow-up task once I revisit views for layouts, error pages, etc.

Thanks. :)

2. Both HTML responses include <link rel="canonical" href="https://github.com/livebud/bud" /> in their <head> to say that the lowercase version is the canonical route.

Cool, that makes sense.

So I think your PR makes sense once the tests pass!

Great! I got the tests passing, but I'm not sure of my approach. There were a few places that iterated over bytes, not runes. The "α" ("\xce\xb1") route would be inserted fine, but then inserting "β" ("\xce\xb2") would see"\xce" as a common prefix and set "α" and "β" as children of path:"\xce" in the routing tree. This somehow led to /β being returned for requests to /α.
So I changed Tokens to operate on runes rather than bytes, which affects Size, At, and Split. Took a while to figure out!
I'm interested in doing 2., but pushing just these changes for now; I'll try to find time to do it soon, so feel free to wait or merge as-is (if they actually pass in CI).


Implicit tracing for CDI

At the moment CDI beans are traced by adding @Traced annotation. I think we could provide a way to enable automatic tracing. It issue might be that there would be too many CDI beans e.g. from the frameworks and container so we should think how to scope it down. For example trace only beans from the app package. Or trace beans matching specific package name.

Would the beans only be traced if there was already an active span? Or could they also start a new trace?


CombinedLinear Gaussian Transition Model

One issue that we noticed is regarding the CombinedLinearGaussianTransitionModel.
For example looking at the metric example we have a KalmanPredictor. This has the following property:
 transition_model: LinearGaussianTransitionModel = Property(         doc="The transition model to be used.")
In the Example the transition model chosen is CombinedLinearGaussianTransitionModel.
Looking at the code the class is the following:
class CombinedLinearGaussianTransitionModel(LinearModel, _CombinedGaussianTransitionModel):
So the type is not LinearGaussianModel and neither are _CombinedGaussianTransitionModel(TransitionModel, GaussianModel): and class LinearModel(Model):
Because the UInterface uses the parents and children classes to give the opportunity to choose the class, in our case is not possible to select CombinedLinearGaussianTransitionModel as property of the KalmanPredictor.
Maybe class CombinedLinearGaussianTransitionModel(LinearModel, _CombinedGaussianTransitionModel) should have LinearGaussianTransitionModel  as parent class?
We can't see the link between KalmanPredictor and CombinedLinearGaussianTransitionModel

The current model inheritance hierarchy certainly isn't clear. A quick fix to your issue might be to register CombinedLineaerGaussianTransitionModel as a subclass of LinearGaussianTransitionModel.
For an example of subclass registering, see: https://github.com/dstl/Stone-Soup/blob/0cc1eabd4ba525f55970e7bf41416dab663bbefe/stonesoup/types/state.py#L472
By registering as a subclass, the class will be inserted in to the inheritance hierarchy without the need to inherit the superclass' attributes and methods.


auth: Improve credentials management

Currently, if the users didn't log in using az, they will need to re-auth on each command run. We improve this by using tokenCache to save the credentials locally. The implementation uses cache.ExportReplace allowing saving RefrestToken as well so user stays logged in for longer intervals as well. az login follows the same approach as well (you can compare ~/.azure/msal_token_cache.json vs ~/.kubectl-az/token-cache.json ). Also, we keep AzureCLICredential in chain to keep supporting az login auth.
Fixes #2
Testing done
$ az logout
# you should be asked to authenticate via browser
$ ./kubectl-az check-apiserver-connectivity --node aks-agentpool-77471288-vmss000000
# running the command again works w/o auth for this PR
$ ./kubectl-az check-apiserver-connectivity --node aks-agentpool-77471288-vmss000000

Thanks for the reviews!


mate.libmateweather: 1.26.1 -> 1.26.2

Description of changes
https://github.com/mate-desktop/libmateweather/compare/v1.26.1...v1.26.2
Things done

Built on platform(s)

[x] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

For non-Linux: Is sandboxing enabled in nix.conf? (See Nix manual)

[ ] sandbox = relaxed
[ ] sandbox = true

[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[x] Tested basic functionality of all binary files (usually in ./result/bin/)
23.11 Release Notes (or backporting 23.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[x] Fits CONTRIBUTING.md.

With glib-networking I can get weather info for the first time using the mateweather-applet

Also moves stuff to propagated since they are in Requires of mateweather.pc.
Bot backport won't eval since 0e0b2fb549c02a48c29c3ad72a3b1e59db0a23ed is missing on 23.05.

Result of nixpkgs-review pr 262496 run on x86_64-linux 1

40 packages built:

blueberry
cinnamon.cinnamon-common
cinnamon.cinnamon-gsettings-overrides
cinnamon.cinnamon-screensaver
cinnamon.cinnamon-session
cinnamon.nemo
cinnamon.nemo-fileroller
cinnamon.nemo-python
cinnamon.nemo-with-extensions
cinnamon.nemo.dev
cinnamon.pix
cinnamon.warpinator
cinnamon.xapp
cinnamon.xapp.dev
cinnamon.xreader
cinnamon.xviewer
hypnotix
lightdm-slick-greeter
mate.libmateweather
mate.mate-applets
mate.mate-indicator-applet
mate.mate-media
mate.mate-netbook
mate.mate-notification-daemon
mate.mate-panel
mate.mate-power-manager
mate.mate-screensaver
mate.mate-sensors-applet
mate.mate-tweak
mate.mate-tweak.dist
mate.mate-utils
python310Packages.xapp
python311Packages.xapp
sticky
timeshift
timeshift-minimal
timeshift-unwrapped
xed-editor
xmonad_log_applet_mate
xplayer


TC-SC-4.1 Need YAML support to enable Extended Discovery

Summary:
As per testplan [TC-SC-4.1] need YAML support to enable Extended discovery for DNS advertisings
Testplan screenshot:

I don't understand what this YAML support would do.  Extended discovery needs to be enabled on the actual DUT, no?
@cjandhyala

@bzbarsky-apple its not related to yaml can you please close this issue

@manjunath-grl Sure thing.


NanoAssaultNeo_Resolution

Game: Nano Assault Neo (All Version)
Cemu Graphic Packs: Resolution
Tested: Cemu v1.4.0c
Description: Put below file into folder  Cemu\graphicPacks\NanoAssaultNeo_Resolution
rules.txt
Code (rules.txt):
[Definition]
titleIds =<PHONE_NUMBER>110100,0005000010110600,0005000E10110100,0005000E10110600
name = "Resoluton"
path = "Nano Assault Neo/Graphics/Resolution"
description = Changes the games resolution.
version = 3

[Preset]
name = 1280x720 (Default)
$width = 1280
$height = 720
$gameWidth = 1280
$gameHeight = 720

// Performance

[Preset]
name = 256x144
$width = 256
$height = 144
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 427x240
$width = 427
$height = 240
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 640x360
$width = 640
$height = 360
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 854x480
$width = 854
$height = 480
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 960x540
$width = 960
$height = 540
$gameWidth = 1280
$gameHeight = 720

// Quality

[Preset]
name = 1600x900
$width = 1600
$height = 900
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 1920x1080
$width = 1920
$height = 1080
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 2560x1440
$width = 2560
$height = 1440
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 2732x1536
$width = 2732
$height = 1536
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 3200x1800
$width = 3200
$height = 1800
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 3840x2160
$width = 3840
$height = 2160
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 5120x2880
$width = 5120
$height = 2880
$gameWidth = 1280
$gameHeight = 720

// Enthusiast

[Preset]
name = 7680x4320
$width = 7680
$height = 4320
$gameWidth = 1280
$gameHeight = 720

[Preset]
name = 10240x5760
$width = 10240
$height = 5760
$gameWidth = 1280
$gameHeight = 720

[TextureRedefine] # Game Resolution
width = 1280
height = 720
overwriteWidth = ($width / $gameWidth) * 1280
overwriteHeight = ($height / $gameHeight) * 720

I am not against the idea but I don't know how that can be accomplished because the thing about mass generation of all none covered games, is their title ids. That would have to be manual.
And in other news, crementif is working on automating the whole generation of the packs. Like it use to. So I suppose that is similar.

Nope. I was and am still working on a new build method that would allow for filling in missing resolutions in existing graphic packs by users themselves so that we can get rid of users asking for resolutions.
I'm not very fond of the "see what sticks" pack generation, that's exactly what BatchFW tries to do and it doesn't work very well in any of the cases. https://github.com/slashiee/cemu_graphic_packs/issues/242#issuecomment-435869375
Maybe later on, I guess.


Help implementing

Hi, I was wondering how to implement Vue-redactor in a already set vue element, would this be ok? thanks for the help
new Vue({
  el: '#app',
  data: {
     something_else: true,
     content: '
Hello and welcome
',
     configOptions: {
           plugins: ['table']
     }
  },
  methods: {
  }
})

Please provide the html for the page that you are trying to enable vue-redactor on.
This package adds a global component to Vue that lets you call <Redactor v-model="content" :config="configOptions" /> from anywhere in your DOM.
If you are asking about how to add something_else to the component, you can do something like this...
<Redactor v-model="content" :config="configOptions" :another-prop="something_else" />

Hi Devin, this works great, I finally bought redactor and Im very happy, thank you, I got some notes hope you consider for a future version

Target in links modal, so it can be selected by user (like in edit image: “Open link in new tab”)
Is there a way to make the toolbarFixed dark mode like the air version?
In edit images, why not put max width/height and automatically set width to 100% (mobile first)
is there a way to upload images using an Ajax request so the server can resize, watermark , etc the images and then return the url to redactor and maybe refresh images.json list
is there a way to stop drag toolbar icon? it happens a lot and it inserts the script url to the content

Thanks Devin, excellent wysiwyg editor

@nam-co I didn't create Redactor. The credit goes to @imperavi. However, I will try to answer your questions.

Target in links modal, so it can be selected by user (like in edit image: “Open link in new tab”)
Is there a way to make the toolbarFixed dark mode like the air version?
In edit images, why not put max width/height and automatically set width to 100% (mobile first)

You can submit feature requests in the support page while logged in.

is there a way to refresh images.json list
is there a way to stop drag toolbar icon? it happens a lot and it inserts the script url to the content

If you want to go into more detail I might be able to help, but otherwise you can use the same support form above for any assistance with Redactor. 😄

Hi @web3devin , sorry I didn't notice this wasn't from imperavi , thanks for the implementation
Devin Im trying to use it on laravel with something like:

but when I submit this inside a form, the request comes empty (content[desc][es]), any ideas why?
Thanks

@nam-co
Would you be able to provide more information on how you are using this package and attempting to post the form?
It should work using either the 1 way data binding example in this repo. For instance:
<Redactor v-model="desc_es" name="content[desc][es]"></Redactor>


[WIP] 616

Fixes #616

[?] npm run test succeeds.
[x] npm run lint succeeds.
[ ] Appropriate changes to README are included in PR.

@grant Not sure why is crashed on Node 8 tests.
Still, this PR is more so that you can judge and comment the design principle.
new files:

pathproxy.ts the base class to handle reference to config file (file doesn't have to exist, if path points to a folder then default filename is appended, etc.)
conf.ts a singleton to manage the pathproxy configuration files (replacing the DOTobject)

The other changes are mostly switching for DOT use to Conf. Handling of auth as being either local or global can be tricky but should be fine.
Pending your feedback (take your time) I'll make the requested changes and add specific tests.

@grant approved?

Oops. Didn't mean to approve. Just the commander change looked okay.
Looking for a smaller PR.

This PR is not meant to be merged as is. But for you to "preview" what I have in mind and give directions.
I know it will be a rather large PR (unless you choose small kludges & patches) :P

Do you want me to open a cleanup PR with the package updates (commander) and the drop of pre node 8 poly fill?

Please create smaller PRs that only do 1 thing.
Like bump commander.
Let's continue conversation in an issue or new small PR.


Add backwards search to preferences view

This patch allows shift+f to search backwards in the preferences search.

@hoovercj,
Thanks for your contribution as a Microsoft full-time employee or intern. You do not need to sign a CLA.
Thanks,
Microsoft Pull Request Bot

Addresses #22497

@hoovercj Thanks for the PR. I will look into it and get back to you. Thanks.

Thanks for the PR.
LGTM.
Merged


Deployment Error

Your local environment details:
Node version (node -v): [v16.13.1]
NPM version (npm -v) [8.3.0]
SFDX version (sfdx -v) [sfdx-cli/7.132.0 win32-x64 ]
Your remote environment details:
Salesforce B2C Commerce version: [ 21.3]

Error occur while deploy. command:1. npm run crm-sync:sf:org:deploy  2.sfdx force:source:deploy -p "./src/sfdc/base"

Hi @26shivani02 , as noted in the error message, the sharing model of private for account is not consistent with opportunities. You can adjust the code to match (or simply omit) your sharing model you need or change your sharing model. I'm assuming Accounts are public given this error.


Return the number of differences

Hi @neighborhood999 ,
Would it be possible to return these values?

        <ReactGhLikeDiff
          options={{
            originalFileName: TITLE,
            updatedFileName: TITLE,
          }}
          past={this.state.past}
          current={this.state.current}
          diff={({remove,add}) => console.log(remove, add)}
        />

@neighborhood999 : Are there any news?

@neighborhood999 : Are there any news?


Timex.day_name incompatible with Timex.days_to_beginning_of_week

Steps to reproduce

Call Timex.day_name(Timex.days_to_beginning_of_week(~U[2021-04-11 00:00:00Z], :sun)) (You can replace the date with any date that falls on a Sunday)

Description of issue
Expected Result:
Sunday

Actual Result:
{:error, :invalid_weekday_number}

What's happening?

Timex.days_to_beginning_of_week(~U[2021-04-11 00:00:00Z], :sun) returns 0 as the date is a Sunday.
Timex.day_name/1, however, expects day_num to be in 1..7, thus the error.

Same behaviour happens if Timex.day_name(Timex.days_to_beginning_of_week(date)) is called where date is a Monday (for example, ~U[2021-04-12 00:00:00Z]).
Given than both are from the same library, I'd expect these functions to be compatible with each other. The issue is that Timex.days_to_beginning_of_week always returns a result in 0..6 and Timex.day_name expects an argument in 1..7.
Work around
I have to call Timex.day_name(Timex.days_to_beginning_of_week(date) + 1) to get the expected day of the week.
Potential fix
Maybe we could add a flag to Timex.day_name to accept an argument in 0..6?

Just learnt about weekday from reading through the issues and using weekday solves this issue.


Binary downloads

One of this repository's proposed benefits as written in the readme: "Reflex has no dependencies. No need to install Ruby or anything like that." Yet the instillation reads:
$ go get github.com/cespare/reflex

I don't want to install go to use this library. Could this dependency be removed with binary downloads?

The README also says

TODO: provide compiled downloads for linux/darwin amd64.

But I've never gotten around to it, mostly because I have no need for this. Do you have a suggested method? I've considered using Bintray.

GitHub releases are preferable as that's where I generally check first.

Ah, I forgot that GH releases can included binaries. Good idea.

@calebmer just uploaded some to my fork. compiled them with gox.
https://github.com/cescoferraro/reflex/releases/tag/v0.1.0
@cespare go get its not cacheble inside a Dockerfile there is a actual need for them on this repo

I would consider using https://github.com/goreleaser/goreleaser
It's quite awesome and integrates nicely into the CI workflow.

Here's a sample goreleaser config that would work well for this repo:
build:
  main: .
  binary: reflex
  goos:
    - darwin
    - linux
archive:
  replacements:
    amd64: 64-bit
    386: 32-bit
    darwin: MacOS
    linux: Linux
  files:
    - README.md
    - LICENSE

You can install goreleaser on your system with brew install goreleaser/tap/goreleaser or a manual download from https://github.com/goreleaser/goreleaser/releases.
Once you do that, you can run the following workflow:
export GITHUB_TOKEN=`YOUR_TOKEN` # Get this at https://github.com/settings/tokens
git tag -a v1.2.3 -m "your release message"
git push origin --tags
goreleaser

There is also Travis Integration.

This would be very much appreciated by many users who don't have the full go toolkit installed. I'm sure @sagikazarmark would be happy to answer any questions, as am I.

I've opened a PR https://github.com/cespare/reflex/pull/80 that should totally address the concerns of this issue.

OK, releases have binaries attached to them now.


Is bb_detected_in_front_of_vehicle in sensor_agent.py be used?

Hello, I wondering if  bb_detected_in_front_of_vehicle is used in sensor_agent.py. If not, the agent is totally controled by the model output, not considering the red light and vehicle bbox detected by ther model, is it so?
I found some red light infraction and vehicle collison of my reproduced model.
Thank you.

The function bb_detected_in_front_of_vehicle is not used. It's a leftover from the transfuser repository where it was used for the latentTF model to replace the LiDAR safety check.
Yes the red light and vehicle bounding box detections are not used during inference.
The stop sign bounding boxes are optionally used, see here.


CI/CD building apps with dependencies error "Property "AppId" cannot be found."

Hi! I am trying to follow the AL-Go workshop (https://github.com/microsoft/AL-Go/blob/main/Workshop/Index.md), but I'm encountering an error when attempting to run the CI/CD pipeline on a repo with multiple projects and dependencies between apps using packages to resolve dependencies.
The repo 'MySolution' has the apps 'W1', 'DK', and 'US'. 'W1' has a dependency to app 'Licensing' in repo 'Common'. The apps 'DK' and 'US' are dependant on 'W1'.
The app 'W1' builds using the deployed packages from repo 'Common', but the apps 'DK' and 'US' fail with error message "Property "AppId" cannot be found."
Here is the full output from the log,
Log.txt

I did run into this bug myself last week - and will have a fix ready one of the next days.

Just had a look - the issue is actually in BcContainerHelper and a new version has just been released (6.0.1), so your pipelines should work now when they discover the new version (this can take hours though)
If you want to expedite this, you can add a setting to the org settings variable called BcContainerHelperVersion and set it to preview - then it should work right away.

Thanks, it's working as expected now. Btw, I have been looking for documentation on all of the different settings in the AL-Go-Settings.json. Is this available anywhere? Thanks again

https://aka.ms/algosettings is reference for all settings


82439 dev price information validation

Added validations for unit of sale price information.
Added unit test cases.
Moved Models and Services folder to common for reuse in price change webjob

Reviewed FT and Looks good. @Sadha1501493 some of the checks have failed, could you please have a look, thanks

@RaviK2233 : Checks are passing now. Please approve..


feat(bedrock): support metrics for bedrock

[x] I have added tests that cover my changes.
[ ] If adding a new instrumentation or changing an existing one, I've added screenshots from some observability platform showing the change.
[x] PR name follows conventional commits format: feat(instrumentation): ... or fix(instrumentation): ....
[ ] (If applicable) I have updated the documentation accordingly.

@nirga Could you please advise why I always get the following error, even though I tried changing the model ID? Thanks.
https://github.com/traceloop/openllmetry/actions/runs/10912918948/job/30288462269?pr=1957
botocore.errorfactory.AccessDeniedException: An error occurred (AccessDeniedException) when calling the InvokeModel operation: You don't have access to the model with the specified model ID.    cc @gyliu513

I already know the root cause why I always getting the error botocore.errorfactory.AccessDeniedException: An error occurred (AccessDeniedException) when calling the InvokeModel operation: You don't have access to the model with the specified model ID.. Thanks.

/lgtm
@nirga can you help review? Thanks

@nirga Do you have more comments? Thanks.


Fix #18908: Add stdClass as possible return type to getBodyParams

Q
A

Is bugfix?
❌

New feature?
❌

Breaks BC?
❌

Tests pass?
✔

Fixed issues
#18908

Closes #18908

Thanks.


inform when the task is completed

main thread hangs until portMAX_DELAY expires, causing the program to stop responding when the upload task fails

I don't want to use goto.

Changed xQueueSend to xTaskNotify.


Add installation instructions to README.md

Include instructions for downloading the binary and for compiling with
Go.

Thanks @mgibson323


Allow use of accept headers in rpc requests

things to do before completing this pr:

[ ] verify this doesn't break existing rpc calls
[ ] verify setting this header actually works

[ ] verify we are able to programmatically set the header, not sure if possible atm


"RangeError: Unsupported time zone specified undefined" after npm start

C:\Users\abelr\WebstormProjects>npx create-react-app todolist1 --use-npm
Creating a new React app in C:\Users\abelr\WebstormProjects\todolist1.
Installing packages. This might take a couple of minutes.
Installing react, react-dom, and react-scripts...

<EMAIL_ADDRESS>postinstall C:\Users\abelr\WebstormProjects\todolist1\node_modules\babel-runtime\node_modules\core-js
node scripts/postinstall || echo "ignore"

<EMAIL_ADDRESS>postinstall C:\Users\abelr\WebstormProjects\todolist1\node_modules\core-js
node scripts/postinstall || echo "ignore"

<EMAIL_ADDRESS><EMAIL_ADDRESS><EMAIL_ADDRESS>added 1441 packages from 686 contributors and audited 904901 packages in 265.658s
found 0 vulnerabilities

Initialized a git repository.
Success! Created todolist1 at C:\Users\abelr\WebstormProjects\todolist1
Inside that directory, you can run several commands:
npm start
Starts the development server.
npm run build
Bundles the app into static files for production.
npm test
Starts the test runner.
npm run eject
Removes this tool and copies build dependencies, configuration files
and scripts into the app directory. If you do this, you can’t go back!
We suggest that you begin by typing:
cd todolist1
npm start
Happy hacking!
C:\Users\abelr\WebstormProjects>cd todolist1
C:\Users\abelr\WebstormProjects\todolist1>npm start

<EMAIL_ADDRESS>start C:\Users\abelr\WebstormProjects\todolist1
react-scripts start
Starting the development server...
Compiled successfully!

You can now view todolist1 in the browser.
Local:            http://localhost:3000/
On Your Network:  http://<IP_ADDRESS>:3000/
Note that the development build is not optimized.
To create a production build, use npm run build.
C:\Users\abelr\WebstormProjects\todolist1\node_modules\webpack\lib\Stats.js:979
builtAtDate.toLocaleDateString(undefined, {
^
RangeError: Unsupported time zone specified undefined
at new DateTimeFormat (native)
at Date.toLocaleDateString (native)
at Function.jsonToString (C:\Users\abelr\WebstormProjects\todolist1\node_modules\webpack\lib\Stats.js:979:17)
at Stats.toString (C:\Users\abelr\WebstormProjects\todolist1\node_modules\webpack\lib\Stats.js:859:16)
at Object.reporter (C:\Users\abelr\WebstormProjects\todolist1\node_modules\webpack-dev-middleware\lib\reporter.js:8:31)
at process.nextTick (C:\Users\abelr\WebstormProjects\todolist1\node_modules\webpack-dev-middleware\lib\context.js:42:23)
at process._tickCallback (internal/process/next_tick.js:61:11)
npm ERR! code ELIFECYCLE
npm ERR! errno 1
npm ERR<EMAIL_ADDRESS>start: react-scripts start
npm ERR! Exit status 1
npm ERR!
npm ERR! Failed at the<EMAIL_ADDRESS>start script.
npm ERR! This is probably not a problem with npm. There is likely additional logging output above.
npm ERR!      C:\Users\abelr\AppData\Roaming\npm-cache_logs\2019-10-05T01_45_07_525Z-debug.log
C:\Users\abelr\WebstormProjects\todolist1>

Interestingly this seems to be a Chrome bug where the local timezone is not being recognized (see for example https://github.com/GoogleChrome/lighthouse/issues/1056). This issue should be probably filed to webpack repo so the Stats module can account for timezone issues.

@abel406 to fix this issue, either update your NodeJS version to 12 or run the command with for example TZ=Europe/Helsinki npm start


pip install is broken

when running pip install ocio-lut-prescription it doesn't download certain required files such as the following:
./ui/main_window.ui
./ui/icon.png
./ui/resource.qrc
Due to main_window.ui not being downloaded during the pip install process, the python application errors out

Hi @kangstarr
Thanks for letting me know, and giving me details about the issue.
Let me come back to you as soon as possible,
JF

hi @kangstarr
Thanks for the wait and patience, I fixed this issue.
JF


Need help with minification

I get token errors on using a minifier. Can anybody please help?

@TauseefMalik yes! It's because the selection.js script uses es6, which isn't compatible with a lot of minification tools (which use the standard es2015, or es5). You should be able to find it soon with
<script src="https://unpkg.com/selectionjs"></script>

To automatically get a minified version in your projects.


Decorator interface for registering processing funcs?

What's your opinion on a using decorators to register processing functions?
It would eliminate the whole needing to have the -f fixer:add_header explicit syntax. Instead you just point to a module and the decorated funcs are auto loaded.
Also the requirement that the module is on the python path could be avoided by a simple import of the file directly
Whatcha think?

I agree, the -f fixer:add_header is a little cryptic, one needs to remember the syntax and I seem to forget every time.
So if I understand correctly, you propose to pass just a python file like -f path/to/fixer.py that would get loaded (wherever it is) and then use some magic decorator like say @massedit to let the script know about the program.
I'd like to keep the backward compatibility with -f fixer at least (provided fixer is in $PYTHONPATH, but yeah, sounds like a good idea.

Yes exactly. Personally I'd go with a api something like,
@massedit.processor
def my_processing_func(lines, path):
    for line in lines:
        ...

This lets you then do verification at import time with inspect:

verify the function signature args
verify that the processor is a generator

I can offer up a PR if you'd like.

Yeah, that sounds good. I was hoping you'd offer :-)

So I took a different approach and created an option --generate to generate a template fixer.py file.
I found that most of the time the issue was not so much what function I should tell massedit.py to call (I had just created it) but what the callback should look like in the first place.
565bbd3fd46449884f4426ded6cc92f35eb3823a should fix that problem and allow the user to quickly see how to use massedit.


Futures should play nicer with pattern matching

So as a newcomer to future-rs, I had a hard time wrapping my brain around why I couldn't build a decision tree based off of futures.
My intuitive approach was as follows:
    let routine = match predicate {
        //result can be obtained synchronously
        Ok(x) => future::ok(x),
        Err(_) => {
            //we need to asynchronously obtain the value instead
            let x = async_funcction()
                .map(|x| some_transform)
                .map_err(|err| println!("Failure in async value obtain! {:?}", err))
        }
    }
    .and_then(|final_value| {
        //we have obtained the value either synchronously or asynchronously
        //now do something asynchronous with it
        ....
    });

This obviously doesn't work, because the match arms have different types. Does rust offer an ergonomic solution to this problem that could be adopted?

Thanks for the report! Unfortunately there's not a great solution to this today. On stable you can use Box<Future> or if you know there's exactly two branches you can use the Either type in this crate. On nightly though we'll soon have #[async] and await! which should make this much nicer!

Thanks, @alexcrichton. I'm excited to rust coming one step closer to full-fledged, hopefully-someday-native async/await support; the linked document looks like a good start!

Oh, and as to my initial question: as soon as I realized I was barking up the wrong tree, I was able to use futures::future::result (I wish it were named from_result to be more consistent with the rust api) to basically deconstruct the predicate into map and map_err as my two cases, then continue on my merry way.

Ok great! In that case I think I'll close this for now.
Right now result is intended to mirror the ok and err apis to create the "noop" future where it just matches the name of what it returns.


[BUG] :bug: Object classes are lost when updating a realm on ldap store

should be fixed by https://github.com/InseeFr/sugoi-api/pull/620/files


Support quantised SQRT operator in TFLite

Supoort SQRT quantization operator convertion as a part of tasks from issue #9187
cc @leandron

@leandron I have rebase the code and pass the CI, please take a look.

This is merged now, thanks @elinx, @lhutton1 and @ophirfrish!


HDDS-10413. Recon - UnsupportedOperationException while merging Incremental Container Reports.

What changes were proposed in this pull request?
This PR fixes the UnsupportedOperationException while merging Incremental Container Reports.
Recon processes the Incremental Container Reports (ICRs) being sent from datanodes and to improve performance and process multiple ICRs in a heartbeat,  HDDS-9883 merged multiple ICRs from datanodes into a single report before sending to Recon ICR handler (ReconIncrementalContainerReportHandler) where it handles such merged container reports , but merge operation was throwing UnsupportedOperationException while merging ICRs. This PR fixes the issue and handles the merge operation correctly.
What is the link to the Apache JIRA
https://issues.apache.org/jira/browse/HDDS-10413
How was this patch tested?
This patch was tested manually by adding new org.apache.hadoop.ozone.recon.scm.TestReconIncrementalContainerReportHandler#testMergeMultipleICRs.

@jojochuang @sumitagrawl Pls review.

Merged. Thanks @devmadhuu


[NFC] Python Lint: Fix E275(missing whitespace after keyword) issues.

There are E275(missing whitespace after keyword) issues with current python scripts.
This PR fixes them.

@swift-ci Please Python lint

@swift-ci Please smoke test and merge

@swift-ci Please smoke test Linux platform


seafile-client: 6.2.1 -> 6.2.2

Motivation for this change
Things done

[x] Tested using sandboxing (nix.useSandbox on NixOS, or option sandbox in nix.conf on non-NixOS)
Built on platform(s)

[x] NixOS
[ ] macOS
[ ] other Linux distributions

[ ] Tested via one or more NixOS test(s) if existing and applicable for the change (look inside nixos/tests)
[ ] Tested compilation of all pkgs that depend on this change using nix-shell -p nox --run "nox-review wip"
[x] Tested execution of all binary files (usually in ./result/bin/)
[ ] Determined the impact on package closure size (by running nix path-info -S before and after)
[x] Fits CONTRIBUTING.md.

Success on x86_64-linux (full log)
Attempted: seafile-client, seafile-shared
Partial log (click to expand)
shrinking RPATHs of ELF executables and libraries in /nix/store/0s31nrw27spimyzxvl7kcg5n0k497pqm-seafile-client-6.2.2
shrinking /nix/store/0s31nrw27spimyzxvl7kcg5n0k497pqm-seafile-client-6.2.2/bin/.seafile-applet-wrapped
strip is /nix/store/4qvrxzxa535y8304mk195x50b6p9607d-binutils-2.30/bin/strip
stripping (with command strip and flags -S) in /nix/store/0s31nrw27spimyzxvl7kcg5n0k497pqm-seafile-client-6.2.2/bin
patching script interpreter paths in /nix/store/0s31nrw27spimyzxvl7kcg5n0k497pqm-seafile-client-6.2.2
checking for references to /tmp/nix-build-seafile-client-6.2.2.drv-0 in /nix/store/0s31nrw27spimyzxvl7kcg5n0k497pqm-seafile-client-6.2.2...
postPatchMkspecs
postPatchMkspecs
/nix/store/0s31nrw27spimyzxvl7kcg5n0k497pqm-seafile-client-6.2.2
/nix/store/db9sqdyjf3lhyrxkwvxgddyhx08c0i29-seafile-shared-6.2.2

Failure on aarch64-linux (full log)
Attempted: seafile-client, seafile-shared
Partial log (click to expand)
[7299/16620] CXX obj/skia/skia/SkSwizzle.o
[7300/16620] CXX obj/skia/skia/SkStream.o
[7301/16620] CXX obj/third_party/webrtc/pc/peerconnection/webrtcsessiondescriptionfactory.o
[7302/16620] CXX obj/third_party/webrtc/rtc_base/rtc_base_generic/ifaddrs_converter.o
[7303/16620] CXX obj/skia/skia/SkTime.o
[7304/16620] CXX obj/skia/skia/SkVertState.o
[7305/16620] CXX obj/skia/skia/SkTypeface.o
building of '/nix/store/9xhc0p79i75c1qbaf4mi9wz78b3x209c-qtwebengine-5.11.1.drv' timed out after 3600 seconds
cannot build derivation '/nix/store/1rscc9z22cbwgmcgid1fhxax01iiv9jn-seafile-client-6.2.2.drv': 1 dependencies couldn't be built
error: build of '/nix/store/1rscc9z22cbwgmcgid1fhxax01iiv9jn-seafile-client-6.2.2.drv' failed


[Feature Request] Plugin available for Mac users

It would be nice to have this plugin also available for Mac OS users of Stream Deck. 👍

I think it should not be a big issue. We just need one test guinea pig that would try the app on it and we are good to go.
Currently the manifest file has only these as supported OS's:
"OS": [
{
"Platform": "windows",
"MinimumVersion": "10"
}
]
but adding the mac os should bring it available. @nansravn do you have mac that you could test with?
{
"Platform": "mac",
"MinimumVersion" : "10.11"
},

@panuoksala Yes, I do have. I can help testing the app on my Mac.
I've just reviewed the manifest.json file, and I've seen this line:
"CodePath": "StreamDeckAzureDevOps.exe"

An .exe wouldn't work on a Mac OS, is this line a problem?
By now I've just installed plugins directly from the Stream Deck Store. What should I do to test this project on my Mac? Do you have any docs for sharing?
I'm totally new to Strem Deck, so I don't know anything about the conventions for developing a Stream Deck plugin.

I will provide you the Mac compatible version and details how to install it.

This version has now MacOS as supported OS, can you install the plugin directly with this file?
https://1drv.ms/u/s!Ap4gpegjXAK1iYQ-MPAXBKWegE1cDA?e=DmKVzo
The file is .streamDeckPlugin so I think it should also work in Mac too?

Were you able to install the plugin from provided file?

I was able to install the plugin, but it isn't working to trigger my pipeline. It doesn't appear any error message, but on my stream deck it appears a yellow triangle with a ! in the middle.
How can I help you debugging this issue?

I'm not sure I'm using the correct value for the Definition ID parameter. Here's the url that appears when I'm editing my build pipeline YAML from the Az DevOps interface:
https://dev.azure.com/revilasn/MLOps/_apps/hub/ms.vss-build-web.ci-designer-hub?pipelineId=22&nonce=DcEqv2w7sAp1xu6ptET9Mg%3D%3D&branch=master
Is my Definition ID 22?

Yes that is correct. Does your PAT token has required permissions?
Renan Novas @.***> kirjoitti 5.1.2022 kello 22.02:

[Screen Shot 2022-01-05 at 16 00 26]https://user-images.githubusercontent.com/9952451/148280631-03232fcb-2c90-429f-b46a-0a6597353d37.png
I'm not sure I'm using the correct value for the Definition ID parameter. Here's the url that appears when I'm editing my build pipeline YAML from the Az DevOps interface:
https://dev.azure.com/revilasn/MLOps/_apps/hub/ms.vss-build-web.ci-designer-hub?pipelineId=22&nonce=DcEqv2w7sAp1xu6ptET9Mg%3D%3D&branch=master
Is my Definition ID 22?
—
Reply to this email directly, view it on GitHubhttps://github.com/panuoksala/streamdeck-azuredevops-plugin/issues/9#issuecomment-1006036468, or unsubscribehttps://github.com/notifications/unsubscribe-auth/ADXV4Q756B5ZAW224B7BW43UUSPTLANCNFSM5IFKSZHA.
Triage notifications on the go with GitHub Mobile for iOShttps://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675 or Androidhttps://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub.
You are receiving this because you were mentioned.Message ID: @.***>

I've just tested it again with a Full Access PAT and the problem remains the same.

OK. Your organization name should be set to revilasn and project name should be MLOps. Definition Id is 22 and pipeline type i think is Build if it is not a Release pipeline.

It it is still no go, I will add logging and provide new version for you.

It is still a no go, please add logging so I can debug it.

Sorry I was off during holidays, but I will provide the logging version soon.

There is some logging actually already present. The log files should arrive under plugin folder. In windows that is:
Elgato\StreamDeck\Plugins\net.oksala.azuredevops.sdPlugin\log
The logging need to be improved, but could you check the existing log

Here is the link to new version which logs more info about DevOps problems:
https://1drv.ms/u/s!Ap4gpegjXAK1iYQ9cEmki_Pbb1WM0A?e=1zwfCk

I'm planning to do new release and it would be cool if we could verify this. Any news on your side?


Add email header affordance

Prior to this change when a user opens a RTD email the header may be very thin and then suddenly
expand as the image loads the email content lowers. This caused me to click the header instead of
the email confirmation link

Nice catch :) Thanks for the addition!


Unprivileged containers

Edit: Figured it out, found another issue, see below.
I am unable to create unprivileged containers. All of my containers are owned by root and I can't find an option to specify another user in the UI or configuration files. Based on a commit message from googley's repo stating LWP supports unprivileged containers, I assume the feature in included in this fork. Am I missing something?

For anyone else:
Simply create a user with the same credentials as your desired linux user and login to the webui as that user.

Can't get it to work, did so that root and another user is Unprivileged
when trying to create a server with ubuntu 15.04 it says "Error! testserver"
tried database user and pam
also tried to root lwp as another user with the same error

It uses another command:
#$ lxc-create -n server1 -t debian
This template can't be used for unprivileged containers.
You may want to try the "download" template instead.
lxc-create: lxccontainer.c: create_run_template: 1197 container creation template for avs failed
lxc-create: lxc_create.c: main: 274 Error creating container avs
#$ lxc-create -t download -n server1 -- -d debian -r jessie -a amd64
works in console

@arocnies I don't really understand in your second message if there is still a problem or if it was fixed. If so please close the issues
I reproduce your problem @cronner and I believe that it is a configuration issue inherith by default /etc/lxc/default.conf .
$ lxc-start -n server1 --logfile /tmp/log.txt
lxc-start: lxc_start.c: main: 344 The container failed to start.
lxc-start: lxc_start.c: main: 346 To get more details, run the container in foreground mode.
lxc-start: lxc_start.c: main: 348 Additional information can be obtained by setting the --logfile and --logpriority options.
(lxc)cmignanti@cmignanti-asus:~/code/LXC-Web-Panel$ cat /tmp/log.txt
      lxc-start<PHONE_NUMBER>.115 ERROR    lxc_start - start.c:lxc_spawn:1000 - failed to create the configured network
      lxc-start<PHONE_NUMBER>.150 ERROR    lxc_start - start.c:__lxc_start:1164 - failed to spawn 'server1'
      lxc-start<PHONE_NUMBER>.156 ERROR    lxc_start_ui - lxc_start.c:main:344 - The container failed to start.
      lxc-start<PHONE_NUMBER>.156 ERROR    lxc_start_ui - lxc_start.c:main:346 - To get more details, run the container in foreground mode.
      lxc-start<PHONE_NUMBER>.156 ERROR    lxc_start_ui - lxc_start.c:main:348 - Additional information can be obtained by setting the --logfile and --logpriority options.

The error "failed to create the configured network" could be due to lxc.include in your ~/.config/lxc/default.conf
Anyway this is not a LXC-Web-Panel issues.


103 translation

Hi, I tried installing your package, and then running  django-admin makemessages --al to try and be able to update it to spanish, but no dice.  Any idea how I can either help translate this to spanish, or set up a command to do so?


Vulnerability roundup 91: evolution-data-server-3.36.4: 1 advisory [7.5]

search, files

[ ] CVE-2020-16117 CVSSv3=7.5 (nixos-unstable)

Scanned versions: nixos-unstable: 840c782d507. May contain false positives.
Cc @dasj19
Cc @hedning
Cc @jtojnar
Cc @worldofpeace

The description mentions e.d.s versions up to 3.35.91 and indeed was fixed at that point release: https://download.gnome.org/sources/evolution-data-server/3.35/evolution-data-server-3.35.91.news

Obviously a typo in the CPE match expression


Bug: Connector stop working after nats reconnection

Bug description
After the NATS system recreates a connection, the connector ceases to function. This issue has been observed consistently following each instance of NATS connection recreation. Consequently, data transmission and communication processes stop working, leading to major operational setbacks.
Steps to reproduce

Start the connector and NATS server.
Create a pipeline file with NATS Jetstream as the source and log as the destination.
Use NATS benchmark to create some load: nats bench test --js --pub 1 --size 16 --msgs 10
Run conduit and observe logs of messages received working.
Stop NATS server
Stop NATS benchmark
Start NATS server
Start NATS benchmark
Observe logs of messages received NOT working.

Version
0.3.1

Pipeline that I have been using for testing:
version: 1.0
pipelines:
  nats-to-log:
    status: running
    description: >
      nats to log
    connectors:
      nats-source:
        type: source
        plugin: standalone:nats@latest
        settings:
          subject: test
          urls: nats://<IP_ADDRESS>:4222
      log-dest:
        type: destination
        plugin: builtin:log
        settings:

Problem fixed: https://github.com/nassor/conduit-connector-nats-jetstream/tree/fix/jetstream-reconnection in this PR
Still need to fix the tests to create a PR.


Cannot delete sheets

Calling excel.delete(sheetName) can throw this error:
[ERROR:flutter/runtime/dart_vm_initializer.cc(41)] Unhandled Exception: Unsupported operation: Cannot remove from an unmodifiable list
E/flutter (20043): #0      UnmodifiableListMixin.removeWhere (dart:_internal/list.dart:139:5)
The problem seems to be trying to delete from _archive.files, which is an UnmodifiableListView

I am facing this issue while using the rename function.
It tries to delete the old named sheet

Apparently they are trying to call removeWhere() on _archive.files, which is an UnformidableView
I am not sure why they make _archive.files unformidable but also call removeWhere on it. Dart documentation clearly says it is not supported. removeWhere method

Renaming sheet throws error too.
Renaming or deleting sheets is not possible.
    final excel = Excel.createExcel();
    excel.rename("Sheet1", "newName");

this throws following error for me

Error
dart-sdk/lib/internal/js_dev_runtime/private/ddc_runtime/errors.dart 297:3  throw
dart-sdk/lib/internal/list.dart 139:5                                        removeWhere
packages/excel/src/excel.dart 265:16                                         delete
packages/excel/src/excel.dart 199:7                                          rename

Could anyone please confirm if that issue continues on 4.0.x?

I'm able to rename sheets that I create.
This is on windows 11, lib version v4.0.2
  Excel excel = Excel.createExcel();
  var overviewSheet = excel['OVERVIEW'];
  excel.rename("OVERVIEW", "REQUIREMENTS");

I cannot delete "Sheet1", however. It gives me this error:
Unhandled exception:
Unsupported operation: Cannot remove from an unmodifiable list
#0      UnmodifiableListMixin.removeWhere (dart:_internal/list.dart:139:5)
#1      Excel.delete (package:excel/src/excel.dart:279:22)
#2      main (*)

If I remove the block of code that is throwing an exception then I can delete Sheet1:
      // _archive.files.removeWhere((file) {
      //   return file.name.toLowerCase() == _xmlSheetId[sheet]?.toLowerCase();
      // });

What is the purpose of deleting from the unmodifiable list?

I upgraded to v4.0.3 and this was fixed, even for Sheet1.


clang: error: linker command failed with exit code 1 (use -v to see invocation)

Hi,
I find your framework really interesting and I would like to link to to my project and use it..
Unfortunately, when I compile the code, xCode find 55 duplicate symbols for architecture armv.


Pr snapdragon fixes

These are changes meant to move towards solving #9444
With these changes you can flash Snapdragon and the dsp does not crash anymore (no more missing symbols in libpx4.so and libpx4muorb_skel.so).
@dagar Given that you are our build system expert we should go through the changes together and see if we can find a better solution / root cause for some of the stuff, especially:

why does geo.cpp not work (undefined symbol _Dbl)
why does -fno-math-errno not work

Partial fixes https://github.com/PX4/Firmware/pull/9492

ECL side - https://github.com/PX4/ecl/pull/449

Replaced by #9503


Set path option to null to stream to stdout/stderr

AWS, Heroku, and many other logging endpoints and aggregators expect to receive logs on stdout/stderr. This change allows passing path: null as an option to do this easily as a Bunyan stream.

Hey Jordan,
Nice one .. there's a js linting rule for triple equals instead of double equals, so I'll update this, then bump version and npm publish.
Might also be some dependencies that need updating so we could see two minor version increase today.
Cheers.

Awesome, thanks for the merge!


Lightnet sub-commands implementation (start/stop/status).

Corresponding RFC implementation with slightly extended API.
FYI: boolean options with default value of true can be negated by adding --no- prefix.
For example:

The --archive option of zk lightnet start sub-command is true by default. And to set it to false you can do zk lightnet start --no-archive.

Tests will added later as part of the work on https://github.com/o1-labs/zkapp-cli/issues/509.

Closes #500

I have forgotten to check it on Windows and of course there are some issues. It should not impact review process though. Apologies for inconvenience.

Seems to be false alarm and the issue was caused by Docker Engine not being started. I'll add additional check.

Ah, so Windows does work? Even the logs store mechanism? I'm surprised since it's using non friendly windows seperators in paths :sweat_smile:

Seems to be false alarm and the issue was caused by Docker Engine not being started. I'll add additional check.

Ah, so Windows does work? Even the logs store mechanism? I'm surprised since it's using non friendly windows seperators in paths 😅

Yeah it worked before on Windows as well. Paths do resolve correctly.


Last Snapshot data to calculate power amount rank

Used last snapshot data to calculate expected project rank corresponding to power amount  (powerAmountRank)
Refs https://github.com/Giveth/giveth-dapps-v2/issues/1947

Thank you @CarlosQ96


timit

sorroy, could you provider a linker about timit dataset and I can't find a effective link. Thank you very much.

https://github.com/philipperemy/timit

@dreamibor thank you


Add style to map using Ionic 2 plugin

Hello,
Could you please help me how to set a style to my map declared with Ionic?
let element: HTMLElement = document.getElementById('map');
let map: GoogleMap = this.googleMaps.create(element);
I'm trying with this but is not working
map.setOptions({         styles:[{...}]
Thanks!

https://github.com/mapsplugin/cordova-plugin-googlemaps/issues/1180#issuecomment-261125046


Ladoo Catcher - Gesture

sir , can u provide me some reference what u want

@hemant933 In this game idea was to create a game where the character would catch ladoos falling from sky. There would be also some non edible items like paper or stone which we should avoid. But this is just suggestion, you can design anything you think would be appropriate for this theme.

Cool, I'll check it out.
On Sat, 13 Jan 2024, 12:17 pm Tushar Amdoskar, @.***>
wrote:

@hemant933 https://github.com/hemant933 In this game idea was to create
a game where the character would catch ladoos falling from sky. There would
be also some non edible items like paper or stone which we should avoid.
But this is just suggestion, you can design anything you think would be
appropriate for this theme.
—
Reply to this email directly, view it on GitHub
https://github.com/TusharAMD/Runn/issues/560#issuecomment-1890347482,
or unsubscribe
https://github.com/notifications/unsubscribe-auth/AZAZIZWMYWERE5T5NOTBGNLYOIUY7AVCNFSM6AAAAABBW4RTJKVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTQOJQGM2DONBYGI
.
You are receiving this because you were mentioned.Message ID:
@.***>

assign it to me

sir , i am working on this game and as well as its documentation

Ok assigned


Potential Mismatch Between Checkpoint Saving and Loading Behavior When Using DeepSpeed Stage 1

Bug description
I've used ZeRO Stage 1 on 4 GPUs, my checkpoint is sharded into multiple states. Here is the trainer call I used:
    trainer = pl.Trainer(
        default_root_dir=root_dir,
        callbacks=[
            ModelCheckpoint(
                dirpath=root_dir,
                every_n_train_steps=10000//(args.batch_size * args.grad_acc * torch.cuda.device_count()),
                filename=model_name + "_{epoch}_{step}",
                save_last=True)
        ],
        accelerator="gpu",
        accumulate_grad_batches=args.grad_acc,
        strategy=DeepSpeedStrategy(
            stage=1,
            allgather_bucket_size=500000000,
            reduce_bucket_size=500000000,
            pin_memory=True,
            hysteresis=100,
            overlap_comm=True
        ) if args.deepspeed else None,
        devices=-1,
        num_nodes=1,
        precision=16 if args.half_precision else 32,
        max_epochs=args.epoch,
        check_val_every_n_epoch=args.valid_every,
        gradient_clip_val=5,
        plugins=[SLURMEnvironment(requeue_signal=signal.SIGHUP)]
    )

When I call convert_zero_checkpoint_to_fp32_state_dict on the checkpoint directory, I get the following:
from pytorch_lightning.utilities.deepspeed import convert_zero_checkpoint_to_fp32_state_dict
convert_zero_checkpoint_to_fp32_state_dict(save_path, output_path)
Processing zero checkpoint '/Users/ftaj/Library/CloudStorage/OneDrive-UniversityofToronto/PycharmProjects/autopath/scTransformers/RegressionTransformer/checkpoints/last.ckpt/checkpoint'
Traceback (most recent call last):
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 3553, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-16-1ecd0e27460d>", line 1, in <cell line: 1>
    convert_zero_checkpoint_to_fp32_state_dict(save_path, output_path)
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/pytorch_lightning/utilities/deepspeed.py", line 81, in convert_zero_checkpoint_to_fp32_state_dict
    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/deepspeed/utils/zero_to_fp32.py", line 406, in get_fp32_state_dict_from_zero_checkpoint
    return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir)
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/deepspeed/utils/zero_to_fp32.py", line 164, in _get_fp32_state_dict_from_zero_checkpoint
    zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir)
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/deepspeed/utils/zero_to_fp32.py", line 131, in parse_optim_states
    raise ValueError(f"unknown zero stage {zero_stage}")
ValueError: unknown zero stage 1

These are the contents of my checkpoint directory:
-rw-r----- 1 ftaj lstein 6.5M Dec 19 01:54 mp_rank_00_model_states.pt
-rw-r----- 1 ftaj lstein 9.4M Dec 19 01:54 zero_pp_rank_0_mp_rank_00_optim_states.pt
-rw-r----- 1 ftaj lstein 9.4M Dec 19 01:54 zero_pp_rank_1_mp_rank_00_optim_states.pt
-rw-r----- 1 ftaj lstein 9.4M Dec 19 01:54 zero_pp_rank_2_mp_rank_00_optim_states.pt
-rw-r----- 1 ftaj lstein 9.4M Dec 19 01:54 zero_pp_rank_3_mp_rank_00_optim_states.pt

And when I try to load the mp_rank_00_model_states.pt file directly, I get this
model = RegressionTransformer.load_from_checkpoint(checkpoint_path+"/checkpoint/mp_rank_00_model_states.pt")

Traceback (most recent call last):
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/IPython/core/interactiveshell.py", line 3553, in run_code
    exec(code_obj, self.user_global_ns, self.user_ns)
  File "<ipython-input-12-87290d30a2b7>", line 1, in <cell line: 1>
    model = RegressionTransformer.load_from_checkpoint(checkpoint_path+"/checkpoint/mp_rank_00_model_states.pt")
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/pytorch_lightning/core/saving.py", line 137, in load_from_checkpoint
    return _load_from_checkpoint(
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/pytorch_lightning/core/saving.py", line 180, in _load_from_checkpoint
    return _load_state(cls, checkpoint, strict=strict, **kwargs)
  File "/Users/ftaj/opt/anaconda3/envs/autopath/lib/python3.9/site-packages/pytorch_lightning/core/saving.py", line 238, in _load_state
    keys = obj.load_state_dict(checkpoint["state_dict"], strict=strict)
KeyError: 'state_dict'

I tried looking into mp_rank_00_model_states.pt with torch.load(). The keys of the dict are as follows:

dict_keys(['module', 'buffer_names', 'optimizer', 'param_shapes', 'lr_scheduler', 'sparse_tensor_module_names', 'skipped_steps', 'global_steps', 'global_samples', 'dp_world_size', 'mp_world_size', 'ds_config', 'ds_version', 'epoch', 'global_step', 'pytorch-lightning_version', 'loops', 'callbacks', 'lr_schedulers', 'hparams_name', 'hyper_parameters'])

It is mentioned in the Docs that Lightning uses DeepSpeed's implementation for saving the checkpoint, but loading the checkpoint still uses the Lightning Module's on_load_checkpoint:
https://github.com/Lightning-AI/lightning/blob/0abd6864082a456c07e03b80b0a60075b3f33efa/src/pytorch_lightning/core/saving.py#L236-L238
If DeepSpeed users have to modify their on_load_checkpoint() method in their LightningModule, please advise.
Note that I updated to 1.8.5 and I'm still having the same problem.
Thank you,
Farzan
How to reproduce the bug
No response
Error messages and logs
# Error messages and logs here please

Environment

Current environment
#- Lightning Component (e.g. Trainer, LightningModule, LightningApp, LightningWork, LightningFlow): LightningModule/Trainer
#- PyTorch Lightning Version (e.g., 1.5.0): 1.8.4.post0
#- Lightning App Version (e.g., 0.5.2):
#- PyTorch Version (e.g., 1.10): 1.12.1
#- Python version (e.g., 3.9): 3.8.13
#- OS (e.g., Linux): Linux, Red Hat Enterprise Linux
#- CUDA/cuDNN version: 11.4.4
#- GPU models and configuration: x4 V100, 1 Node, Slurm environment
#- How you installed Lightning(`conda`, `pip`, source): pip
#- Running environment of LightningApp (e.g. local, cloud): cluster

More info
No response

I have experienced exactly the same two errors as above when 1) trying to convert the deepspeed checkpoint to fp32 and 2) when trying to directly load the deepspeed model using the lightning module. Suggestions are much appreciated!

I fixed it by adding this following to my Lightning Module.
def on_load_checkpoint(self, checkpoint: dict[str, Any]) -> None:
        """Fix the checkpoint loading issue for deepspeed."""
        if "state_dict" in checkpoint:
            return
        state_dict = checkpoint['module']
        state_dict = {k.partition('module.')[2]: state_dict[k] for k in state_dict.keys()}
        checkpoint['state_dict'] = state_dict
        return

Time to load utils op: 0.0010721683502197266 seconds
[3]
0%|          | 0/833 [00:00<?, ?it/s]                                                                                Using /root/.cache/torch_extensions/py38_cu117 as PyTorch extensions root...
No modifications detected for re-loaded extension module utils, skipping build step...
Loading extension module utils...
Time to load utils op: 0.0003685951232910156 seconds
[3]
0%|          | 0/833 [00:01<?, ?it/s]
Traceback (most recent call last):
File "/root/autodl-tmp/train_wll.py", line 162, in
trainer.run(m_cfg, train_dataset, None, tconf)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/lightning_fabric/fabric.py", line 628, in _run_impl
return self._strategy.launcher.launch(run_method, *args, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/lightning_fabric/strategies/launchers/subprocess_script.py", line 90, in launch
return function(*args, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/lightning_fabric/fabric.py", line 638, in _run_with_setup
return run_function(*args, **kwargs)
File "/root/autodl-tmp/src/trainer.py", line 177, in run
run_epoch('train')
File "/root/autodl-tmp/src/trainer.py", line 119, in run_epoch
loss = model(x, y) # forward the model
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/lightning_fabric/wrappers.py", line 110, in forward
output = self._forward_module(*args, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/deepspeed/utils/nvtx.py", line 11, in wrapped_fn
return func(*args, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/deepspeed/runtime/engine.py", line 1656, in forward
loss = self.module(*inputs, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/root/autodl-tmp/src/model.py", line 408, in forward
x = self.head(x)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 114, in forward
return F.linear(input, self.weight, self.bias)
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.30 GiB (GPU 1; 15.74 GiB total capacity; 14.23 GiB already allocated; 1.31 GiB free; 14.23 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
0%|          | 0/1666 [00:01<?, ?it/s]
Traceback (most recent call last):
File "train_wll.py", line 162, in
trainer.run(m_cfg, train_dataset, None, tconf)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/lightning_fabric/fabric.py", line 628, in _run_impl
return self._strategy.launcher.launch(run_method, *args, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/lightning_fabric/strategies/launchers/subprocess_script.py", line 90, in launch
return function(*args, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/lightning_fabric/fabric.py", line 638, in _run_with_setup
return run_function(*args, **kwargs)
File "/root/autodl-tmp/src/trainer.py", line 177, in run
run_epoch('train')
File "/root/autodl-tmp/src/trainer.py", line 119, in run_epoch
loss = model(x, y) # forward the model
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/lightning_fabric/wrappers.py", line 110, in forward
output = self._forward_module(*args, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/deepspeed/utils/nvtx.py", line 11, in wrapped_fn
return func(*args, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/deepspeed/runtime/engine.py", line 1656, in forward
loss = self.module(*inputs, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/root/autodl-tmp/src/model.py", line 408, in forward
x = self.head(x)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1190, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/envs/mygpt/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 114, in forward
return F.linear(input, self.weight, self.bias)
torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 2.30 GiB (GPU 0; 15.74 GiB total capacity; 14.23 GiB already allocated; 812.69 MiB free; 14.23 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF
trainer = Trainer(devices=NUM_GPUS, accelerator="gpu", precision='bf16')
# trainer = Trainer(strategy="deepspeed", devices=NUM_GPUS, accelerator="gpu", precision='bf16') #省显存方式：strategy="deepspeed"

strategy=DeepSpeedStrategy(
        stage=1,
        allgather_bucket_size=200000000,
        reduce_bucket_size=200000000,
        pin_memory=True,
        hysteresis=100,
        overlap_comm=True
    )

trainer = Trainer(strategy=strategy, devices=1, accelerator="gpu", precision='bf16')

I have no idea if this works for all use cases of deepspeed 1 - but i found that for mine. The checkpoint format "is compatible" with deepspeed 2.
A simple search and replace for "== 2" to "<= 2" in the conversion script, allows it to work.
https://github.com/microsoft/DeepSpeed/pull/3936
If you are facing this issue, please do try and validate if it works for your use case. Cause until someone from deepspeed confirms that the format is the same - i have no idea if this is the right path.

Thanks @PicoCreator for sending the fix in the deepspeed repo! I reproduced the issue described here and can confirm your changes fixed it with the latest DeepSpeed version from master.
My steps to reproduce using the following script:
import torch
from torch.utils.data import DataLoader, Dataset

from lightning.pytorch import LightningModule, Trainer
from lightning.pytorch.callbacks import ModelCheckpoint
from lightning.pytorch.utilities.deepspeed import convert_zero_checkpoint_to_fp32_state_dict

class RandomDataset(Dataset):
    def __init__(self, size, length):
        self.len = length
        self.data = torch.randn(length, size)

    def __getitem__(self, index):
        return self.data[index]

    def __len__(self):
        return self.len

class BoringModel(LightningModule):
    def __init__(self):
        super().__init__()
        self.layer = torch.nn.Linear(32, 2)

    def forward(self, x):
        return self.layer(x)

    def training_step(self, batch, batch_idx):
        loss = self(batch).sum()
        self.log("train_loss", loss)
        return {"loss": loss}

    def validation_step(self, batch, batch_idx):
        loss = self(batch).sum()
        self.log("valid_loss", loss)

    def test_step(self, batch, batch_idx):
        loss = self(batch).sum()
        self.log("test_loss", loss)

    def configure_optimizers(self):
        return torch.optim.Adam(self.parameters())

def run():
    train_data = DataLoader(RandomDataset(32, 64), batch_size=2)
    val_data = DataLoader(RandomDataset(32, 64), batch_size=2)
    test_data = DataLoader(RandomDataset(32, 64), batch_size=2)

    model = BoringModel()
    trainer = Trainer(
        max_epochs=2,
        accelerator="cuda",
        devices=2,
        strategy="deepspeed_stage_1",
        callbacks=ModelCheckpoint(dirpath="deepspeed_checkpoint")
    )
    trainer.fit(model, train_dataloaders=train_data, val_dataloaders=val_data)
    trainer.test(model, dataloaders=test_data)

    if trainer.global_rank == 0:
        convert_zero_checkpoint_to_fp32_state_dict(
            "deepspeed_checkpoint/epoch=1-step=32.ckpt",
            "deepspeed_checkpoint/model.pt"
        )

    trainer.strategy.barrier()

    # verify we can load
    loaded_model = BoringModel.load_from_checkpoint("deepspeed_checkpoint/model.pt")
    # success!

if __name__ == "__main__":
    run()

Run the above with latest version of Lightning (2.0) and deepspeed <= 0.9.5. You will get this error:
Traceback (most recent call last):
  File "/home/adrian/repositories/lightning/examples/pytorch/bug_report/bug_report_model.py", line 73, in <module>
  File "/home/adrian/repositories/lightning/examples/pytorch/bug_report/bug_report_model.py", line 63, in run
    convert_zero_checkpoint_to_fp32_state_dict(
  File "/home/adrian/repositories/lightning/src/lightning/pytorch/utilities/deepspeed.py", line 79, in convert_zero_checkpoint_to_fp32_state_dict
    state_dict = get_fp32_state_dict_from_zero_checkpoint(checkpoint_dir, tag)
  File "/home/adrian/.conda/envs/lightning/lib/python3.10/site-packages/deepspeed/utils/zero_to_fp32.py", line 505, in get_fp32_state_dict_from_zero_checkpoint
    return _get_fp32_state_dict_from_zero_checkpoint(ds_checkpoint_dir)
  File "/home/adrian/.conda/envs/lightning/lib/python3.10/site-packages/deepspeed/utils/zero_to_fp32.py", line 201, in _get_fp32_state_dict_from_zero_checkpoint
    zero_stage, world_size, fp32_flat_groups = parse_optim_states(optim_files, ds_checkpoint_dir)
  File "/home/adrian/.conda/envs/lightning/lib/python3.10/site-packages/deepspeed/utils/zero_to_fp32.py", line 172, in parse_optim_states
    raise ValueError(f"unknown zero stage {zero_stage}")
ValueError: unknown zero stage 1

pip install git+https://github.com/microsoft/DeepSpeed.git@master (https://github.com/microsoft/DeepSpeed/pull/3936)

Run again to see it succeed with the following logs:
Processing zero checkpoint 'deepspeed_checkpoint/epoch=1-step=32.ckpt/checkpoint'
Detected checkpoint of type zero stage 1, world_size: 2
Parsing checkpoint created by deepspeed==0.10.0+103884ae
Reconstructed fp32 state dict with 2 params 66 elements
Saving fp32 state dict to deepspeed_checkpoint/model.pt

Thanks again @PicoCreator! Closing this issue.


This fixes Issue #1

fixes #1
Changed the underscore to a dash in lib/assets for sidebar
sidebar_body to sidebar-body
sidebar_title to sidebar-title

LGTM


ModuleNotFoundError: No module named 'geotile'

Hi !
When I import geotile, following the readme from geotile import GeoTile gives me:
ModuleNotFoundError: No module named 'geotile'
I figured out that geotile is actually registered as geoTile so from geoTile import GeoTile works.
Thank you for your work by the way !

Hi @Aerius42, I think you are using v0.1.x version. I change the folder structure on v0.2.x. Can you try it with the latest version?
pip install geotile==0.2.2


Cloudathon

Thank you for the submission. The intent of the fabric-samples repository is to support the official Fabric documentation tutorials with minimal duplication of application patterns. Since this chaincode is similar in overall pattern to the pre-existing asset-transfer-basic java chaincode, I don't think a second sample is needed. If you'd like to improve the existing application patterns, I'd suggest to enhance the asset transfer samples and related tutorial documentation rather than introducing a new sample.


Revert "Include changes to the target branch when action is re-run"

Reverts swiftlang/github-workflows#58
This has resulted in a destructive outcome for developers using act to run the workflows locally, which is also in our public documentation now, particularly when used with --bind.
This patch recreates the entire repo and force updates to a ref. It literally deleted my Git repo and left me with a grafted shallow clone. It discarded all my local branches and no reflog was available.
We need to revert this one quickly.
I've verified that the revert mitigates the problem by making this change in my YAMLs locally, to the commit before this PR was merged:
-    uses: apple/swift-nio/.github/workflows/cxx_interop.yml@main
+    uses: swiftlang/github-workflows/.github/workflows/soundness.yml@814f5831ccc6aac159903e8db6daba726c8b62d5

I'm sympathetic to the motivation behind the PR but I think we should revert immediately to avoid others hitting this.

//cc @shahmishal @ahoppen @ktoso @rnro

Thanks for merging promptly.
I'm finished for today now but I think we could investigate using a conditional here on the CI environment variable and only have this behaviour if running in CI. I believe we have a similar behaviour somewhere else already but I'm on a mobile device so can't validate right now.

Sorry for breaking the act workflow @simonjbeaumont and thanks for reverting my change.
If you have an example of how you guard behavior on the CI environment, I’d be interested to see that and check if we can apply it here as well.

@ahoppen Looks like we can use job.if here with an environment variable that's only set when using act:
jobs:
  foo:
    runs-on: ubuntu-latest
    name: Foo
    steps:
      - name: Dump env
        run: env | sort
      - name: Echo always
        run: echo "always"
      - name: Echo only if FOO=true
        if: env.FOO == 'true'
        run: echo "job running with FOO set to true"
      - name: Echo only if not FOO=true
        if: env.FOO != 'true'
        run: echo "job not running with FOO set to true"
      - name: Echo only if running with act
        if: env.ACT == 'true'
        run: echo "job running with ACT"
      - name: Echo only if not running with act
        if: env.ACT != 'true'
        run: echo "job not running with act"

So I think it will just be adding if: env.ACT != 'true' to the steps. I'll open a PR to reintroduce the change.


ci: add node-14.x to workflow

Motivation, Context & Description

Test with Node 14.x
Added Node 14.x CI all workflow configurations.

See https://github.com/apache/cordova/issues/223 for more details.
Testing

No local testing required.
Use CI service test results

Checklist

[x] If this Pull Request resolves an issue, I linked to the issue in the text above (and used the correct keyword to close issues using keywords)

Closing this PR as this plugin has been deprecated.


"failed to run temp binary" on Windows

Hello 👋
Thanks for the great library. It was simple to get it implemented in our code base. We have it working successfully on Mac but I'm running into a bit of trouble on Windows. We're using the HTTP fetcher which is downloading the file and placing it in a temp directory successfully (can see it show up in file explorer). But when the fetch process tries to see if the downloaded binary is executable it returns an error and bails out:
failed to run temp binary: exec: "C:\\Users\\Level\\AppData\\Local\\Temp\\overseer-1dc5f76e2b9039ce": file does not exist (C:\Users\Level\AppData\Local\Temp\overseer-1dc5f76e2b9039ce) output ""
The file certainly does exist but for some reason Go thinks it doesn't. The error is coming from this line: https://github.com/jpillora/overseer/blob/6877a7e73f6a4bebbfe1999fcbf84e52a3c1e6ca/proc_master.go#L287

Does anyone have any experience or advice related to this error? Thanks!

Also, the file appears in file explorer and then short while later is deleted. I assume the delete happens after it fails to apply the update but don't know that for sure.

I got to root of this problem. Turns out it's because the temp binary doesn't have an extension and the PATHEXT env variable doesn't include "." by default. This issue could be fixed in user-land by adding that env variable when the program starts. But maybe the ideal solution would be for this package to be updated to either: make the temp binary an exe on Windows or to add "." to the PATHEXT before it tries to execute the temp file.

hey @joshforbes, could you test v1.1.5 - thanks for your help @tgulacsi

1.1.5 is great and fixes my other Windows problem (https://github.com/jpillora/overseer/issues/56). But does nothing for this one. The problem here is that the default PATHEXT for windows 10 is: .COM;.EXE;.BAT;.CMD;.VBS;.VBE;.JS;.JSE;.WSF;.WSH;.MSC but the temp file doesn't have an extension.
https://superuser.com/a/1027081
Changing the PATHEXT to: .COM;.EXE;.BAT;.CMD;.VBS;.VBE;.JS;.JSE;.WSF;.WSH;.MSC;. (with a "." at the end for no extension files) makes it work.
I think we could likely change:
https://github.com/jpillora/overseer/blob/36ed46f9bcbd7314d3b5b0643b1d907adea775fe/proc_master.go#L22
To have an ".exe" extension on windows and it would fix the problem. Does that seem right?

Sure, just not globally, but only on Windows.

You should try
--- a/proc_slave_windows.go
+++ b/proc_slave_windows.go
@@ -16,6 +16,10 @@ var (
        Timeout = 3 * time.Second
 )

+func init() {
+       tmpBinPath += ".exe"
+}
+
 type Win32_Process struct {
        Name                  string
        ExecutablePath        *string


Citation

Hi @mobinasri to cite this pipeline should we cite the pangenome paper or do you have a methods paper for this?
Thanks,
Mitchell

@mrvollger Hi, The methods paper is being written. Please cite the pangenome paper for now.


Improving Java interface

@davidrpugh These are the first steps to improve the Java interface. I first tried to replicate the Scala class structure in Java in order to get the same level of flexibility. I ran into a couple of problems, e.g. related with the implicit parameters in FourHeapOrderBook.empty.
Rather than trying to solve all of these problems, I started to re-implement sandbox.sc in Java in order to see how easy it would be to use the Scala classes directly (see src/main/java/org/economicsl/auctions/Sandbox.java). Surprisingly, that's now rather simple and straightforward. There is still some syntactic clutter (e.g. the '$' characters or the lack of +and - operators), but overall it looks pretty clear. Also, I added a helper class Clearing that encapsulates the conversion of the clearing result into something that's more easily usable in Java.
I haven't integrated the quoting stuff into the sandbox yet and I haven't tested the direct access from within our demonstrator. I'll do that now. But if it turns out that all of that works, then I'm currently inclined to get rid of the previous Java wrapper (JDoubleAuction.java) altogether and use the Scala classes directly.
What do you think? Is the syntax acceptable from a usability perspective? Some of the stuff could certainly be further simplified, e.g. by adding more helper classes similar to Clearing.java.

@bherd-rb This is definitely an improvement and assuming that you can get it working with you simulator then I think we should drop the old Java wrapper in favor of this approach.
A couple thoughts: first I will get rid of the + and - operators (or rather add another method that does the same thing) in order to eliminate that source of clutter from the Java code.  Second, I could also make the implicit ordering that need to be passed to the FourHeapOrderBook constructor explicit if that would help. Third, regarding the clearing class, would it be simpler to have a ClearingResult class in Scala rather than my using a Tuple which then has to be converted?
In general, I will see if there is a way that I can structure the Scala code in order to avoid Java users having to call $.MODULE.someMethod.

@bherd-rb There seems to be a lot of cruft involved in created an instance of LimitAskOrder etc on the Java side.  I made some changes to the Scala code in order to improve the situation.   Now you can create a limit ask order in Java using...
 // Create some single-unit limit ask orders...
LimitAskOrder<GoogleStock> order3 = new LimitAskOrder<>(issuer, 5, google);
LimitAskOrder<GoogleStock> order4 = new LimitAskOrder<>(issuer, 6, google);

...the solution is to create a trait called LimitAskOrderLike which can be used as a mixin to provide LimitAskOrder like behavior to other order types as needed but then create a class LimitAskOrderthat implements theLimitAskOrderLike trait` for simple limit orders.
Does this work for you? If so, then I will open a new PR against the develop branch and make similar changes for all of the order types.

@davidrpugh Great -- that's much better!

@bherd-rb Sounds good. I will try to get to this over the weekend but can't promise anything.

@bherd-rb I have made the necessary changes to the various order traits as discussed above.  I have also change the + and - methods on the FourHeapOrderBook class to be insert and remove.  This improves the syntax on the Java side.
I don't like that Java users creating a new FourHeapOrderBook instances using...
FourHeapOrderBook<GoogleStock> orderBook1 = FourHeapOrderBook.empty(
                LimitAskOrder$.MODULE$.ordering(),
                LimitBidOrder$.MODULE$.ordering());

...I can sort this problem by creating various Ordering classes (perhaps in their own package) and then place an implicit reference to these classes in the relevant companion objects. Scala users get the nice syntax that makes use of the implicit params; Java users will need to pass the orderings directly, but at least will not have to use the $.MODULE$ syntax.
BTW, do you know why you can directly call the empty method on the FourHeapOrderBook object?  It seems like you should need to write FourHeapOrderBook$.MODULE$.empty(???, ???)?
Finally, I would like to figure out a way to avoid the call to the apply method when using the various pricing functions if possible.

@bherd-rb I came across this repo that has a lot of useful information about Java-Scala interop.


[release-1.19] Fix dry-run deactivating default webhook

This is an automated cherry-pick of #48266

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