docs: replace patchesStrategicMerge with patches

Hi @stefanprodan @hiddeco!
I am addressing this PR #1545

NOTE: I've tested everything on my side using kustomize build command

There is a point I'd like to discuss. In cron-job-image-auth.md we were using patchesStrategicMerge that allows us to apply patches to multiple resources within one patch file. When I tried to do the same with inline patches, I wasn't able because it's not supported in Kustomize version earlier than 5.2.1. Please check the changelog file for a PR that adds a support for this. When I upgrade to the latest version I was able to do it.
So I'd like to clarify if the latest version of FluxCD supports the latest stable version of Kustomize?
Also some small fixes of these markdown violations:

MD014/commands-show-output: Dollar signs used before commands without showing output
MD031/blanks-around-fences: Fenced code blocks should be surrounded by blank lines
MD032/blanks-around-lists: Lists should be surrounded by blank lines
MD029/ol-prefix: Ordered list item prefix

Hey @Stringls we're blocked with the Kustomize upgrade by cli-utils, some details here https://github.com/fluxcd/flux2/issues/3991#issuecomment-1688387251

Hey @Stringls we're blocked with the Kustomize upgrade by cli-utils, some details here fluxcd/flux2#3991 (comment)

Sadly, but in that case what'd you like to see:

Two separate patch files configmap-patch.yaml and azure-identity-patch.yaml
Two patches in kustomization.yaml without any files

I'd prefer two separate patch files as it's easier to maintain them. Please, let me know so I can address it

I'd prefer two separate patch files as it's easier to maintain them.

Sounds good 👍

@stefanprodan Thank you for an approve. I just spotted that numbering in Mozilla SOPS guide is incorrect. Please check the preview link. I'll fix that soon and let you know


Move RSA key exchange implementation to provider.

Move the RSA key exchange code to providers/implementation/exchanges. The existing dh_exch.c should give a general idea as to the bulk of the changes required.
This will be the most cumbersome of the key exchange algorithms to move across.

Not required.


Dropdown menu to view any of the ~700 possible fields stored in Marketo

Just in case anyone wants to view certain fields not included in details.html by default...

It sometimes says it fails at retrieving that field's value, but all you have to do is try again, and it almost always works the second time... Not sure why it fails the first time though... might have something to do with the speed at which we are allowed to query Marketo.


*: shared namespace execution modes

There are various use cases where running a full pod (with all of the isolation and lifecycle that implies) isn't desirable and users simply want to perform a "simpler" execution of a container image. In the simplest case this is just using rkt as a package manager - discovering/downloading/extracting an image onto the filesystem, chrooting in, and execing the desired executable. The rkt fly prototype (#1072, #1416) implements a very basic example of this.
Obviously in this mode there is (aside from the filesystem) no isolation whatsoever, in terms of either resources or namespaces - it is just another process executing directly on the host. But different users may have more nuanced requirements, like sharing some namespaces and not others with the host. One example is #1046 about using the host's PID namespace. Another use case would be running the CNI networking plugins using rkt, rather than bundling them into it as is done today. system-nspawn's --share-system flag provides one other example of a possible execution mode that might be desirable.
This is a tracker ticket to start fleshing out some example use cases and design work.

/cc @eyakubovich
/cc @ppalucki re: https://github.com/coreos/rkt/pull/1072#issuecomment-140351382

Namespace specific tickets

Namespace
Related Issues/PRs
Status

PID
#1046
WIP

Network
#1418
WIP

Mount
TODO
TODO

User
TODO
TODO

Just chiming in on a use-case for this:
I want a way to use rkt as a way to distribute and run things like monitoring agents on my hosts. Similarly, any many types of debugging tools would need minimal isolation in order to inspect system state, and state of other containers, but the usefulness of the "packaging/distribution" of rkt would still shine here.
Another thing I was thinking of was it simply makes the transition to containers easier when certain applications (like docker/kubelet) misbehave when running inside a container. For example, we could begin shipping Docker as an ACI and iteratively work on making it work inside of the other namespaces. It means we could have something between "docker runs on the host" or "docker runs in a container", when we can't get the latter to work.

@ecnahc515 I've been having very similar thoughts lately.
Every namespace the container shares removes isolation. Sharing all namespaces would practically means to run an application that has been installed/downloaded as an ACI and not using any other packaging/deployment manager.
Cherry-picking namespace isolation is not supported by systemd-nspawn, it's either all (default, also what rkt is currently using) or nothing (--share-system). If we wanted to switch to the former, we couldn't use --boot anymore, which we currently do to run systemd inside the container and eventually start the apps as services.
We need to investigate the following options for gaining fine-grained namespace control:

Patch systemd-nspawn
OR

Manually setup chroot, cgroups, requested namespaces and exec systemd

@n0rad: can you explain the use cases you would have for rkt fly here? Would systemd-nspawn --share-system --capability=all  be enough for you? Is it fine without pre-start/post-stop eventHandlers in your use cases?

Hi there,
We have some use cases that is not working with RKT, like sysdig and some dell hardware tools. We also had quite the same issue while running chef and think we will probably have it while running mesos.
For the moment we are getting around this by using a unit doing :
[Service]
ExecStartPre=/opt/bin/rkt --insecure-skip-verify fetch example.com/aci-omsa --no-store
ExecStartPre=/opt/bin/rkt image render --overwrite  example.com/aci-omsa  /opt/aci/omsa
ExecStart=/usr/bin/systemd-nspawn  --directory="/opt/aci/omsa/rootfs" --capability=all --bind=/dev --share-system --bind=/lib/modules --user=root bash -c "/cnt/bin/prestart.sh && /opt/dell/start.sh"
KillMode=mixed
Restart=always

And some script doing the same on demand for tools like sysdig
Note that we have to bind some host directories like /dev and /lib/modules
We will probably need at least pre-start since CNT, that build the ACI, rely on it to do templating and prepare the run. We have to call it manually in the systemd-nspawn command with our current system.

Primary use case for initial mode here is going to be to run Docker, kubelet, rkt within rkt.
/cc @aaronlevy @steveeJ

Fixed by #1833.

I think #1833 solves one particular use case but there's still some more to be teased out here.

I asked systemd-nspawn upstream: https://github.com/systemd/systemd/pull/2982


chore: do not set C(XX)FLAGS for rvv

Some users report that they want to set -march freely for performance tunning. Thus, now, the enforcement of flags are removed.

its better to rebase all the commit to one

LGTM

its better to rebase all the commit to one

You can disable merge on github. And always merge with squash and merge.


is this still being maintained?

Description
Is this repo still being maintained? It doesn't seem to include all published endpoints. For example, it's missing chat.scheduleMessage
What type of issue is this? (place an x in one of the [ ])

[ ] bug
[ ] enhancement (feature request)
[x] question
[ ] documentation related
[ ] testing related
[ ] discussion

Requirements (place an x in each of the [ ])

[x] I've read and understood the Contributing guidelines and have done my best effort to follow them.
[x] I've read and agree to the Code of Conduct.
[x] I've searched for any related issues and avoided creating a duplicate issue.

We finally made an update! chat.scheduleMessage is now part of the method corpus on master, and should include all but a very select few published endpoints.


Fix JsonFileStore instanciation in JsonFileStoreGenerator

The GeneratedPuliFactory currently uses a very old way to implement the JsonKeyValueStore, with a cache argument (see https://github.com/webmozart/key-value-store/commit/1e60c6750f67af693f9451f1f65073847efb882d). When we removed the second argument,  PHP simply ignored the boolean and it went unnoticed.
Later, when the JsonKeyValueStore got a second argument back ($flag, https://github.com/webmozart/key-value-store/commit/196c4c8ff4c643e6ba9f954ed482629620ac88d4#diff-d59c34cb33c1eb8de6bace8a46cfea1cR59), a problem started to appear and we got this issue : https://github.com/puli/issues/issues/142.
This PR aims to fix this. I removed the cache system completely as it seems a bit complicated to detect doctrine/cache in the generated file. What do you think?

Side note: I think this isn't a BC-break as the GeneratedPuliFactory is a
generated file, but please tell me if it is and I'll add a line in the Changelog.

This should fix https://github.com/puli/issues/issues/142
Probably also complete https://github.com/puli/cli/pull/23

Looks good! Seems like the build fails on 5.3 - can you check?

@tgalopin I didn't investigate in depth yet, but the problem is related to setEscapeSlash and the PHP 5.4+ JSON_UNESCAPED_SLASHES  (ref)

Ah ok, this is fixed in the upcoming release of https://github.com/webmozart/json.

Okay, seems good then :) . Should we update the composer.json to get the last webmozart/json version?

Yes, please update the minimum version to 1.1.0.

I updated it.

Thanks @tgalopin!


rel v23.1.2

  flake8: OK (3.66=setup[0.05]+cmd[0.00,0.13,3.48] seconds)
  sphinx: OK (93.47=setup[6.63]+cmd[0.00,0.32,20.55,9.62,0.07,0.25,0.27,0.02,55.75] seconds)
  py37-tw203: SKIP (0.01 seconds)
  py37-tw2210: SKIP (0.01 seconds)
  py37-twtrunk: SKIP (0.01 seconds)
  py37-asyncio: SKIP (0.01 seconds)
  py311-tw2210: OK (24.95=setup[5.94]+cmd[19.01] seconds)
  py311-twtrunk: OK (26.15=setup[5.98]+cmd[20.17] seconds)
  py311-asyncio: OK (23.61=setup[5.83]+cmd[17.78] seconds)
  pypy37-tw2210: SKIP (0.01 seconds)
  pypy37-twtrunk: SKIP (0.01 seconds)
  pypy37-asyncio: SKIP (0.01 seconds)
  pypy39-tw2210: SKIP (0.01 seconds)
  pypy39-twtrunk: SKIP (0.01 seconds)
  pypy39-asyncio: SKIP (0.08 seconds)
  congratulations :) (172.07 seconds)
(cpy311_5) oberstet@intel-nuci7:~/scm/crossbario/autobahn-python$


Add an output-file option

This may be used instead of basic shell redirection, particularly on
(broken) systems where that might not work.

This pull request will not be merged; output is meant to be directed to a file through shell redirection.
Additionally the manner by which it outputs to the standard output has been changed fundamentally; see 6c55e8c9928a0a70ad0880e2ab64e4299e7cd023.

understood. Can't really blame you for not working around fundamentally broken shells/OSes :)

@chungy it is not so much the workarounds, but that I would rather see shell redirection working and when it does work I have yet to see a good reason for the file output option.


feat: add preset-typescript into babel

So that we can write typescript in test

Thank you so much. No idea how this didn't come until now. I'm just testing things and will get the release out shortly.


Fix frontend index.html

<-- Add travis and codecov badge -->
Fix search box bug.
Screen shot

Codecov Report

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The diff coverage is n/a.

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@@           Coverage Diff           @@
##             beta      #69   +/-   ##
=======================================
  Coverage   69.83%   69.83%
=======================================
  Files          23       23
  Lines         620      620
  Branches       76       76
=======================================
  Hits          433      433
  Misses        169      169
  Partials       18       18

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Implement PuppeteerLoaderFixture

This class will help us download chromium and set up a WebServer on a CI server.
Wanna take a look @Meir017 ?

how is the CI configured? I don't see an appveyor.yml file?

@Meir017 It CI is configured in AppVeyor, I don't think we need the yml file (yet)

I noticed that the ci runs are taking around 1 Hour to finish, could it be because the server process is still open? I'm guessing that the 1 Hour is the default test run timeout

I'll take a look


Add @RequiresInstalledToolChain to tests that, well, require an installe...

Add @RequiresInstalledToolChain to tests that, well, require an installed toolchain.

Thanks for the contribution!  I've merged the changes that add annotations to the native tests.  For the non-native tests, I just fixed the issue that was causing the exception so the annotations shouldn't be required.


Bump Gradle wrapper to 3.4

Merged in https://github.com/SpongePowered/SpongeCommon/commit/36a3454d07609df26753db2ecb8ad797b6e826ed


Solution explorer is shown in explorer window although preference is set to acitivityBar

Since a few days solution explorer is suddenly showing in the explorer window although I didn't change the setting.

Same problem here. Started to happen after updating vscode to version 1.42.


Next-line rule was too strict

We have a few places where we do this:
if {
  //...
}
// Look, a comment
else {
  //...
}

I don't think we want to forbid these cases, so I'm loosening the requirement from "must be on the line after the prior curly brace" to "can't be on the same line as the curly brace".

:+1:


check for nullness

This should fix #59. The if there was failing b/c a fsspec.get_mapper() returns false. I don't know enough about fsspec but I guess that makes sense if a directory is not created yet. Regardless we should always check for nullness instead of if var: do it in those cases.

I'm going to cc @martindurant on this. It seems unexpected that fsspec.get_mapper() evaluates to False. Martin, is this expected behavior or an fsspec bug?

Since it derives from MutableMapping, I think that bool(mapper) is essentially a test for emptiness, like bool(dict). The behaviour is not explicitly defined in fsspec.

Ok great, so let's go forward with this.
@ocefpaf - clearly the situation in #59 was not covered by our tests. Could you manage to add a simple test for this scenario?  I believe the right combo is

rechunking an xarray dataset
passing a mutable mapping (rather than path string) as temp_store / target_store

I would add an additional parameterization here:
https://github.com/pangeo-data/rechunker/blob/17053cc2956ab8d417a666cc8675bcb4df1c5c56/tests/test_rechunk.py#L45-L54
Which parameterizes the store arguments (rather than setting them within the test function).

Thanks Felipe! This is a fine solution.


Update Dockerfile to be based on 9.2-base-ubuntu18.04

While this has a great potential to work, we are not continuously testing TF on cuda 9.2
I would like to see what @zheng-xq and @tfboyd think about this change before I merge it.

referencing this ticket: https://github.com/tensorflow/tensorflow/issues/18906

@tfboyd ?

I feel the device driver is too new for most people as it is not easy to get via the official debian repository or even the ubuntu repoistory (I just checked again) which is updated faster.  NVIDIA does not support officially support the driver on their DGX-1.  It is not hard to install but I find it odd how any people cannot install these tools.  I posted some basic performance numbers  and you get most of the CUDA 9.2 gains with CUDA 9.0/cuDNN 7.1.4.  I would like us to support two versions of CUDA like the other ML tools but that is not something the infrastructure is supporting right now.  That will have to change with the CUDA 10 launch.  There is some mid and long-term hope.  NVIDIA has suggested they will make CUDA 10 through 10.x backwards compatible with the initial device driver, and as soon as CUDA is early access I want to publish builds.
Per the issue below, I am open to suggestions and other ways to look at it.  One perspective is people that cannot update their device driver should get an older version of TensorFlow.  I kind of dig that idea, but I wonder how painful that is for people to then find out they need a much newer device driver.  On the plus side NVIDIA is publishing better CUDA install packages.
https://github.com/tensorflow/tensorflow/issues/18906
Let me know what you think and if you have time what you are using that is specifically in CUDA 9.2/7.1.4 that is not in CUDA 9.0/7.1.4.  I am curious and that might help tip the scales in the short-term.

I believe that in order to use Ubuntu 18.04 you need to be using CUDA 9.2 (see https://github.com/NVIDIA/nvidia-docker/issues/666#issuecomment-389118126). I would like to upgrade to 18.04 for a number of reasons, the primary being native support for Python 3.6.

@cancan101  Ahh so CUDA 9.2 is not the goal the goal is Ubuntu 18.04.  CUDA 9.2 is a means to an end.  I did not consider that.

18.04 seems fresh and as an indication are not offering an upgrade from 16.04 LTS until maybe later July.  I do not know how popular the Docker is but moving it to Python 3.6 as the default seems like a big deal if people were expecting it to be 2.x.  NVIDIA dropped 14.04 and we should move to 18.04 I do not think it should happen right now, that is an even bigger move in my opinion than CUDA 9.2.
Thank you for the info.  I really had not considered the Ubuntu angle.
If we moved to building tensorflow with CUDA 9.2 would that reduce your pain.  You could have a custom docker file with a pip install tf-nightly or whatever and get Ubuntu 18.04.  Just asking.

no no no. I am not suggesting moving from python 2 to python 3.6. There is already a python 3 image which I am suggesting moving to python 3.6 (from 3.6).

see: https://github.com/tensorflow/tensorflow/blob/444d3a7b382cd2a0f3759eb9f7791054f6319843/tensorflow/tools/docker/parameterized_docker_build.sh#L282-L316

Let me try and get some base truth (to keep it straight for me, I can be slow and I do not know if what I was reading is correct.)

Ubuntu 18.04 is default Python 3.6, meaning if we move to that as the base we would need to switch the default as part of the DockerFile to Python 2.x for the python 2.x build
Ubuntu 18.04 needs CUDA 9.2
CUDA 9.2 needs device driver 396.26

My current concerns (and I want to upgrade):

Device driver is really new.
Ubuntu 18.04 was just released.

If I made up a random rule or idea.  I would jump to Ubuntu 18.04 with CUDA 10.  That way people just have to upgrade once and off we go.  I still would like to have a second CUDA build but that is not up to me.

Ubuntu 18.04 is default Python 3.6, meaning if we move to that as the base we would need to switch the default as part of the DockerFile to Python 2.x for the python 2.x build

What I should have said above is that the default python3 version in 18.04 went from 3.5 to 3.6.

I think what you are suggesting is the following, just to get the ask 100% correct.

Upgrade both Python 2 and 3 Dockers to Ubuntu 18.04 (which then means CUDA 9.2)
For the Python 2.x Docker we would include command to swap in Python 2.x as the default.

I know this does not help you now, but I am inclined to push for 18.04 for the CUDA 10 release.  Thoughts? dirty looks?

Yes that sounds about right.
What is the timeline for Cuda 10 + support in tf + docker images for Cuda 10? If it's soon, than might be no problem. If could be a while, I'd love to get onto 18.04 without having to wait for that.

My guess is CUDA 10 will be later Q3 or early Q4.  I can see moving to CUDA 9.2 near the end of the cycle in early Q3.  That makes the move to Ubuntu 18.04 not really relevant, and I still think it may be a good time to move to 18.04 as that keeps us in the middle of the cycles  16.04 end of life's April 2021.
How many systems to you manage and are you upgrading them all to Ubuntu 18.04?  That seems aggressive for a production system.  I am going to mark this closed as we will not be accepting the change in the near-term.

We use Docker so upgrading the "system" involves bumping the base Docker image. All we need to do is update the Nvidia driver version on the host. That involves pre-baking an AMI.

Last question, if I install tf from pypi, should it work with Cuda 9.2?

No, the pypi versions are  built against CUDA 9.0.

No, the pypi versions are built against CUDA 9.0.

A few versions later and it is no longer true. TF 1.13.1 uses CUDA 10.0. What if our servers don't have NVIDIA drivers new enough for CUDA 10? What is the newest TF wheel I can still use under CUDA 9.0?
(And a suggestion: why not include CUDA / cuDNN versions in wheel names?)

https://www.tensorflow.org/install/source#linux
tensorflow_gpu-1.12.0
You have no idea how long it took me to find this closed issue and add that link .
I try to keep us on the same CUDA until a major release happens do to driver issues.  NVIDIA keeps getting closer to backward compatibility but it is not there just yet.  Really close and likely kind of working, but I also like to keep it simple even when I get flamed by a minority of people or maybe majority secretly I have no idea.  :-)

@mirekphd
https://www.tensorflow.org/install/source#linux
1.12 was the last on CUDA 9.0
I try to keep us on the same CUDA until a major release comes out.  This results in me getting a decent amount of flames from the interwebs.  NVIDIA is close and kind of has some backwards compatibility working and keepings making it better every quarter.  I have hopes the situation gets better.
I cannot believe I am commenting on an issue closed almost 1 year ago. It took me 30 minutes just to find this issue after seeing it on my phone and then finding the link to the versions on the website.  Time to go home.

@tfboyd : thank you, much appreciated. I ended up installing 1.12.2 from PyPi and it works in the GPU under CUDA 9.0 (<IP_ADDRESS>-1).
Well, Google is the best search engine for closed Github issues, as the closed issues tend to contain more solutions than the open ones, so the closed ones should rank higher:)

I need to get some internet points for commenting on old issues.  I really
am glad you found what you needed.  I read more closed bugs when looking
for answers as well.
*From: *mirekphd<EMAIL_ADDRESS>*Date: *Tue, May 14, 2019, 4:42 AM
*To: *tensorflow/tensorflow
*Cc: *Toby Boyd, Mention
@tfboyd https://github.com/tfboyd : thank you, much appreciated. I ended

up installing 1.12.2 from PyPi
https://pypi.org/project/tensorflow-gpu/1.12.2/ and it works in the GPU
under CUDA 9.0 (<IP_ADDRESS>-1).
Well, Google is the best search engine for closed Github issues, as the
closed issues tend to contain more solutions than the open ones, so the
closed ones should rank higher:)
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
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Is Coded UI going to be supported in Windows 2016 ?

Hi,
Is coded UI going to be supported in Windows 2016, we are having UI automated test case which running fine in Windows8 , Now we need to upgrade to 2016 , wish to know if is test will or not.

@PBoraMSFT Could you answer this?

Coded UI is supported on the platforms that Visual Studio supports. Please refer the system requirements documentation for details - https://docs.microsoft.com/en-us/visualstudio/releases/2019/system-requirements?view=vs-2019.

@PBoraMSFT Thanks!


Too many open files

Denoliver crashes after a few hours with active use.
thread 'main' panicked at 'called `Result::unwrap()` on an `Err` value: Os { code: 24, kind: Other, message: "Too many open files" }', cli/fs.rs:87:15
stack backtrace:
   0: <std::sys_common::backtrace::_print::DisplayBacktrace as core::fmt::Display>::fmt
   1: core::fmt::write
   2: std::io::Write::write_fmt
   3: std::panicking::default_hook::{{closure}}
   4: std::panicking::default_hook
   5: std::panicking::rust_panic_with_hook
   6: rust_begin_unwind
   7: core::panicking::panic_fmt
   8: core::option::expect_none_failed
   9: deno::fs::resolve_from_cwd
  10: deno::permissions::Permissions::resolved_and_display_path
  11: deno::permissions::Permissions::check_read
  12: deno::ops::fs::op_open
  13: deno::state::State::core_op::{{closure}}
  14: deno_core::core_isolate::CoreIsolateState::dispatch_op
  15: deno_core::bindings::send
  16: <extern "C" fn(A0) .> R as rusty_v8::support::CFnFrom<F>>::mapping::c_fn
  17: _ZN2v88internal25FunctionCallbackArguments4CallENS0_15CallHandlerInfoE
  18: _ZN2v88internal12_GLOBAL__N_119HandleApiCallHelperILb0EEENS0_11MaybeHandleINS0_6ObjectEEEPNS0_7IsolateENS0_6HandleINS0_10HeapObjectEEESA_NS8_INS0_20FunctionTemplateInfoEEENS8_IS4_EENS0_16BuiltinArgumentsE
  19: _ZN2v88internalL26Builtin_Impl_HandleApiCallENS0_16BuiltinArgumentsEPNS0_7IsolateE
note: Some details are omitted, run with `RUST_BACKTRACE=full` for a verbose backtrace.
fatal runtime error: failed to initiate panic, error 5
/Users/xxxxxxxx/.deno/bin/denoliver: line 3: 13193 Abort trap: 6           deno "run" "--allow-read" "--allow-net" "https://deno.land/x/denoliver/mod.ts" "$@"

@balzaczyy What Deno version are you using?

@balzaczyy I have a fix up which will come with v2

@joakimunge v1.1.0
Looking forward to v2. 👍


Use updated image names for wheel workflows

The wheels workflow were using some bad image names:

Having the architecture in the image name (or tag name), vs. using platform/arch tag features of docker to use the native architecture of the runner host
Using an unspecified implicit :latest instead of an explicit tag
Lack of detail of the image (which OS, which CUDA version, etc.)

I have since overhauled the naming scheme for wheel-related images; for example, cibuildwheel_x86_64:latest is replaced with its more informative new name, cibuildwheel:cuda-runtime-11.5.1-ubuntu18.04.
It was tested to build cuDF (testing both the pure and manylinux workflows):
https://github.com/rapidsai/pypi-wheel-scripts/actions/runs/3733934876
(this is a custom cuDF build job that points to this branch)
This is a small PR to ensure that existing wheels using @main don't break when I clean up the old invalid image names.
The goal is to cleanly support CUDA 11 and 12 in 23.02, by having the CTK version in the image name. There will be a bigger 23.02 PR which will encompass bigger wheel workflow changes.

These are intentional discrepancies, related to the manylinux environments where we build wheels, and how it influences where we can test wheels:

x86_64 wheels are built on CentOS 7 and tested on Ubuntu 18.04 (libc 2.17 for building, libc 2.27 for testing)
aarch64 wheels are built on Ubuntu 20.04 and tested on Ubuntu 20.04 (libc 2.31 for building and testing)

The total effect is a patchwork of different images available on different architectures, summarized in the cibuildwheel-imgs README:
https://github.com/rapidsai/cibuildwheel-imgs#cibuildwheel-imgs


vc: Remove bind destination when unmounting

virtcontainers.ensureDestinationExists will create the bind destination directory/file, which should be removed properly when unmounting.
Fixes: https://github.com/kata-containers/runtime/issues/1974
Signed-off-by: Li Yuxuan<EMAIL_ADDRESS>

/test

/test

@jodh-intel I have used errors.Wrapf instead of the logger and added a unit test, PTAL :)

/test

/test

Hi @jodh-intel, how can I restart the CI test? I have tried re-pushing and commenting with /test but it seems that both don't work..

/retest

thanks @nitkon . @darfux - you might not have enought 'rights' on the github org to re-trigger. There are maybe three options to re-trigger:

issue a / t e s t or / r e t e s t
issue a / t e s t - u b u n t u or similar if you need to trigger just one CI, and it has an individual trigger phrase
if re-building a single failed test, follow the details link to the Jenkins page for that job, log into Jenkins (it uses your github acct details), and click 'rebuild' for that job. This also requires you have enough 'rights' in the kata github organisation etc.

@grahamwhaley Thanks for the explanation 😀


PR: Improve handling of IPython Console preferences

Description of Changes

[x] Wrote at least one-line docstrings (for any new functions)
[ ] Added unit test(s) covering the changes (if testable)

[x] Included a screenshot or animation (if affecting the UI, see Licecap)

When at least an option needs a restart:

All the options that don't need a restart are applied always
TODO

[ ] Support Completion type hot change (needs change over QtConsole)
[x] Check preferences application when a console is running something (currently execution is interrupted, for example when debugging)

Issue(s) Resolved

Depends on spyder-ide/spyder-kernels#223
Depends on jupyter/qtconsole#451
Fixes #11357
Affirmation
By submitting this Pull Request or typing my (user)name below,
I affirm the Developer Certificate of Origin
with respect to all commits and content included in this PR,
and understand I am releasing the same under Spyder's MIT (Expat) license.

I certify the above statement is true and correct: dalthviz

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

In the file external-deps/spyder-kernels/spyder_kernels/utils/misc.py:

Line 30:1: E302 expected 2 blank lines, found 1

This looks pretty good @dalthviz and I don't have more comments about it. The only thing that worries me a bit is the dialog we'll show to our users to inform them about a change in Preferences, because it's very long and hard to read.
I think we should talk to Isabella in our next meeting about that. What do you say?

Sure :+1:

It looks quite good! A word of advice with comms: using call_kernel(interrupt=True) executes the code immediately and in a thread. You must be careful about thread safety. Matplotlib for example is not thread safe. I marked onr spot in the code where it might be problematic. You have two options if the code is not thread safe:

Call it with (interrupt=False) (the default). It will be executed when coming back to the main prompt (So it won't work while debugging)
use shellwidget.execute(..., hidden=True). This will execute the code at the next prompt, including pdb prompt.

Thanks for the feedback @impact27 ! :+1:

@dalthviz, I think this one is ready, except for a couple of improvements I'm working on. Please don't push more commits to this PR.

Given that users can be working in a long debugging session, I added a message about preferences not being applied in that case:

This is a limitation that we can address in a future PR (to not make this one longer). Perhaps @impact27 could help us with that?


Example in README.md does not compile

In the README there are a few examples showing debug checks of ralloc. One of them doesn't compile for me:

https://github.com/redox-os/ralloc/blob/master/README.md#debug-check-double-free

extern crate ralloc;

fn main() {
    // We start by allocating some stuff.
    let a = Box::new(500u32);
    // Then we memcpy the pointer (this is UB).
    let b = Box::from_raw(&a as *mut u32);
    // Now both destructors are called. First a, then b, which is a double
    // free. Luckily, ralloc provides a nice message for you, when in debug
    // tools mode:
    //    Assertion failed: Double free.

    // Setting RUST_BACKTRACE allows you to get a stack backtrace, so that you
    // can find where the double free occurs.
}

Leads to the following error:
src/main.rs:5:27: 5:41 error: casting `&Box<u32>` as `*mut u32` is invalid
src/main.rs:5     let b = Box::from_raw(&a as *mut u32);
                                        ^~~~~~~~~~~~~~

I somehow expected this not to compile because there was no unsafe block. Is this intended?

I somehow expected this not to compile because there was no unsafe block. Is this intended?

Yeah, the example is wrong. I'll fix it.


feat(controller): acr short-lived token support

Fixes #2372
Needs a lot of TLC

I amended the PR with 655ce12bf8fb0eb0848aefbd6f762088ce58e481
It's some changes to how we configure and initialize the component.
Please do feel free to revert it if you don't like it.

I amended the PR with 17ecfed
It's some changes to how we configure and initialize the component.
Please do feel free to revert it if you don't like it.

This looks great, thanks!

@blakepettersson def more to do still. Wanna keep tag-teaming this til we're both happy with it?

@blakepettersson 🤦♂ I realized my optimization of using the controller's own managed identity to try to discover the tenantID (in case the admin installing Kargo hasn't bothered to provide it) doesn't work in practice...
Because you need to know the tenantID to configure workload identity for the controller itself.
i.e. There is no getting around requiring tenantID to be specified at the time the chart is installed. I will make the requisite simplifications to my previous amendment.

@blakepettersson I've just realized a major issue with the overall approach...
With EKS and GKE, getting a token for ECR or GAR using those platforms' respective workload identity solutions works as long as the controller in question is running in EKS or GKE.
The solution you and I have been going back and forth on here requires the Kargo control plane to be running in AKS since that is where the Project-specific SAs that are federated with each Project's managed identity will reside.
There are reasons this may be a somewhat damning limitation. I'll ping you off-line.

With the realization that this approach requires the Kargo control plane to live in AKS, this isn't going to hold up. I'm going to tentatively close this PR, but we may one day be able to salvage parts of it once we have identified a more acceptable option.


Does this plugin work for flutter web?

Is this supposed to work for flutter web also?
I have managed to get it to display and play an asset video but I am getting some errors... Not sure if it's because it's in a SliverList or just because it doesn't work...

Nope use this: https://pub.dev/packages/video_player_web or with Controls: https://pub.dev/packages/flutter_web_video_player

Hey -- this plugin actually should work just fine for web, but there are a couple caveats:

You must depend on Video Player 0.10.5 and higher
Autoplay will not always work ,since Chrome has disabled autoplay videos when a site first starts. That's why you might see some errors, so make sure to only use autoplay: true when you're not on the "home page" of your app


MiniTool Partition Wizard Crack 12.8 + Serial Key Download [2024]

MiniTool Partition Wizard Crack 12.8 + Serial Key Download [2024]
MiniTool Partition Wizard 12.8 Crack is an impressive application designed to quickly help IT professionals manage disks and partitions on multiple computers. It is developed for the business environment of system administrators and IT professionals who want to work with thousands of computers simultaneously.

It is developed for the business environment of system administrators and IT professionals who want to work with thousands of computers simultaneously.

Download license key Free
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Get error during composer update

Try to update with composer and get the following error after
 - Removing yiisoft/yii2-composer (dev-master 094ffe8)
  - Installing yiisoft/yii2-composer (dev-master ced9e6a)
    Downloading: 100%

[ErrorException]
file_get_contents(): Filename cannot be empty

I just run into this problem today...I run composer update, waited for about 45 mins and realized it wasn't going to work. Tried again about 4 times
I "googled"  found this thread, removed codeception from composer.json and vaala, it worked flawlessly!


DCP 0.7.8 Windows version not working

Hi,
the 0.7.8 Windows version of DCP is not working properly and does nothing.
It seem that the 0.7.8 ZIP archive is missing the node-64.node file.
Others win64 ZIP archives (0.7.5 and <) include this file and these DCP versions are fully fonctionnal.
Using the 0.7.5 node-64 file with 0.7.8 dcp.exe don't work either.
Could you check ?
Best regards.

I confirm that the same thing happens to me.


The maximum 20 upper limit of file number of hot files table is too small for production environment

even in trouble shutting environment.
Recommend a larger number, say 100.

Done

Hi, Huafeng, Can you increate the maximum file number in host files table too?

Now increased to 50


COPY row parser/serializer

Extend postgresql.string to include a means to make COPY rows from a sequence of Python strings or None's. Where None represents NULL. For strings, this would mean properly escaping field content.
Also, include a parser to split and normalize the fields of a given serialized COPY row.
This will only support the traditional tab-separated values

Not sure this would actually be useful.


Nodes with circles as custom images

I'd like to use nodes with a custom image, i.e. without using standard circle (or a transparent circle) and overlaying in top of them a custom image. Or the standard circle, but with a custom image in the center, without the font awesome icon.
Just created a fork, will be proposing a PR soon.

Like this??

@souravprakashjena how the image can fit to the circle ? can you help me please ?


Remove PREFIX variable

Some vars are derived from PREFIX, some are not. This simplifies
by making everything explicit. It removes PREFIX from the code
requirements.

This requires:

A change in SUSE-Cloud/automation
The change in the heat stack #232 .
A rebase when #230 will merge.

As discussed on mumble, I would prefer to use the PREFIX variable everywhere to define the needed resources (like network, servers, volumes, ...)

We'll also need to define keypair by prefix.
I believe this PR should be revised with the input given in our meeting https://github.com/SUSE-Cloud/socok8s/pull/230#issuecomment-480739616 .
I will go back to the drawing board, giving the variable a different name than "PREFIX" (like suggested in the meeting: environment_name or something)

Abandonning this.


New logo/icon

Hi, I am a graphic designer, I want to help others in graphic design.
After I reviewed your project, you have no logo on this project. Therefore I want to contribute to this project by creating a new logo / icon. what do you think?

Hello @mansya,
Thanks for your offer! I guess we didn't put it in the repository, but this was our "logo" we put on the presentation for the hackathon this was made in:

If you want to improve it or suggest a new logo, we'd be happy to take a look!
(P.S. If you are looking for any other projects, my swarms library for the Crazyflie 2.0 could use a logo too!)


quick fix fcn-xs example

this is a quick fix.
Due to the pool/conv shape is changed currently , so the fcn-xs example is broken, such as https://github.com/dmlc/mxnet/issues/2925 https://github.com/dmlc/mxnet/issues/3638 https://github.com/dmlc/mxnet/issues/3634
the reason for this issue should due to the shape before deconv is smaller than old-mxnet-version, so we just make the output shape of deconv bigger than before, i test in on fcn-32 training, and it seems ok.

@tornadomeet so i need to pull the latest version of MXNet, then compile again or something else?

no need compile again,just change some line of symbol_fcnxs.py as this pr does.

I still get this error despite the changes.
For me it is not an error training the system (it is not my intention to do so) but an error using the model to segment certain images.
It works for 95% of the images but for some of them the program crashes.
To evaluate the images I run the example:
fcnxs_args["data"] = mx.nd.array(get_data(fullimagePath), ctx)
data_shape = fcnxs_args["data"].shape
label_shape = (1, data_shape[2]*data_shape[3])
fcnxs_args["softmax_label"] = mx.nd.empty(label_shape, ctx)
exector = fcnxs.bind(ctx, fcnxs_args ,args_grad=None, grad_req="null", aux_states=fcnxs_args)
exector.forward(is_train=False)
output = exector.outputs[0]
and I get the following error:
/home/gabriel/MXNet/mxnet/dmlc-core/include/dmlc/logging.h:235: [22:29:41] src/operator/./crop-inl.h:117: Check failed: (static_cast(param_.offset[0])) <= (data_shape[2]-out_shape[2]) offset[0] should be less than the residual space of height
[22:29:41] /home/gabriel/MXNet/mxnet/dmlc-core/include/dmlc/logging.h:235: [22:29:41] src/engine/./threaded_engine.h:306: [22:29:41] src/operator/./crop-inl.h:117: Check failed: (static_cast(param_.offset[0])) <= (data_shape[2]-out_shape[2]) offset[0] should be less than the residual space of height
An fatal error occurred in asynchronous engine operation. If you do not know what caused this error, you can try set environment variable MXNET_ENGINE_TYPE to NaiveEngine and run with debugger (i.e. gdb). This will force all operations to be synchronous and backtrace will give you the series of calls that lead to this error. Remember to set MXNET_ENGINE_TYPE back to empty after debugging.
terminate called after throwing an instance of 'dmlc::Error'
what():  [22:29:41] src/engine/./threaded_engine.h:306: [22:29:41] src/operator/./crop-inl.h:117: Check failed: (static_cast(param_.offset[0])) <= (data_shape[2]-out_shape[2]) offset[0] should be less than the residual space of height
An fatal error occurred in asynchronous engine operation. If you do not know what caused this error, you can try set environment variable MXNET_ENGINE_TYPE to NaiveEngine and run with debugger (i.e. gdb). This will force all operations to be synchronous and backtrace will give you the series of calls that lead to this error. Remember to set MXNET_ENGINE_TYPE back to empty after debugging.
Aborted (core dumped)
I'm also attaching  the image that makes the system crash

hello, @GMarzinotto  because the model is trained with old version of mxnet, so it may crash when used in the newest mxnet. the model provided will crash with some size of input image with newest mxnet, so you'd better resize the image to a good size(which not crash, should just try)at first

I was wondering if I use not real RGB- image that composed by 3 same gray image ,Can that be worked?

you can convert your old json file into lastest version to solve this problem. there are three deconvolution nodes in this fcn network. Add "adj": "(0, 0)" after "workspace": "" line in the first two deconvolution nodes' params, and add "adj": "(0, 0)" ( I use it and bingo~) or "adj": "(7, 7)" after  "workspace": "" line in the last deconvolution node's params.


Fix NestJS 10 compatibility issues

PR Checklist
Please check if your PR fulfills the following requirements:

[x] The commit message follows our guidelines: https://github.com/nestjs/nest/blob/master/CONTRIBUTING.md
[x] Tests for the changes have been added (for bug fixes / features)
[x] Docs have been added / updated (for bug fixes / features)

PR Type
What kind of change does this PR introduce?

[ ] Bugfix
[ ] Feature
[ ] Code style update (formatting, local variables)
[ ] Refactoring (no functional changes, no api changes)
[ ] Build related changes
[ ] CI related changes
[x] Other... Please describe: Compatibility issue with NestJS 10

What is the current behavior?

Issue Number: #488
What is the new behavior?
Does this PR introduce a breaking change?
[ ] Yes
[x] No

Other information

Replaced the deprecated stuff from @nestjs/core Module in order to fix the compatibility issue with the latest released version 10.0.3.
This only changes the internal implementation of the library and how it extracts the properties from the Module. This can be improved further in the future by renaming the properties of the lib as well to match NestJS names for consistency.

Thanks for the PR @Pedr0Rocha


Request for translating into Chinese

Dear @phil-opp,
Hello!
I'm Luo Jia, a blog author on Rust programming from China. I'm here writing to ask for a permission to translate and repost your article Writing an OS in Rust (Second Edition).
Your nice article has benefited me a lot, and is worth being known by a wide range of readers. What I want to do is to translate the whole series of articles into Chinese and post them onto my blog and special columns(of course with credits, origin authors, licenses, github address and origin article links).  I will spare no effort to polish my words and sentences, to meet up with the origin idea of the article, as well as meet up with the appetite of Chinese readers who wish to read pieces of wonderful article on Rust OS developing in our native language.
If permitted, I will be more than glad.
Yours,
Luo Jia (洛佳)

Hi @luojia65! Thanks for the kind words :).
Translations are fine with me. It's great that the content of this blog will be available to more readers. Thanks for asking for permission!

Thank you for your approval @phil-opp :)
I've done one chapter today in my github repo http://github.com/luojia65/writing-an-os-in-rust

Nice! Let me know if you have any questions!


Added DynamicMap.opts method to apply opts to returned object

When applying opts to a DynamicMap using the .opts method the options sometimes aren't applied correctly. By mapping the applied opts on the DynamicMap the opts are applied directly to the returned Elements. I think the issue may be that the id doesn't get copied or applied correctly, which means that the DynamicMap._style method doesn't apply the options correctly.

Tests are now passing. Merging.


#533 Creates a card with random images

Description
Creation of a new component which displays a random image with card title and card description.

Merged

This is an automated message from Fork, Commit, Merge [BOT].

Thank you for your contribution! Your pull request has been merged. The files have been reset for the next contributor.
What's next?
If you're looking for more ways to contribute, I invite you to check out my other projects. Just click here to find more. These projects contain real issues that you can help resolve. You can also check out the Influences section in the README to find more projects similar to this one.
Also please leave a star to this project if you feel it helped you, i would really appreciate it.
I look forward to seeing your contributions!


Atom-shell dependency with grunt

One of the more annoying parts of getting everything up and running for a developer is getting atom-shell working. This can't be done until #20 is completed.
Luckily, this can be automated with grunt!
This could help: https://github.com/atom/grunt-download-atom-shell
*Note This will probably be a tricky dependency

Joey fixed this


Update dependencies on 03 Navigation

Update dependencies, check if we are using the latest react-router (probably not), if not write a comment on this issue and we can work with you on updating the router version with you (on a different issue and branch)

The following dependencies have been updated: react, react-dom, @types/react, @types/react-dom, file-loader, url-loader, style-loader and webpack.
react-router needs to be updated (from version 3.0.5 to 4.2.0) and also @types/react-router (from 3.0.11 to 4.0.16).

Lo tengo solucionado, pero no he tenido tiempo de subirlo.
Saludos
El El dom, 5 nov 2017 a las 12:44, ebarriosara<EMAIL_ADDRESS>escribió:

The following dependencies have been updated: react, react-dom, , ,
file-loader, url-loader, style-loader and webpack.
react-router needs to be updated (from version 3.0.5 to 4.2.0) and also (from
3.0.11 to 4.0.16).
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You are receiving this because you are subscribed to this thread.
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Looking over these examples today, I am having an issue on the react-router that may be dependency related.  I am getting an error
@types/react-router/index"' has no exported member 'hashHistory'

I have been trying different versions of router and the types.  My current versions are:
react:  16.3.2
react-router: 4.2.0
@types/react-router: 4.0.23

realizing you guys are not the maintainers of react-router or the types, I'm hoping you might have some insights.

@dfmartin Hi, there are breaking changes between react router 3 and 4
Refer to this sample for a version 4 friendly  version, thanks:
https://github.com/Lemoncode/react-by-sample/tree/master/14 ReactRouter


Improve error message of calling unsupported non-"C"/"system"-ABI foreign function

Miri currently reports the following foo() call has ABI-mismatch UB:
#[cfg(unix)]
extern "Rust" { // or any non-"C" ABI
    fn foo();
}

#[cfg(windows)]
extern "C" { // or any non-"system" ABI
    fn foo();
}

fn main() {
    unsafe {
        foo();
    }
}

Output when targeting Linux (and maybe also macOS):
error: Undefined Behavior: calling a function with ABI C using caller ABI Rust
  --> src/main.rs:13:9
   |
13 |         foo();
   |         ^^^^^ calling a function with ABI C using caller ABI Rust
   |
   = help: this indicates a bug in the program: it performed an invalid operation, and caused Undefined Behavio

Output when targeting Windows:
error: Undefined Behavior: calling a function with ABI system using caller ABI C
  --> <anon>:13:9
   |
13 |         foo();
   |         ^^^^^ calling a function with ABI system using caller ABI C
   |
   = help: this indicates a bug in the program: it performed an invalid operation, and caused Undefined Behavior

However, to my knowledge, that's not UB -- it's just unsupported by Miri (and Miri can't assume the function has "C" or "system" ABI since Miri doesn't know about it). I believe that is because of the overzealous check_abi() call before the long match in src/shims/{posix,windows}/foreign_items.rs. The ABI is checked to match the system one ("system" on Windows, "C" otherwise) no matter the callee is recognized as a shim or an unsupported foreign function.

Thanks a lot, looking good. :-)
@bors r+

:pushpin: Commit 7ec919daa4c3e211dd2ef56014a11f967c583013 has been approved by RalfJung

:hourglass: Testing commit 7ec919daa4c3e211dd2ef56014a11f967c583013 with merge 80d6b569547cfb14e6fd8671599da205f7860652...

:sunny: Test successful - checks-actions
Approved by: RalfJung
Pushing 80d6b569547cfb14e6fd8671599da205f7860652 to master...


Currently, subquery is not supported in HAVING clause

I'm using the TPC-H queries you used in your paper, however, when I run query 11 I get this error:
java.sql.SQLException: org.verdictdb.exception.VerdictDBDbmsException: Currently, subquery is not supported in HAVING clause.
	at org.verdictdb.jdbc41.VerdictStatement.executeQuery(VerdictStatement.java:134)
	at com.speedment.example.App.runQuery(App.java:84)
	at com.speedment.example.App.main(App.java:46)
	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.lang.reflect.Method.invoke(Method.java:498)
	at org.codehaus.mojo.exec.ExecJavaMojo$1.run(ExecJavaMojo.java:282)
	at java.lang.Thread.run(Thread.java:748)
Caused by: org.verdictdb.exception.VerdictDBDbmsException: Currently, subquery is not supported in HAVING clause.
	at org.verdictdb.sqlreader.RelationStandardizer.standardize(RelationStandardizer.java:556)
	at org.verdictdb.sqlreader.RelationStandardizer.standardizeSelectQuery(RelationStandardizer.java:103)
	at org.verdictdb.coordinator.ExecutionContext.standardizeSelectQuery(ExecutionContext.java:357)
	at org.verdictdb.coordinator.ExecutionContext.standardizeQuery(ExecutionContext.java:337)
	at org.verdictdb.coordinator.ExecutionContext.standardizeQuery(ExecutionContext.java:332)
	at org.verdictdb.coordinator.ExecutionContext.sqlSelectQuery(ExecutionContext.java:236)
	at org.verdictdb.coordinator.ExecutionContext.sql(ExecutionContext.java:160)
	at org.verdictdb.coordinator.ExecutionContext.sql(ExecutionContext.java:137)
	at org.verdictdb.jdbc41.VerdictStatement.executeQuery(VerdictStatement.java:131)
	... 8 more

The query is this:
select
	ps_partkey,
	sum(ps_supplycost * ps_availqty) as value
from
	partsupp,
	supplier,
	nation
where
	ps_suppkey = s_suppkey
	and s_nationkey = n_nationkey
	and n_name = 'GERMANY'
group by
	ps_partkey having
		sum(ps_supplycost * ps_availqty) > (
			select
				sum(ps_supplycost * ps_availqty) * 0.0001000000
			from
				partsupp,
				supplier,
				nation
			where
				ps_suppkey = s_suppkey
				and s_nationkey = n_nationkey
				and n_name = 'GERMANY'
		)
order by
	value desc;

According to my notes, we used this query instead (by processing the subquery first):
select
  ps_partkey,
  sum(ps_supplycost * ps_availqty) as value
from
  partsupp,
  supplier,
  nation
where
  ps_suppkey = s_suppkey
  and s_nationkey = n_nationkey
  and n_name = 'GERMANY'
group by
  ps_partkey
having
    sum(ps_supplycost * ps_availqty) > 10
order by
  value desc;

I don't guarantee that the current version supports this query since we have disabled some features for better usability (rather than covering every case).


:sparkles: Trigger a manual test on crowd-testing provider TestIO

Type of Change

[ ] Bugfix
[x] Enhancement / new feature
[ ] Refactoring
[ ] Documentation

Description
We want to enable everyone to trigger a manual test on the crowd-testing provider TestIO from a PR.
Checklist

[x] Add relevant labels (for example type of change or patch/minor/major)
[x] Make sure not to introduce some mistakes
[ ] Update documentation
[x] Review the Contributing Guideline and sign CLA
[ ] Reference relevant issue(s) and close them after merging

I have read the CLA Document and I hereby sign the CLA

recheck

@flaxel thanks for your review 🙏 What do you suggest, shall I merge this PR now or wait until I have the approval from Legal to open-source the GHA?

@jreimone I guess it's valid to merge the PR now depending on how urgent it is to bring it to production. 🙌

💙


Adding a parameter to optionally allow debounce to occur without triggering a digest cycle

Also explicitly listing dependencies to comply with strict mode.

Cool, thanks!

Released as v1.1.1

Wow, that was quick! Thank you, @rubenv!


saas config update initialization action no longer exists

Bug Description
In fidesops, on webserver bootup we ran an update "script" for saas configs to pick up any updates coming from a new version of their corresponding templates. See https://github.com/ethyca/fidesops/pull/1307 and associated issue https://github.com/ethyca/fidesops/issues/1098 for more context.
Unless I'm missing something, we seem to have removed this functionality from unified fides. Was there a particular reason for that? We will need this functionality moving forward.

@ThomasLaPiana @pattisdr just looping you in, in case you have any context on whether this was intentional or just an oversight of the merge. i can try to take a stab at adding it back in, just have a couple of things higher on my queue so may take me a bit to get to it

good catch @adamsachs I assume this was just an oversight

I'd also agree it was an oversight, there was code that didn't appear to do anything (tests passed with or without it) so I might've missed reimplementing it, good catch!


Adding content

Loading in the content for the resources and site navigation. This does not include homepage content.

@jbum Looks like we don't have a site preview (perhaps because https://d3vciwww1cf3tt.cloudfront.net/ is a preview itself?), so hopefully I didn't make any major errors in here. I noted a few things to QA I'll check after publishing if all looks good to you.


Node 12 is not supported

error when starting dev server:
contents: result?.code ?? "",
^
SyntaxError: Unexpected token '.'

@chengzhuo5 which version of Node are you running?

@chengzhuo5 Node 12 is EOL since 2022-04-30, so we don't plan to support it. Please update to 16 which is the current stable LTS.


Apply for submitting A Chineses version of markdown

Hello, I'm interested in gocrawl and I want to submit Chinese version of translation of readme. What can I do ? Can I give a PR on that?

Yeah sure, a PR with the translation in a separate markdown file, and a
link to the translation from the readme would be great!
On Thu, May 5, 2022 at 09:38 Vooce @.***> wrote:

Hello, I'm interested in gocrawl and I want to submit Chinese version of
translation of readme. What can I do ? Can I give a PR on that?
—
Reply to this email directly, view it on GitHub
https://github.com/PuerkitoBio/gocrawl/issues/80, or unsubscribe
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Cannot run plan or apply on a confluent_schema_registry_cluster_config which has been imported

Steps to recreate:

Create a Schema Registry in the Confluent Cloud console.
Run an import after exporting the suggested environment variables.
Run a plan. succeeds
Run an apply. fails with the below error

Error: error reading Schema Registry Cluster Config: 403 Forbidden: User is denied operation ReadCompatibility on this server.

Thanks for creating an issue @laurence-hubbard!
Could you share your TF config (more specifically, what TF config did you try to apply)? Also it'd be great to confirm the role of your service account that owns SR API Key.

Thanks for looking into this @linouk23 !
Hopefully this is all the information you requested.
The config:
terraform {
  backend "s3" {
    bucket = "A_BUCKET"
    key    = "A_KEY"
    region = "eu-west-1"
  }
  required_version = "1.3.2"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "3.71.0"
    }
    confluent = {
      source  = "confluentinc/confluent"
      version = "1.26.0"
    }
  }
}

The provider (with OrganizationAdmin role associated to the service account which owns the API key)
provider "confluent" {
  cloud_api_key    = jsondecode(data.aws_secretsmanager_secret_version.confluent_credentials_current.secret_string)["api_key"]
  cloud_api_secret = jsondecode(data.aws_secretsmanager_secret_version.confluent_credentials_current.secret_string)["api_secret"]
}

The service account:
resource "confluent_service_account" "schema_registry_sa" {
  display_name = "betting-services-schena-registry-service-account"
  description  = "Service Account for Betting Services schema registry"
}

The API key:
resource "confluent_api_key" "betting_services_schema_registry" {
  display_name = "betting_services_schema_registry_api_key_${terraform.workspace}"
  description  = "Kafka Schema Registry API Key that is owned by 'tf_runner' service account"

  owner {
    id          = confluent_service_account.schema_registry_sa.id
    api_version = confluent_service_account.schema_registry_sa.api_version
    kind        = confluent_service_account.schema_registry_sa.kind
  }

  managed_resource {
    id          = confluent_schema_registry_cluster.betting_services.id
    api_version = confluent_schema_registry_cluster.betting_services.api_version
    kind        = confluent_schema_registry_cluster.betting_services.kind

    environment {
      id = confluent_environment.env.id
    }
  }

The resource:
resource "confluent_schema_registry_cluster_config" "betting_services" {
  schema_registry_cluster {
    id = confluent_schema_registry_cluster.betting_services.id
  }

  rest_endpoint       = confluent_schema_registry_cluster.betting_services.rest_endpoint
  compatibility_level = "BACKWARD"
  credentials {
    key    = confluent_api_key.betting_services_schema_registry.id
    secret = confluent_api_key.betting_services_schema_registry.secret
  }

  lifecycle {
    prevent_destroy = true
  }
}

nit:
"Kafka Schema Registry API Key that is owned by 'tf_runner' service account"
->
"Schema Registry API Key that is owned by 'betting-services-schena-registry-service-account' service account"

OK so I feel like I know why it returns 403: you're creating a brand new service account (schema_registry_sa) without any roles attached and try to use its SR API Key (that inherits 0 roles from schema_registry_sa) to apply an operation on SR cluster.

So when I try
resource "confluent_service_account" "schema_registry_sa" {
  display_name = "betting-services-schena-registry-service-account"
  description  = "Service Account for Betting Services schema registry"
}

data "confluent_schema_registry_cluster" "betting_services" {
  id = local.schema_registry_id
  environment {
    id = local.env_id
  }
}

resource "confluent_api_key" "betting_services_schema_registry" {
  display_name = "betting_services_schema_registry_api_key_${terraform.workspace}"
  description  = "Schema Registry API Key that is owned by 'tf_runner' service account"

  owner {
    id          = confluent_service_account.schema_registry_sa.id
    api_version = confluent_service_account.schema_registry_sa.api_version
    kind        = confluent_service_account.schema_registry_sa.kind
  }

  managed_resource {
    id          = data.confluent_schema_registry_cluster.betting_services.id
    api_version = data.confluent_schema_registry_cluster.betting_services.api_version
    kind        = data.confluent_schema_registry_cluster.betting_services.kind

    environment {
      id = data.confluent_schema_registry_cluster.betting_services.environment[0].id
    }
  }
}

resource "confluent_schema_registry_cluster_config" "betting_services" {
  schema_registry_cluster {
    id = data.confluent_schema_registry_cluster.betting_services.id
  }

  rest_endpoint       = data.confluent_schema_registry_cluster.betting_services.rest_endpoint
  compatibility_level = "BACKWARD"
  credentials {
    key    = confluent_api_key.betting_services_schema_registry.id
    secret = confluent_api_key.betting_services_schema_registry.secret
  }
}

I can see
│ Error: error reading Schema Registry Cluster Config: 403 Forbidden: User is denied operation ReadCompatibility on this server.
│
│   with confluent_schema_registry_cluster_config.betting_services,
│   on main.tf line 48, in resource "confluent_schema_registry_cluster_config" "betting_services":
│   48: resource "confluent_schema_registry_cluster_config" "betting_services" {

too but

Hi @linouk23 thanks for looking into this! I'll try that and get back to you.

@laurence-hubbard did you get a chance to try it out?

I'm closing this issue for now since my previous comment should help but feel free to reopen it.


Doxygen docs fix

@kiritigowda @randyh62 Adds fix in RPP headers for docs not showing newer arithmetic, logical, audio groups

I think you need to add these files to the INPUT = section of the docs/doxygen/Doxyfile
I see it on line 948 of the file.

@randyh62 The 3 "rppt" header files for audio/arithmetic/logical already seem to be there in ToT
https://github.com/ROCm/rpp/blob/develop/.Doxyfile#L970-L972


Crash on SliceOp during ConstProp

I ran into a problem when I was lowering an ONNX model with the onnx.SliceOp. The end input for the SliceOp is from a constant operator, but the op only contains buffer_id as the attribute instead of the value attr. When calling allocateBufferFor(replacingValue.getType(), /*useMaxSize=*/true), the shape of the type still contains a dynamic dimension (-1). Therefore, it crashes on llvm-project/mlir/lib/IR/BuiltinTypeInterfaces.cpp:33: static int64_t mlir::ShapedType::getNumElements(llvm::ArrayRef<long int>): Assertion 'num >= 0 && "integer overflow in element count computation"' failed.
The backtrace:
#4  0x00005618b8c607fc in mlir::ShapedType::getNumElements(llvm::ArrayRef<long>) ()
#5  0x00005618b825ff20 in onnx_mlir::getNumberOfElements (ty=...) at ../third_party/onnx-mlir/src/Support/TypeUtilities.cpp:48
#6  0x00005618b7c01434 in getMaxSizeInBytes (ty=...) at ../third_party/onnx-mlir/src/Transform/ONNX/ConstPropHelper.cpp:29
#7  0x00005618b7c01775 in allocateBufferFor (type=..., useMaxSize=true) at ../third_party/onnx-mlir/src/Transform/ONNX/ConstPropHelper.cpp:73
#8  0x00005618b7bc21d2 in (anonymous namespace)::ConstPropSlice (rewriter=..., replacingValue=..., constValue=...) at ../third_party/onnx-mlir/src/Transform/ONNX/ConstProp.cpp:822
#9  0x00005618b7bd0ea7 in (anonymous namespace)::SliceofConst::matchAndRewrite (this=0x5618d2faf2d0, op0=0x5618c76027a0, rewriter=...) at third_party/onnx-mlir/src/Transform/ONNX/ONNXConstProp.inc:1814
#10 0x00005618b8973f0d in mlir::PatternApplicator::matchAndRewrite(mlir::Operation*, mlir::PatternRewriter&, llvm::function_ref<bool (mlir::Pattern const&)>, llvm::function_ref<void (mlir::Pattern const&)>, llvm::function_ref<mlir::LogicalResult (mlir::Pattern const&)>) ()
#11 0x00005618b8953914 in mlir::applyPatternsAndFoldGreedily(llvm::MutableArrayRef<mlir::Region>, mlir::FrozenRewritePatternSet const&, mlir::GreedyRewriteConfig) ()
#12 0x00005618b7bfe777 in mlir::applyPatternsAndFoldGreedily (op=0x5618bdbf3c90, patterns=..., config=...)
    at ../third_party/llvm_build_rtti/include/mlir/Transforms/GreedyPatternRewriteDriver.h:71
#13 0x00005618b7bd53b4 in (anonymous namespace)::ConstPropONNXToONNXPass::runOnOperation (this=0x5618d7e1b2e0) at ../third_party/onnx-mlir/src/Transform/ONNX/ConstProp.cpp:1080
#14 0x00005618b8a36683 in mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) ()
#15 0x00005618b8a36ae0 in mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) ()
#16 0x00005618b8a35cee in mlir::detail::OpToOpPassAdaptor::runOnOperationAsyncImpl(bool) ()
#17 0x00005618b8a3672d in mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) ()
#18 0x00005618b8a36ae0 in mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) ()
#19 0x00005618b8a37568 in mlir::LogicalResult llvm::function_ref<mlir::LogicalResult (mlir::OpPassManager&, mlir::Operation*)>::callback_fn<mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int)::{lambda(mlir::OpPassManager&, mlir::Operation*)#1}>(long, mlir::OpPassManager&, mlir::Operation*) ()
#20 0x00005618b7b71024 in llvm::function_ref<mlir::LogicalResult (mlir::OpPassManager&, mlir::Operation*)>::operator()(mlir::OpPassManager&, mlir::Operation*) const (
    this=0x5618bd7f9ab0, params#0=..., params#1=0x5618bd8212a0) at ../third_party/llvm/build/include/llvm/ADT/STLFunctionalExtras.h:68
#21 0x00005618b7b70f13 in mlir::Pass::runPipeline (this=0x5618bd7f9a40, pipeline=..., op=0x5618bd8212a0) at ../third_party/llvm/build/include/mlir/Pass/Pass.h:195
#22 0x00005618b7b6fe1c in (anonymous namespace)::ONNXOpTransformPass::runOnOperation (this=0x5618bd7f9a40) at ../third_party/onnx-mlir/src/Transform/ONNX/ONNXOpTransformPass.cpp:143
#23 0x00005618b8a36683 in mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) ()
#24 0x00005618b8a36ae0 in mlir::detail::OpToOpPassAdaptor::runPipeline(mlir::OpPassManager&, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int, mlir::PassInstrumentor*, mlir::PassInstrumentation::PipelineParentInfo const*) ()
#25 0x00005618b8a37091 in mlir::PassManager::run(mlir::Operation*) ()

@Connor-XY Is it possible to share more information, for example, the onnx model or a simplified onnx model that caused the issue?

When I called onnx-mlir --EmitONNXIR demo.onnx: demo.onnx.zip

I had a look at this one, ran
Debug/bin/onnx-mlir --EmitONNXIR demo.onnx --mlir-print-ir-before-all

and saw
// -----// IR Dump Before (anonymous namespace)::ConstPropONNXToONNXPass //----- //
func.func @main_graph() -> tensor<1x?x10xf32> attributes {input_names = [], output_names = ["slice_output"]} {
  %0 = "onnx.Constant"() {onnx_node_name = "slice_input_node", value = dense<[[[0.520462155, 0.00670582382, 0.871590495, 0.278036267, 0.828379154, 0.884337306, 0.831121981, 0.0893977284, 0.744317293, 0.102747507], [0.856175541, 0.944557726, 0.764496624, 4.865840e-02, 0.600022614, 0.192868724, 0.394807339, 0.968071341, 0.557405055, 0.694378912], [0.880413771, 7.508500e-01, 2.815850e-01, 0.906873285, 0.284533083, 0.138220295, 0.880515933, 0.127991736, 0.0183662809, 0.135350332], [0.865618288, 0.142144546, 0.909440398, 0.540245831, 0.875361681, 0.583869696, 0.327232182, 4.788000e-01, 0.45420298, 0.228400692], [0.427994877, 0.786098182, 0.210147008, 0.512648523, 0.586023569, 0.632613182, 0.260696024, 0.744115173, 8.993780e-01, 0.115426958], [0.656477391, 0.43133384, 0.729191184, 0.0762675256, 0.881418943, 0.147667527, 0.77742511, 0.414225638, 0.499662846, 0.020333793], [0.139379546, 0.459841907, 0.800156355, 0.886660754, 0.317004055, 0.41094026, 0.71376419, 0.0406609811, 0.975891649, 0.858624577], [0.045160342, 0.140623972, 0.262190819, 0.734084606, 0.235340491, 0.123527125, 0.872684121, 0.821631491, 0.64323765, 0.543907702], [0.361088395, 0.140764505, 0.865229189, 0.845452487, 0.893362164, 0.49910304, 0.614656388, 0.851889789, 0.42633155, 0.203791946], [0.842561841, 0.789542675, 0.759935796, 0.522347629, 0.441621631, 0.973008036, 0.0219843164, 0.736513138, 0.4523049, 0.438298196]]]> : tensor<1x10x10xf32>} : () -> tensor<1x10x10xf32>
  %1 = "onnx.Constant"() {onnx_node_name = "start_input_node", value = dense<0> : tensor<1xi64>} : () -> tensor<1xi64>
  %2 = "onnx.Constant"() {onnx_node_name = "axis_input_node", value = dense<1> : tensor<1xi64>} : () -> tensor<1xi64>
  %3 = "onnx.Constant"() {onnx_node_name = "step_input_node", value = dense<1> : tensor<1xi64>} : () -> tensor<1xi64>
  %4 = "onnx.Constant"() {onnx_node_name = "indices_input_node", value = dense<1> : tensor<1xi64>} : () -> tensor<1xi64>
  %5 = "onnx.Constant"() {onnx_node_name = "unsqueeze_axes_input_node", value = dense<0> : tensor<1xi64>} : () -> tensor<1xi64>
  %6 = "onnx.Constant"() {value = dense<[2, 3, 4]> : tensor<3xi64>} : () -> tensor<3xi64>
  %7 = "onnx.Gather"(%6, %4) {axis = 0 : si64, onnx_node_name = "gather_node"} : (tensor<3xi64>, tensor<1xi64>) -> tensor<1xi64>
  %8 = "onnx.Unsqueeze"(%7, %5) {onnx_node_name = "unsqueeze_node"} : (tensor<1xi64>, tensor<1xi64>) -> tensor<1x1xi64>
  %9 = "onnx.Slice"(%0, %1, %8, %2, %3) {onnx_node_name = "slice_node"} : (tensor<1x10x10xf32>, tensor<1xi64>, tensor<1x1xi64>, tensor<1xi64>, tensor<1xi64>) -> tensor<1x?x10xf32>
  return %9 : tensor<1x?x10xf32>
}

I think the problem is that during shape inference the ends input wasn't constant and therefore the inferred output shape of Slice has an unknown dim size. The ends input only becomes constant in the course of constant propagation. A hack to get around it is to run shape inference on SliceOp during constant propagation:
diff --git a/src/Transform/ONNX/ConstProp.cpp b/src/Transform/ONNX/ConstProp.cpp
index 6bc0ceaa..c709f40c 100644
--- a/src/Transform/ONNX/ConstProp.cpp
+++ b/src/Transform/ONNX/ConstProp.cpp
@@ -805,6 +805,11 @@ ONNXConstantOp ConstPropSlice(
   Operation *op = replacingValue.getDefiningOp();
   ONNXSliceOp sliceOp = cast<ONNXSliceOp>(op);

+  if (failed(sliceOp.inferShapes([](mlir::Region &) {}))) {
+    sliceOp.emitOpError("failed to infer shapes");
+    return nullptr;
+  }
+
   ArrayRef<int64_t> inputShape = getShape(constValue.getType());

I tried that but shape inference crashed because of a second problem: the input to Slice is malformed as the ends argument is not a 1-D tensor (shouldn't have been unsqueezed). We could implement a verify() method for Slice to catch that.
Moreover, it's probably impossible for shape inference to see the value of ends when Gather and Unsqueeze are not constant propagated and therefore

@sorenlassen thanks for the investigation!
If ends is not a constant we cannot come to the code  in ConstProp.cpp, since we have a guard in ConstProp.td:
def SliceofConst :  Pat<
    // From Slice (x, starts, ends, axes, steps)
    (ONNXSliceOp:$resOp (ONNXConstantOp:$input $_, $_, $_, $_, $_, $_, $_, $_),
                        $starts, $ends, $axes, $steps),
    // To c' where c' is the sliced value.
    (CreateSliceOfConst $resOp, $input),
    [(IsFromDenseONNXConstantOp:$input), (IsFromDenseONNXConstantOp:$starts),
     (IsFromDenseONNXConstantOp:$ends), (IsFromDenseONNXConstantOpOrNone:$axes),
     (IsFromDenseONNXConstantOpOrNone:$steps)]>;

I think the reason is that the input to Slice is malformed as the ends argument is not a 1-D tensor (shouldn't have been unsqueezed)

This is exactly the issue I think. The type of ends must be tensor<1xi64> instead of tensor<1x1xi64>

We could implement a verify() method for Slice to catch that.

Agree.

@Connor-XY would you be able to add this test to the verify? It should test that the end has a rank of 1. If you do so, please make sure to test it for the other inputs if the same constraint hold on them.

I will implement the test and see if that works.

If ends is not a constant we cannot come to the code in ConstProp.cpp

yes but I'm guessing that it wasn't a constant yet during the preceding shape inference pass (see the IR dump before ConstPropONNXToONNXPass that I posted) and then during constant propagation a cascading set of constant propagations  made the ends input constant but that hadn't been taken into account during shape inference and therefore the inferred shape has an unknown dim size - this is why I thought my hack to re-run inferShapes on sliceOp in ConstProp could address this part of the problem
alternatively, if we are ok with constant propagation giving up in this situation instead of crashing, the guard in ConstProp.td c could be expanded to require that the output type doesn't have unknown dim size

Oh, so you are saying that ends is a constant but that the constant has not reached yet?
In general, we return success when inputs do not have yet a rank and shape, see the tests in shape inference. You can do the same, and eventually, it will converge and the op will be processed, or if it is never processed, then I believe the pass will eventually fails.
@chentong319 can chime in if my recollection is erroneous.

I changed from tensor<1x1xi64> to tensor<1xi64>, but still could observe the error:
demo.onnx.zip

I changed from tensor<1x1xi64> to tensor<1xi64>, but still could observe the error:
demo.onnx.zip

@Connor-XY after you changed the tensor shape  I suggest you try the hack to run shape inference on SliceOp during constant propagation:
diff --git a/src/Transform/ONNX/ConstProp.cpp b/src/Transform/ONNX/ConstProp.cpp
index 6bc0ceaa..c709f40c 100644
--- a/src/Transform/ONNX/ConstProp.cpp
+++ b/src/Transform/ONNX/ConstProp.cpp
@@ -805,6 +805,11 @@ ONNXConstantOp ConstPropSlice(
   Operation *op = replacingValue.getDefiningOp();
   ONNXSliceOp sliceOp = cast<ONNXSliceOp>(op);

+  if (failed(sliceOp.inferShapes([](mlir::Region &) {}))) {
+    sliceOp.emitOpError("failed to infer shapes");
+    return nullptr;
+  }
+
   ArrayRef<int64_t> inputShape = getShape(constValue.getType());

That will tell us whether the root of the problem is that constant propagation made the ends input constant but works off stale shape inference for the output type that didn't take the constant input into account.

Actually, please ignore my inferShapes hack. It doesn't make sense. ONNXSliceOpShapeHelper is called later in the method and, if anything, we could get the static output shape (no unknown dim sizes) from there, except that the "BUFFER_ID_ATTR" logic in ConstProp.cpp opens another can of worms. I tried to work through that but it becomes really messy and, at best, we'd end up with a propagated constant with a type with dynamic dim size (because I don't think constant propagation is allowed to change the result shape).
The simplest "solution" seems to be to restrict the SliceofConst pattern in ConstProp.td to only fire when the output shape is static, and then you could run another shape inference pass and constant propagation pass to push the constant propagation through SliceOp.

I examined the model and found that the problem was because of that ends was produced during the constant propagation, so it is a constant linked with a buffer. That buffer-linked constant is only meaningful in the constant propagation context and does not work with shape inference, while constant propagation for SliceOp called shape inference to compute starts, ends, axes.
I will provide a fix for this. Thanks for reporting an interesting bug!

AFAICT, trying to fix the buffer-linked constant only opens another can of worms. You can see my experiments here: https://github.com/sorenlassen/onnx-mlir-einsum/commit/fb0152a6874717717ea3b4976d3819437d5fc673

@Connor-XY please feel free to reopen this issue if you still see the error. Thanks!


Move to parameterized tests

To ease addition of new features and tests, move the ginkgolinter tests to be parameterized tests.

Pull Request Test Coverage Report for Build<PHONE_NUMBER>

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage increased (+0.6%) to 88.198%

Totals

Change from base Build<PHONE_NUMBER>:
0.6%

Covered Lines:
553

Relevant Lines:
627

💛  - Coveralls


Add CONTRIBUTORS.md file

Add CONTRIBUTORS.md file with the following content:
This is a list of our valued CONTRIBUTORS, who with a lot of effort and dedication have submitted code patches, reported bugs, written documentation, resolved doubts for newbies and who have generally made this a better project:
Guzman D. Darío<EMAIL_ADDRESS>
P.D: Please add yourselves as collaborators in the next Pull Request you make

Solved


BAH-1715 | list-of-patients-with-missed-appointments

BAH-1715 | list-of-patients-with-missed-appointments

Please review @gsluthra @N0-man


Improve test coverage for time.ts

I removed the last 2 tests here because they relied on system time and would intermittently fail. Need to figure out a better way to test FakeTime.
https://github.com/udibo/mock/blob/a22be7fe275697da87fb534e0c92c398eade28d7/time_test.ts#L303-L360

I attempted to resolve the issue but the test would still intermittently fail on MacOS on GitHub actions. The failures were always related to it iterating forward faster than dictated by my delays. See the commits from that PR for more information about what I tried.
Open to suggestions on how to get test coverage for this behavior to be reliable in CI.


Add or document support for Webpack HMR

Issue type:

[x] question
[ ] bug report
[ ] feature request
[x] documentation issue

nestjs-config version
1.3.21
@nestjs/common+core or other package versions

@nestjs/common: 6.1.0
@nestjs/core: 6.1.0

Excepted behavior
Actual behavior or outcome (for issue)
Library worked great for me on a different project.  I want to use this library with a new project, but this time I am trying to use the Webpack HMR capabilities to make the app reload a lot faster.  Since Nest ships with this out-of-the-box would it be nice to have some kind of recipe for supporting this flow?
I'm not familiar with the internals of this library so not sure if it's even possible to be honest.  It would be really handy to be able to use this library with HMR though!
Replication/Example

ConfigModule.resolveRootPath(__dirname).load('config/**/!(*.d).{ts,js}')

Works using yarn start with ts-node.  Doesn't work with yarn start:hmr.  The module initializes but no configuration is being read.  Likely because all of the configuration is being appended into the server.js and is no longer in a config folder.

Hmm this is interesting. Personally I'm always using containers so I just mount an env file and run everything there. I've never really used hmr or webpack package commands.
Since writing the above paragraph I install a new nest v6.1.1 application, I checked package.json for start:hmr and webpack and I think it's since been removed? In an older version hmr looked to be using a dist/service file/folder? Are you still using this functionality with v6? If so do you have an example I can look at and see why it doesn't load configs?
Thanks! :)

Okay so I played around with this a bit more.  Apparently I have an old version of the cli installed and at some point in the last few months Nest removed Webpack from it's typescript-starter repo you get when you run the nest new command.
I wouldn't call this a bug per-se since Nest seems to have abandoned using the HMR (I personally thought it was pretty neat compared to using ts-node.)  That being said if you want to investigate anyway all you really need to do is clone version 5 of the starter here.  Once that's cloned up just bootstrap an MVP nestjs-configsetup and you'll immediately see that it doesn't work with Webpack.
So not sure the internals of this library but it seems like since everything gets compiled into a dist/server.js as opposed to all of the .ts files being compiled and copied over separately.  The problem then probably stems from the fact that since we dynamically require the .ts files Webpack probably doesn't pick them up and bundle them into the server.js.
I tried messing around with it to compile and copy the config folder over but didn't have any luck.  It's definitely an interesting problem though because I personally thought the HMR was pretty useful.
Hopefully that gives you some detailed info, like I said it's probably not something you need to worry about but I think it would be cool if it worked :)

oh I see! So it's more about the file type than the .env file. I was presuming webpack loaded it's own dotenv package and was loading from a different dir or something like that but it sounds like this is more file type related.
I will try and investigate. My time is rather limited at the moment though as I'm working 2 jobs and still got to release V2! If I can find some time to investigate this in the next month or 2 I will. I'll try and get V2 published first though! After that I'll defo have a look into it!

Your library is excellent. And I do not want to give it up.
But this library has a problem with the Webpack HMR capabilities.
When can we expect a bug fix?

I looked into this and it doesn't appear to be possible to use Webpack HMR with this package. nestjs-config tries to load files at runtime after Webpack has transpiled and bundled everything into a single file.
I ended up rolling my own ConfigService based on https://docs.nestjs.com/techniques/configuration so everything would work with HMR.

@marktran, can you share your configuration file?

@OLDIN
import path from 'path';
import { Module, Global } from '@nestjs/common';
import { ConfigService } from './config.service';

import { ROOT_PATH } from '../constants';
const NODE_ENV = process.env.NODE_ENV || 'development';

@Global()
@Module({
  providers: [
    {
      provide: ConfigService,
      useValue: new ConfigService(
        path.resolve(ROOT_PATH, '..', `.env.${NODE_ENV}`),
      ),
    },
  ],
  exports: [ConfigService],
})
export class ConfigModule {}

import _ from 'lodash';
import dotenv from 'dotenv';
import fs from 'fs';
import joi from '@hapi/joi';

import { RedisModuleOptions } from '../redis/redis.interface';
import { TypeOrmModuleOptions } from '@nestjs/typeorm';

import { databaseOptions } from './database.config';
import { redisOptions } from './redis.config';
import { graphQLOptions } from './graphql.config';
import { GqlModuleOptions } from '@nestjs/graphql';

export interface EnvConfig {
  [key: string]: string;
}

export class ConfigService {
  private readonly envConfig: EnvConfig;

  constructor(filePath: string) {
    let config: EnvConfig;

    if (process.env.DATABASE_URL) {
      config = process.env;
    } else {
      config = dotenv.parse(fs.readFileSync(filePath));
    }

    this.envConfig = this.validateInput(config);
  }

  public get(name: string): string {
    return this.envConfig[name];
  }

  getDatabaseOptions(): TypeOrmModuleOptions {
    return databaseOptions(
      this.envConfig.NODE_ENV,
      this.envConfig.DATABASE_URL,
      this.envConfig.TYPEORM_DROP_SCHEMA,
      this.envConfig.TYPEORM_LOGGING,
    );
  }

  getRootDomain(): string {
    const parts = this.get('HOSTNAME').split('.');
    return _.takeRight(parts, 2).join('.');
  }

  getRedisOptions(): RedisModuleOptions {
    return redisOptions(this.envConfig.NODE_ENV, this.envConfig.REDIS_URL);
  }

  getGraphQLOptions(): GqlModuleOptions {
    return graphQLOptions(
      this.envConfig.NODE_ENV,
      this.envConfig.FRONTEND_HOSTNAME,
    );
  }

  private validateInput(envConfig: EnvConfig): EnvConfig {
    const envVarsSchema: joi.ObjectSchema = joi.object({
      AIRTABLE_API_KEY: joi.string().required(),
      AIRTABLE_SALES_CRM_BASE_ID: joi.string().required(),
      DATABASE_URL: joi.string().required(),
      FRONTEND_HOSTNAME: joi.string().required(),
      GOOGLE_AUTH_CLIENT_ID: joi.string().required(),
      GOOGLE_AUTH_CLIENT_SECRET: joi.string().required(),
      HOSTNAME: joi.string().required(),
      NODE_ENV: joi
        .string()
        .valid(['development', 'test', 'production'])
        .default('development'),
      PORT: joi.number().default(5000),
      README_JWT_SECRET: joi.string().required(),
      REDIS_URL: joi.string().required(),
      SENTRY_DSN: joi.string().allow(''),
      SENTRY_ENV: joi.string().allow(''),
      SESSION_SECRET: joi.string().required(),
      TYPEORM_DROP_SCHEMA: joi.boolean().default(false),
      TYPEORM_LOGGING: joi.boolean().default(false),
    });

    const { error, value: validatedEnvConfig } = joi.validate(
      envConfig,
      envVarsSchema,
      { stripUnknown: true },
    );

    if (error) {
      throw new Error(`Config validation error: ${error.message}`);
    }

    return validatedEnvConfig;
  }
}

@marktran @OLDIN what version of nest are you using? Just curious to know if you're using v6+ as HMR has been removed apparently? (not sure if that's still the case).
Looking to add validation into nestjs-config V2 but I don't want to only use a specific package like joi as someone else might want to use something different. How would you like to use the validation? Could implement decorators but not sure if that's a good idea, would be nice or whatever.
As for the loading of configs though, yea I only built this for prod envs really, at the time. It would be possible to implement HMR support, because the ConfigService builds this statically it might be an idea to rebuild at some point. I think the issue is that the nestjs-config package, like you said, loads the files at runtime and therefore doesn't change it's dependants. I'll have a think about the best way to combat this. Currently in V2 I have implemented everything for async providers. This obviously doesn't fix the issue as these are still created at runtime and not rebuilt.

@bashleigh I'm on the latest version of Nest. Not sure what HMR integration looked like in previous versions but it must have been pretty minimal (see: https://docs.nestjs.com/techniques/hot-reload).

Having exact same issue here. It is unable to find config. Using version nestjs-config 1.4.0

Hi,
This is issue is related to how config files are loaded.
For e.g.
 ConfigModule.load(path.resolve(__dirname, 'config', '**/!(*.d).{ts,js}')),
Will load config files in dynamic way, and because of that, webpack doesn't know that those file are required by application.
I made some small hack in library (just for testing), so i can load config data as object, and configuration objects  are imported like all others packages.
import appConfig from "./config/app";

@Module({
  imports: [
    // ConfigModule.load(path.resolve(__dirname, 'config', '**/!(*.d).{ts,js}')),
    ConfigModule.load({
      "app" : appConfig
    }),
    ...modules
  ],
  controllers: [],
  providers: [],
})
export class AppModule {}

That allows webpack to resolve config dependencies, and everything works as expected.

Hi,
I think this issue is related to dynamic path which are used to load config files.
ConfigModule.load(path.resolve(__dirname, 'config', '**/!(*.d).{ts,js}')),
Because of that, webpack doesn't know that file in config dir are required, and those are not merged/copied into webpack bundles in "dist" dir, which later on is used for hot reloading etc.
Possible way for overcome this is use of absolute path to config dir, for e.g.
ConfigModule.load(path.resolve("/var/www/project-dir/src/config/**/!(*.d).{ts,js}"))
Other way (im not sure, not tested) is to use webpack copy plugin, to copy config dir into correct location in "dist"
Hope it helps you a little bit,
@dhaspden  @bashleigh  @OLDIN  @marktran  @abhishekdubey1

@Isurm

Hi,
I think this issue is related to dynamic path which are used to load config files.
ConfigModule.load(path.resolve(__dirname, 'config', '**/!(*.d).{ts,js}')),
Because of that, webpack doesn't know that file in config dir are required, and those are not merged/copied into webpack bundles in "dist" dir, which later on is used for hot reloading etc.
Possible way for overcome this is use of absolute path to config dir, for e.g.
ConfigModule.load(path.resolve("/var/www/project-dir/src/config/**/!(*.d).{ts,js}"))
Other way (im not sure, not tested) is to use webpack copy plugin, to copy config dir into correct location in "dist"
Hope it helps you a little bit,
@dhaspden @bashleigh @OLDIN @marktran @abhishekdubey1

No, the issue is that webpack compresses the entire project into a single js file so you no longer have config/*.js files to load into ConfigModule


Custom Visual API Version supported ?

I remember there was a discussion to add the information what version of the custom visual api is supported in a PBIRS release, would it be possible to add this information in the changelog as well ?

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

ID: ef9c2df3-28df-34d8-bd4e-4209996f7f8d
Version Independent ID: e5dc42c8-b17a-4e0e-09c5-76124b0ad924
Content: Change log for Power BI Report Server - Power BI
Content Source: powerbi-docs/report-server/changelog.md
Service: powerbi
Sub-service: powerbi-report-server
GitHub Login: @jtarquino
Microsoft Alias: jaimeta

Thanks for your comment, @nojetlag.
I've assigned this issue to the doc author for review.

Hi, @nojetlag -- the Custom Visual API version number is in the Power BI Report Server What's new article, https://docs.microsoft.com/power-bi/report-server/whats-new#power-bi-visuals-api
Hope that helps!


Guard for null result from ClangModuleUnit::getClangModule().

The documentation for this method states that this can return null if
the module unit represents [the] imported headers.
We have a crash report on dereferencing the result of this function
farther down, and I suspect it's hitting exactly that
case. Unfortunately we only have a back trace and no test case.
Fixes: rdar://problem/41888568
(cherry picked from commit f94d6535309c9c6a3f3986dcdaf5d8f168841cd0)

@swift-ci Please test

@swift-ci nominate

I opened https://github.com/apple/swift/pull/18370 as an even safer alternative to this change, which originally went into master.

Okay after talking with @jrose-apple, the original change should be just as safe and is somewhat more clear so we'll leave this alone.


Separate each kind of error and warning.

I distinguish the error and warning in the program in detail, so that my program can accurately capture errors and warnings and give feedback to the user.
Even though I don't change anything, unittest still throws an error and I don't know why.
This PR adds:
Errors:

CameraAdjustmentError
InvalidMaskIndexError
InvalidArgumentError
NoMatchExceedsThresholdError
HomographyEstimationError
InvalidContourError
RectanglesNotOverlapError
ResolutionMismatchError
InsufficientImagesError
ImageReadError

Warnings:

IdenticalColorsWarning
ImagesNotFullIncludedWarning

you mean that you need more detailed information on where a StitchingError/Warning occur?

you mean that you need more detailed information on where a StitchingError/Warning occur?

yeah.
I want to use stitching as the backend of an image processing website, so I want to capture more detailed errors and warnings for user feedback.

while I understand that this information is important, I don't like the idea of creating a new Error for each possible exception.
We could maybe introduce error codes so you know better what failed as e.g. in https://stackoverflow.com/questions/6180185/custom-python-exceptions-with-error-codes-and-error-messages

while I understand that this information is important, I don't like the idea of creating a new Error for each possible exception. We could maybe introduce error codes so you know better what failed as e.g. in https://stackoverflow.com/questions/6180185/custom-python-exceptions-with-error-codes-and-error-messages

Compared to create a new Error for each possible exception, using error code is more elegant, I will optimize my code.
I'm a beginner, thanks for your advice!!!

@Luthics are you still working this or can we close the PR?

@Luthics are you still working this or can we close the PR?

I'm sorry for taking up so long, my college has started, there are more things, I try to finish it in this week.

We don't really need this, so just continue if its important to you


AsyncDelegate is not a member of AsyncResult

You need to indicate the versions of .NET this rocket science works in. I'm using 4.7.2.

Document Details
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ID: 17acbfb3-4b90-a358-0417-2975f2475db4
Version Independent ID: a6a6845f-e7cf-8c6f-65a8-04ed09f64a1e
Content: Calling Synchronous Methods Asynchronously
Content Source: docs/standard/asynchronous-programming-patterns/calling-synchronous-methods-asynchronously.md
Product: dotnet
GitHub Login: @rpetrusha
Microsoft Alias: ronpet

I was using System.IdentityModel instead of System.Runtime.Remoting.Messaging.


add /settings endpoint

It would be helpful if we could use the /settings endpoint in core, cause we are using the response (e.g. tag colors) in a lot of places.
Example payload:
{
"user_id": "user-id",
}

Would also be nice if this api returns the FacebookAppId that is configured in the airy.conf. That way the person installing it only has to configure it in one place.


[Bug] Metrics' names shouldn’t be allowed to contain spaces

Is there an existing issue for this?

[X] I have searched the existing issues

Current Behavior
I'm working on macros to generate SQL to calculate metrics, and want to be able to use metric.name as the column alias. I just discovered that they're allowed to contain spaces - I don't know if this was intentional or not considered, but I think it's bad when there's a human-readable label available as well.
Expected Behavior
slack users to be rejected because it's not [_A-Za-z] (or maybe even just [_a-z]?)
Steps To Reproduce
metrics:
    - name: slack joiners
      label: Members of Community Slack
      model: dim_slack_users_2

Relevant log output
No response
Environment
- dbt: 1.0.0

What database are you using dbt with?
snowflake
Additional Context
No response

I think that this was an oversight. We'll discuss what we'd like to accept for the metrics name and fix this.

@jtcohen6 is the exit criteria here just to prohibit spaces in metric names?

My preference would be to constrain it pretty severely - right now I'm passing the metric name directly in as a column alias. For example, even the metrics that our internal data team has made will be problematic, cos they're using periods:
  - name: okr_1.2.0__new_verified_accounts_activated
    label: New Verified Accounts Activated
    model: ref('fct_cloud_accounts')
    description: '{{ doc("okr_new_verified_accounts_activated") }}'
...

Ideally it should be just stuff that's legal in a column name (which also has implications around whether a metric's name can start with a digit).
Alternatively, I can tidy up the column alias myself, but that could cause conflicts with any low-code tools built on top of the metrics package that will need to know how to find the resulting column.


Add publish to Crates.io step in the release workflow.

We would also need to set CARGO_API_KEY in the repository secrets with the Crates.io key

Closed in favor of #492


proposal: testing: reuse the iteration number of the first round when count > 1

We often run all benchmarks of std packages with -count=5 or higher, it usually takes 5-6 hours to finish on our x86 and arm64 servers, the overall turnaround time might be reduced a lot if we can skip the auto adjustment from round #2 and reuse the iteration number computed before.
With an experimental change I got the following numbers:
                                    old                                 new
package math/big            2865.780s                              2242.640s
package runtime              5936.460s                              4926.073s
package encodng/json     486.691s                                321.370s

I realized same attempt was made before but then dropped due to benchmark regressions reported in https://github.com/golang/go/issues/25622, a change to computing the 'grain' value of RunParallel proposed in https://github.com/golang/go/issues/37996 shall avoid the regression. Furthermore this feature could be guarded by an option if necessary.

I believe this is now possible with<EMAIL_ADDRESS>scheduled for go1.24.


Updated goscaleio for re-auth loop fix

This commit adds a fix for ScaleIO where bad creds would cause
a re-authentication loop.

Coverage remained the same at 91.846% when pulling 3aa4b9fb2578022687ef142444bd20ee570bc9ec on clintonskitson:bugfix/scaleio_reauth_loop into ed77cb2b78b708e4e9d54122419636bc0023f000 on emccode:release/0.3.3.

Hi @clintonskitson,
If this is a goscaleio patch, why are there changes in the ec2 driver's imports section?

Eh, it appears to be a formatting issue.