October point release 1

Codecov Report

Merging #8156 into release will increase coverage by 0.35%.
The diff coverage is n/a.

@@             Coverage Diff             @@
##           release    #8156      +/-   ##
===========================================
+ Coverage    58.73%   59.09%   +0.35%
===========================================
  Files          498      498
  Lines        22386    22386
  Branches      3603     3608       +5
===========================================
+ Hits         13149    13229      +80
+ Misses        8393     8320      -73
+ Partials       844      837       -7

Impacted Files
Coverage Δ

src/client/common/utils/platform.ts
76.47% <0%> (ø)
:arrow_up:

src/client/datascience/constants.ts
100% <0%> (+0.34%)
:arrow_up:

src/client/common/process/proc.ts
14.84% <0%> (+1.56%)
:arrow_up:

src/client/interpreter/locators/helpers.ts
73.17% <0%> (+2.43%)
:arrow_up:

src/client/language/characters.ts
33.33% <0%> (+2.56%)
:arrow_up:

src/client/common/utils/version.ts
81.48% <0%> (+3.7%)
:arrow_up:

src/client/datascience/debugLocationTracker.ts
83.01% <0%> (+3.77%)
:arrow_up:

src/client/linters/pydocstyle.ts
89.74% <0%> (+5.12%)
:arrow_up:

src/client/common/platform/pathUtils.ts
72.22% <0%> (+5.55%)
:arrow_up:

src/client/providers/providerUtilities.ts
88.88% <0%> (+5.55%)
:arrow_up:

... and 7 more

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GEODE-8466: Introduction of ClassLoaderService

Introduction of ClassLoaderService as replacement for the direct feature usage of ClassLoader and ClassLoaderPath
Thank you for submitting a contribution to Apache Geode.
In order to streamline the review of the contribution we ask you
to ensure the following steps have been taken:
For all changes:

[ ] Is there a JIRA ticket associated with this PR? Is it referenced in the commit message?

[ ] Has your PR been rebased against the latest commit within the target branch (typically develop)?

[ ] Is your initial contribution a single, squashed commit?

[ ] Does gradlew build run cleanly?

[ ] Have you written or updated unit tests to verify your changes?

[ ] If adding new dependencies to the code, are these dependencies licensed in a way that is compatible for inclusion under ASF 2.0?

Note:
Please ensure that once the PR is submitted, check Concourse for build issues and
submit an update to your PR as soon as possible. If you need help, please send an
email to<EMAIL_ADDRESS>

This PR has been inactive for some while, can it be closed?


Bump webrick from 1.8.1 to 1.8.2 in /docs

Copy of dependabot #8233 to see if it needs a user to run Esti in CI.

Only opened to get CI to pass.


Fixed build crash on tvOS

@aol-public/mobile-sdk-team Ready for review

I assume it is not a crash - just a compile error?

Why the PR named as crash...?

@AndriiMoskvin not anymore =)


Issue with k8s.io/zh-cn/docs/setup/production-environment/tools/kubeadm/setup-ha-etcd-with-kubeadm/

kubelet start failed，message：
kubelet[2813]: E1114 20:10:19.135090    2813 run.go:74] "command failed" err="failed to validate kubelet flags: the container runtime endpoint address was not specified or empty, use --container-runtime-endpoint to set"
systemd[1]: kubelet.service: Main process exited, code=exited, status=1/FAILURE
systemd[1]: kubelet.service: Failed with result 'exit-code'.

/language zh

@xuangbing55  It seems you're seeking a volunteer to review the logs and address the issue causing you trouble. However, the current issue description is unclear. Providing more details about the issue and the required fixes would greatly assist other contributors in helping with this.
/triage needs-information

a better place to ask for help would be on the support channels. please see:
https://git.k8s.io/kubernetes/SUPPORT.md
/kind support
/close

You may want to check the kubelet systemd unit file and see what are the config files it is referencing. Then you will go to, for example /var/lib/kubelet, and find out the files to be changed.

kubelet uccessfully started when kubeadm init completed,thanks


Update processing_data.py

Codecov Report

Merging #65 into master will decrease coverage by 0.00%.
The diff coverage is 0.00%.

@@            Coverage Diff            @@
##           master     #65      +/-   ##
=========================================
- Coverage    1.62%   1.62%   -0.01%
=========================================
  Files          18      18
  Lines        3815    3816       +1
=========================================
  Hits           62      62
- Misses       3753    3754       +1

Flag
Coverage Δ

#unittests
1.62% <0.00%> (-0.01%)
:arrow_down:

Impacted Files
Coverage Δ

ecogvis/signal_processing/processing_data.py
0.00% <0.00%> (ø)

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Prisma schema: Remove empty dbgenerated() attribute

Example
 createdAt DateTime @default(dbgenerated())

In the times of old, an empty dbgenerated() in a @default field attribute was used by the introspection in fields, where we could not parse the default value correctly. Later on in the migration engine, we started to use it to pass custom SQL, and an empty value is in general just skipped.
In the real world, an empty dbgenerated() can cause drift and weird panics. We allow it in the PSL for backwards-compatibility. We should make it a validation error. The user can just db pull the database and get a non-empty value to the field’s default attribute.

[ ] First: investigate why we still create it during introspection for some schemas
[ ] Make it a validation error
[ ] Remove from https://github.com/prisma/prisma/blob/main/packages/client/src/tests/integration/happy/enums/schema.prisma
[ ] Check occurrences from https://github.com/search?q=org%3Aprisma+"dbgenerated()"&type=code&p=1
[ ] Release notes draft
[ ] Test how it looks with the VS Code extension

https://github.com/search?q=repo%3Aprisma%2Fintrospection-ci dbgenerated()&type=code

Note: Just found this small private issue: https://github.com/prisma/schema-team/issues/215

Docs PR prepared for when this got implemented: https://github.com/prisma/docs/pull/5007

Survey to collect feedback on why users might still be using it: https://github.com/prisma/prisma/discussions/20077


Remove bootstrap token being in beta state in kubelet-tls-bootstrappi…

Bootstrap Token have been stable since v1.18 release - https://kubernetes.io/docs/reference/access-authn-authz/bootstrap-tokens/

Thank you for the fix
/lgtm
/approve


fix: improve grammar in Ceph storage provider section

I'd argue that the grammar is more correct with the existing wording, no need for changes


Problems list dominated by unused usings

From @davidfowl on February 12, 2017 18:13
Makes it hard to see real problems. Can we downgrade this thing so it doesn't show up by default in the list of problems?

Copied from original issue: OmniSharp/omnisharp-roslyn#769

This is a duplicate of https://github.com/OmniSharp/omnisharp-vscode/issues/315 but I'm going to keep it on the backlog.
Sadly, there is no way to downgrade a diagnostic such that it's completely hidden in the Problems window today. We could make it a "hint", but that only hides the squiggle in the editor and leaves it in the Problems window, which isn't what we want.
I have https://github.com/Microsoft/vscode/issues/20219 open to get an API that'll allow us to have a better more VS-like experience here.

Maybe we can just remove them as problems for now in general? It's just noise at this point. When we get the new API then we can improve the experience all up.

Maybe, I'm not super-keen on the user experience of having no presentation in the editor at all for this remove unnecessary usings. That said, maybe you're right and it's worth it to hide for now and bring back in it's full glory later. :smile:
I'll take a look for 1.8.

Keep the code fix but remove the info 😄

I was so looking forward to this in 1.8... (

Sorry about this. I had to slip this one to get 1.8 out for some important debugger changes. Fixing this is on my list after restoring test support for csproj .NET Core projects.


Stop passing logging instances in Lab context

Is your feature request related to a problem? Please describe.
InstructLab is currently passing a logger instance around to other parts of the CLI. This violates the recommended way to use loggers and makes code unnecessary awkward to use.
https://github.com/instructlab/instructlab/blob/64eec597e450f5e901090ecc08d2b64c2dfa2416/src/instructlab/configuration.py#L227-L234
Describe the solution you'd like
The recommend approach for logging is:

every module creates its own logger instance with logging.getLogger(__name__)
logging handlers and formaters are configured globally for the root logger logging.getLogger(None)
if necessary, logging can be set for a logging hierarchy. Loggers automatically use settings of their parent loggers. For example a logger with name instructlab.configuration inherits its settings from instructlab, then root (None).

Additional context
https://docs.python.org/3/library/logging.html#module-logging

Bonus points: pylint does not understand our current design well.


Console Errors

The demo projects seem to run fine but when I copy the dist files to my existing application (it's a large angular 14 app, hence tons of style tags in the header ... if that's helpful to know) and link to scroll-timeline.js, I get the errors (pasted below) thrown upon initial load, before I have even attempted to implement any sort of scroll based animations.
Of note: The polyfill does seem to succeed and it turns out I can programmatically create animations via ScrollTimeline.
scroll-timeline-css-parser.js:630 Uncaught TypeError: this.parseError is not a function
    at n.advance (scroll-timeline-css-parser.js:630:18)
    at n.eatUntil (scroll-timeline-css-parser.js:637:12)
    at n.parseSelector (scroll-timeline-css-parser.js:650:10)
    at n.parseQualifiedRule (scroll-timeline-css-parser.js:562:27)
    at n.transpileStyleSheet (scroll-timeline-css-parser.js:79:27)
    at e (scroll-timeline-css.js:39:25)
    at MutationObserver.observe.childList (scroll-timeline-css.js:13:11)

scroll-timeline-css.js:70 Uncaught TypeError: Cannot read properties of null (reading 'animation-timeline')
    at scroll-timeline-css.js:70:24
    at scroll-timeline-css.js:162:24
    at Array.forEach (<anonymous>)
    at scroll-timeline-css.js:153:89

Thanks for reporting this.
You get this error after opening demo files? Which demo file?

Not the demo files. Those run fine. It's when I try to integrate into my own larger application.

That could be the case. If you can share some of your examples, I can take a look into them.

I'll see what I can do. I don't have a lot of time to dedicate to this and I can't publicly expose the app itself. I'll try to create a shareable example that reproduces the issue, but it may take some time. Bear with me.

Okay, I figured out how to reproduce the error. Something in my css processing chain is appending @charset "UTF-8" to the end of a style block which in turn causes the error in css parser. You can reproduce this in any demo by adding @charset "UTF-8" as the final line (or the only line) of any style block. As long as it is not the final line the parser seems to handle it gracefully.

This is invalid use. @charset must be first in the style sheet and not be preceded by any character. See the spec for more details.

I am aware that it is invalid. I didn't think that fact was relevant to the parser throwing an error.

I'm getting the exact same error while trying to use the polyfill on my Wordpress website.
Uncaught TypeError: this.parseError is not a function
at n.advance (scroll-timeline-css-parser.js:681:18)
at n.eatUntil (scroll-timeline-css-parser.js:688:12)
at n.parseSelector (scroll-timeline-css-parser.js:701:10)
at n.parseQualifiedRule (scroll-timeline-css-parser.js:612:27)
at n.transpileStyleSheet (scroll-timeline-css-parser.js:81:27)
at e (scroll-timeline-css.js:39:25)
at MutationObserver.observe.childList (scroll-timeline-css.js:13:11)

Access to script at '.....' from origin 'null' has been blocked by CORS policy: Cross origin requests are only supported for protocol schemes: http, data, isolated-app, chrome-extension, chrome, https, chrome-untrusted.
Hello, can anyone help me with this? I'm trying to use polyfill and this appeared

I dug a bit deeper and noticed that parseError was simply missing from the polyfill. I added this back in https://github.com/flackr/scroll-timeline/pull/139. This issue can be closed, as the error no longer appears (ping @kevers-google @flackr).
As for the polyfill not being able to parse @charset and other at-rules: that’s being tracked in #80 and #100.


Can't start certbot. - cp: cannot stat [...] cert.pem

Info:

Docker version ($ docker --version):
Docker version 18.06.1-ce, build e68fc7a

Laradock commit ($ git rev-parse HEAD):
83a24efa709d15037b0d06ca7f4df235e240d642

System info (Mac, PC, Linux):
Linux

System info disto/version:
Ubuntu 18.04.1 LTS

Issue:
Certbot exited with code 1
$ docker-compose up certbot
Starting certbot_1 ...
Starting certbot_1 ... done
Attaching to certbot_1
certbot_1              | Saving debug log to /var/log/letsencrypt/letsencrypt.log
certbot_1              | Plugins selected: Authenticator webroot, Installer None
certbot_1              | Starting new HTTPS connection (1): acme-v01.api.letsencrypt.org
certbot_1              | Unable to register an account with ACME server
certbot_1              | cp: cannot stat '/etc/letsencrypt/archive/"mydomain.pl"/cert1.pem': No such file or directory
certbot_1              | cp: cannot stat '/etc/letsencrypt/archive/"mydomain.pl"/privkey1.pem': No such file or directory
znajdzrower_certbot_1 exited with code 1
Relevant Code:
mk@mkubus-Vostro-5568:~/workspace/laradock$ cat docker-compose.yml |grep -i certbot -A 5
### Certbot #########################################
    certbot:
      build:
        context: ./certbot
      volumes:
        - ./data/certbot/certs/:/var/certs
        - ./certbot/letsencrypt/:/var/www/letsencrypt
      environment:
        - CN="mydomain.pl"
        -<EMAIL_ADDRESS>      networks:
        - frontend

Remove the quotation marks from the domain.
CN="mydomain.pl" to CN=mydomain.pl

i have remove quotation from domain but still get this
certbot_1              | cp: cannot stat '/etc/letsencrypt/archive/fake.domain.com/cert1.pem': No such file or directory
certbot_1              | cp: cannot stat '/etc/letsencrypt/archive/fake.domain.com/privkey1.pem': No such file or directory

I'm getting the same error too even with quotes removed how do you solve this??

I'm getting the same error too even with quotes removed how do you solve this??

+1


no warning for duplicated options

as you can see,i repeatly defined the methods option twice
so the last one will overwrite the first one
but,there will be no warning for that
i didn't know what is the matter when there was an error said that  handleFoo is not defined
cause of actually i did have defined it

Hi, thanks for filling this issue.
Vue doesn't get to detect a duplicate property inside an object literal -  It's automatically removed by javascript engines. e.g.


Remove printStackTrace usages and ban it.

Codecov Report

Merging #6432 into master will decrease coverage by 0.02%.
The diff coverage is n/a.

@@             Coverage Diff              @@
##             master    #6432      +/-   ##
============================================
- Coverage     82.77%   82.74%   -0.03%
- Complexity    12877    12883       +6
============================================
  Files          1481     1481
  Lines         48062    48061       -1
  Branches       5836     5836
============================================
- Hits          39785    39770      -15
- Misses         5520     5545      +25
+ Partials       2757     2746      -11

Impacted Files
Coverage Δ
Complexity Δ

.../operation/collect/sources/ShardCollectSource.java
85.35% <ø> (+2.43%)
31 <0> (+2)
:arrow_up:

.../main/java/io/crate/exceptions/MultiException.java
74.19% <ø> (ø)
9 <0> (ø)
:arrow_down:

...n/java/io/crate/exceptions/JobKilledException.java
0% <0%> (-66.67%)
0% <0%> (-1%)

...ration/aggregation/statistics/moment/Variance.java
66.66% <0%> (-33.34%)
5% <0%> (-2%)

...ion/aggregation/impl/GeometricMeanAggregation.java
50% <0%> (-30.31%)
9% <0%> (-2%)

...peration/aggregation/impl/VarianceAggregation.java
58.82% <0%> (-21.57%)
9% <0%> (-2%)

...o/crate/analyze/SafeExpressionToStringVisitor.java
83.33% <0%> (-16.67%)
7% <0%> (-1%)

...aggregation/impl/StandardDeviationAggregation.java
66.66% <0%> (-13.73%)
11% <0%> (ø)

core/src/main/java/io/crate/types/ShortType.java
80.76% <0%> (-11.54%)
16% <0%> (-3%)

...n/java/io/crate/planner/projection/Projection.java
90% <0%> (-10%)
6% <0%> (-1%)

... and 32 more

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Tuple support

Coalton should support standard tuples
This can be achieved like with TYAPP and TYFUN using a new TYTUP type. The hope would be to allow for tuples in the language without having to explicitly specify every sized tuple constructor.
Tuple decomposition in matches are also be a nice addition

I agree with this I think. Of course there won't be any functions that are generic on any sized tuple. (You'd have to specialize on tuple size.) But we can get support for the type expressions. We are 1/2 way doing this with tyfuns now which have arbitrary arity.


Get Special Price products and liked products via api

Hi, i want to get Specific product ,Related products and Up Selling products, but can't find any api url for it.

Hi @megalightfm
Sorry, currently we don't have any APIs for fetching Related products and Up-selling products but you will definitely find these APIs in our next release of Bagisto.


Very bad wifi signal

Compiled a Arduino ESP32 framework with the glitch fix (#3).
https://github.com/Jason2866/esp32-arduino-lib-builder/releases/download/427/framework-arduinoespressif32-master-583026f04.tar.gz So https://github.com/espressif/esp-idf/issues/7082 is solved. No more boot loops. But signal is -76dBM at 1 meter of Wifi AP, far too low.
Source code: https://github.com/arendst/Tasmota
Compiled binary https://jason2866.github.io/Tasmota-specials/
Other C3 (revision 3 too) boards do work without any issue!
See screenshot from running Tasmota on a AI-Thinker ESP-C3-01M module

Sorry for the inconvenience, the new version has been updated to fix it.


chore(deps): bump @cdk8s/projen-common

⚪ Backport skipped
The pull request was not backported as there were no branches to backport to. If this is a mistake, please apply the desired version labels or run the backport tool manually.
Manual backport
To create the backport manually run:
backport --pr 1855

Questions ?
Please refer to the Backport tool documentation


Add mix deps.get to adding a package

Pull Request Test Coverage Report for Build 58

25 of 25 (100.0%)  changed or added relevant lines in 3 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 100.0%

Totals

Change from base Build 56:
0.0%

Covered Lines:
314

Relevant Lines:
314

💛  - Coveralls


Code junk in instructions

Challenge http://freecodecamp.com/challenges/waypoint-comment-your-javascript-code has an issue. Please describe how to reproduce it, and include links to screenshots if possible.

@georgiel please, provide the description of your issue, thanks!

Please review the Guidelines for Contributing, thank you!.

sorry, yeah specifically obvious, if you look in the code validations, I don't believe that the statement "assert(editor.getValue().match(/(//)...../g), 'Create a // style comment that contains at least five letters');" should be a visible element to users, it isn't meant to be there.

@georgiel thanks for posting this issue!
Closing this issue as a duplicate.
For more info see here.

Please review the Guidelines for Contributing, thank you!.


🐛 [Bug] Torch Tensor RT crash when trying to compile a script module on Windows (C++)

Bug Description
I can't compile a script module with TorchTensorRT.
This is my code:
#include <iostream>
#include <vector>
#include <ATen/Context.h>
#include <torch/torch.h>
#include <torch/script.h>
#include "torch_tensorrt/torch_tensorrt.h"

void compile(std::string model_path) {

    const torch::Device device = torch::Device(torch::kCUDA, 0);
    torch::jit::script::Module model;

    std::cout << "Trying to load the model" << std::endl;
    try {
        model = torch::jit::load(model_path, device);
        model.to(device);
        model.eval();
        std::cout << "AI model loaded successfully." << std::endl;
    }
    catch (const c10::Error& e) {
        std::cerr << e.what() << std::endl;
    }

    auto input = torch_tensorrt::Input(std::vector<int64_t>{ 1, 3, 512, 512 });
    std::cout << "Creating compile settings" << std::endl;
    auto compile_settings = torch_tensorrt::ts::CompileSpec({ input });
    // Compile module
    std::cout << "Compiling..." << std::endl;
    auto trt_mod = torch_tensorrt::ts::compile(model, compile_settings);  <-- CRASHES HERE.
    // Run like normal
    std::cout << "Create tensor" << std::endl;
    auto in = torch::randn({ 1, 3, 512, 512 }, device);
    std::cout << "Forward pass..." << std::endl;
    auto results = trt_mod.forward({ in });
    // Save module for later
    trt_mod.save("output/model/path.ts");

}

int main() {

    compile("path/to/traced_script_module.pt");

    return 0;
}

This is the error I get:

First a WARNING get printed "WARNING: [Torch-TensorRT] - Interpolation layer will be run through ATen, not TensorRT. Performance may be lower than expected",
and then, as you can see from the screenshot, I got an exception "read access violation. creator was nullptr." when running the following lines:
auto creator = getPluginRegistry()->getPluginCreator("Interpolate", "1", "torch_tensorrt");
auto interpolate_plugin = creator->createPlugin(name, &fc);

The file interpolate.cpp is located at path/to/Torch-TensorRT/core/conversion/converters/impl.
What am I doing wrong?
This is my CMakeLists.txt:
cmake_minimum_required (VERSION 3.8)

project(example-app)

find_package(Torch REQUIRED)
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}")

add_executable(example-app create_trt_module.cpp)

target_include_directories(example-app PRIVATE "path/to/Torch-TensorRT/cpp/include")

target_link_libraries(example-app "${TORCH_LIBRARIES}")
target_link_libraries(example-app  path/to/Torch-TensorRT/out/build/x64-Release/lib/torchtrt.lib)
target_link_libraries(example-app  path/to/Torch-TensorRT/out/build/x64-Release/lib/torchtrt_plugins.lib)

I exported the traced script module with the following code:
# Import model
# ...
model.to("cuda")
model.eval()

# Create dummy data for tracing and benchmarking purposes.
shape = (1, 3, 512, 512)
input_data = torch.randn(shape).to("cuda")

# Convert model to script module
print("Tracing PyTorch model...")
traced_script_module = torch.jit.trace(model, input_data)
torch.jit.save(traced_script_module, "traced_script_module.pt")

Environment

Torch-TensorRT Version: built from source from this branch (that is currently being merged) #1058
TensorRT Version: <IP_ADDRESS>
CUDNN: 8.3.1
CPU Architecture: x86-64
OS : Windows 11
LIbtorch: 1.11.0
CUDA version: 11.5.2
GPU model: NVIDIA RTX 3080 Mobile

The release notes for version 1.1.0 indicates

Torch-TensorRT 1.1.0 targets PyTorch 1.11, CUDA 11.3, cuDNN 8.2 and TensorRT 8.2. Due to recent JetPack upgrades, this release does not support Jetson (Jetpack 5.0DP or otherwise). Jetpack 5.0DP support will arrive in a mid-cycle release (Torch-TensorRT 1.1.x) along with support for TensorRT 8.4.

I cannot guarantee it is related, but I would try with TensorRT 8.2.

Thanks @gcuendet! I will try with TensorRT 8.2

Unfortunately, I'm facing the same problem even using TensorRT <IP_ADDRESS>.

Now that I have a second look at it, I think it's just your CMake. There are a few problems, but typically, when you do
target_link_libraries(example-app  path/to/Torch-TensorRT/out/build/x64-Release/lib/torchtrt.lib)

you explicitly link a library (torchtrt.lib / dll) into your executable. That's a pretty old-fashioned way of using CMake.
The main idea of what is sometimes referred to as "modern" CMake is to use targets instead. A CMake target can encapsulate more informations about what and how to link to (such as list of libraries, obviously, but also headers that are exposed, dependencies to link against, specific flags to use, etc.).
I strongly suspect that in your case you are missing a whole bunch of dependencies (at least TensorRT to start with) since you are not using torch-tensorrt target and you are also not explicitly linking to tensorRT (and possibly other) libraries.
The CMake branch that you are using generates a CMake finder for torch-tensorRT that allows you to do
find_package(torchtrt REQUIRED)

in the exact same way you are doing for libtorch.
With that, you'll get torch-tensorRT cmake targets usable in your own CMakeLists.txt and you should link your executable in the following way:
target_link_libraries(example-app  PRIVATE torchtrt)

Note that now torchtrt is not the name of a library anymore, but really a CMake target. Linking against that target will also link against torch-tensorRT dependencies (typically TensorRT). As a side note, you can actually do the same for libtorch and replace:
-target_link_libraries(example-app "${TORCH_LIBRARIES}")
+target_link_libraries(example-app torch)

If you want to see an example of that, check in the example directory on that "CMake" branch, that's exactly how these are linked to torch-tensorRT, using CMake.
The one small problem that you might encounter when doing find_package(torchtrt REQUIRED) is that CMake doesn't find that CMake finder I am mentioning above, depending on where you installed torch-tensorRT when you compiled it from sources. In that case, the error message is pretty explicit and should tell you what to do, but basically you can tell CMake where to find that finder by setting the CMAKE_MODULE_PATH cmake variable to the path of your torch-tensorRT install folder.
Again, as a conclusion, please have a look at how the torch-tensorRT examples are compiled and linked to torch-tensorRT.
Let me know if that helps.

Ok, I tried to change my CMakeLists.txt file in:
cmake_minimum_required (VERSION 3.8)

project(example-app)

find_package(Torch REQUIRED)
find_package(torchtrt REQUIRED)

add_executable(example-app create_trt_module.cpp)
target_link_libraries(example-app PRIVATE torch "-Wl,--no-as-needed" torchtrt_runtime "-Wl,--as-needed")

And it fails with:
1> [CMake] CMake Error at C:/src/vcpkg/scripts/buildsystems/vcpkg.cmake:335 (_find_package):
1> [CMake]   By not providing "Findtorchtrt.cmake" in CMAKE_MODULE_PATH this project has
1> [CMake]   asked CMake to find a package configuration file provided by "torchtrt",
1> [CMake]   but CMake did not find one.
1> [CMake]
1> [CMake]   Could not find a package configuration file provided by "torchtrt" with any
1> [CMake]   of the following names:
1> [CMake]
1> [CMake]     torchtrtConfig.cmake
1> [CMake]     torchtrt-config.cmake
1> [CMake]
1> [CMake]   Add the installation prefix of "torchtrt" to CMAKE_PREFIX_PATH or set
1> [CMake]   "torchtrt_DIR" to a directory containing one of the above files.  If
1> [CMake]   "torchtrt" provides a separate development package or SDK, be sure it has
1> [CMake]   been installed.

So I tried with
cmake_minimum_required (VERSION 3.8)

project(example-app)

set(torchtrt_DIR C:/src/Torch-TensorRT/out/build/x64-Release)  # That contains torchtrtConfig.cmake
find_package(Torch REQUIRED)
find_package(torchtrt REQUIRED)

add_executable(example-app create_trt_module.cpp)
target_link_libraries(example-app PRIVATE torch "-Wl,--no-as-needed" torchtrt_runtime "-Wl,--as-needed")

And now it fails with
1> [CMake] CMake Error at C:/src/vcpkg/scripts/buildsystems/vcpkg.cmake:335 (_find_package):
1> [CMake]   By not providing "FindTensorRT.cmake" in CMAKE_MODULE_PATH this project has
1> [CMake]   asked CMake to find a package configuration file provided by "TensorRT",
1> [CMake]   but CMake did not find one.
1> [CMake]
1> [CMake]   Could not find a package configuration file provided by "TensorRT" with any
1> [CMake]   of the following names:
1> [CMake]
1> [CMake]     TensorRTConfig.cmake
1> [CMake]     tensorrt-config.cmake
1> [CMake]
1> [CMake]   Add the installation prefix of "TensorRT" to CMAKE_PREFIX_PATH or set
1> [CMake]   "TensorRT_DIR" to a directory containing one of the above files.  If
1> [CMake]   "TensorRT" provides a separate development package or SDK, be sure it has

Since there's no TensorRTConfig.cmake file in the TensorRT installation directory I added your (@gcuendet ) Modules directory to CMAKE_MODULE_PATH
cmake_minimum_required (VERSION 3.8)

project(example-app)

set(CMAKE_MODULE_PATH C:/src/Torch-TensorRT/cmake/Modules) # here
set(torchtrt_DIR C:/src/Torch-TensorRT/out/build/x64-Release)
find_package(Torch REQUIRED)
find_package(torchtrt REQUIRED)

add_executable(example-app create_trt_module.cpp)
target_link_libraries(example-app PRIVATE torch "-Wl,--no-as-needed" torchtrt_runtime "-Wl,--as-needed")

And I get
1> [CMake] CMake Error at C:/Program Files (x86)/Microsoft Visual Studio/2019/Community/Common7/IDE/CommonExtensions/Microsoft/CMake/CMake/share/cmake-3.20/Modules/FindPackageHandleStandardArgs.cmake:230 (message):
1> [CMake]   Could NOT find TensorRT (missing: TensorRT_LIBRARY TensorRT_INCLUDE_DIR)

But at this point I guess I'm just doing something wrong.

I think the main problem here is that you didn't install torchtrt. I am assuming that looking at:
1> [CMake] CMake Error at C:/src/Torch-TensorRT/out/build/x64-Release/torchtrtConfig.cmake:35 (include):

which looks like your build folder.
My assumption is that you did something like:
cmake -S. -Bbuild [and possibly set other options here]
cmake --build build

but not the install step:
cmake --build build --target install

Is that correct?
You should install it (last command above), when copying everything in the install folder, some paths can "correct" (typically the finders in  cmake/Module get staged at the right place). Then this the path C:/src/Torch-TensorRT/out/build/x64-Release in
set(torchtrt_DIR C:/src/Torch-TensorRT/out/build/x64-Release)  # That contains torchtrtConfig.cmake

becomes the path to the install folder.:
list(APPEND CMAKE_PREFIX_PATH <install folder path>)

Actually, writing this answer, it reminded me of a similar recent issue. Maybe you could have a look at the answer there, it might be helpful.

Oh right, I added on VS the install option as a build command argument into the CMakeSettings for x64-Release

And it built an install directory with everything needed by cmake (almost, it still wanted me to specify the TensorRT_ROOT) to work properly.
This is my new CMakeLists.txt
cmake_minimum_required (VERSION 3.8)

project(example-app)

list(APPEND CMAKE_PREFIX_PATH "C:/src/Torch-TensorRT/out/install/x64-Release/lib/cmake/torchtrt/")

set(TensorRT_ROOT "C:/src/TensorRT-<IP_ADDRESS>/")
set(torchtrt_DIR "C:/src/Torch-TensorRT/out/install/x64-Release/lib/cmake/torchtrt/")

find_package(Torch REQUIRED)
find_package(torchtrt REQUIRED)

add_executable(example-app create_trt_module.cpp)

target_link_libraries(example-app PRIVATE torch "-Wl,--no-as-needed" torchtrt_runtime "-Wl,--as-needed" torchtrt_plugins "-Wl,--as-needed" torchtrt "-Wl,--as-needed" )
# I linked against all targets even though I don't think it's necessary

Unfortunately it still crashes in the same point, creator is still nullptr.
auto creator = getPluginRegistry()->getPluginCreator("Interpolate", "1", "torch_tensorrt");

@narendasan Is this something that ever happened or am I the first to experience this kind of behaviour? At this point I don't understand what I'm possibily doing wrong.

As an additional note, I was able to optimize the model on the same PC by using WSL. Then I tried to create a super trivial executable that just loaded the model
test.cpp
#include <ATen/Context.h>
#include <torch/torch.h>
#include <torch/script.h>

int main(){
    std::string model_path = "path/to/trt_script_module.pt";
    const torch::Device device = torch::Device(torch::kCUDA, 0);
    torch::jit::script::Module model;
    try {
        model = torch::jit::load(model_path, device);
        model.eval();
        std::cout << "AI model loaded successfully." << std::endl;
    }
    catch (const c10::Error& e) {
        std::cerr << e.what() << std::endl;
    }
  return 0;
}

cmake_minimum_required (VERSION 3.8)

project(example-app)

set(TensorRT_ROOT "C:/src/TensorRT-<IP_ADDRESS>/")
set(torchtrt_DIR "C:/src/Torch-TensorRT/out/install/x64-Release/lib/cmake/torchtrt/")

find_package(torchtrt REQUIRED)
find_package(Torch REQUIRED)

add_executable(example-app test.cpp)
target_link_libraries(example-app PRIVATE torch "-Wl,--no-as-needed" torchtrt_runtime "-Wl,--as-needed")

It compiles, and when i try to run the executable it asks me to copy the torch .dll files in the build directory (a known problem when using torch in Windows) but it doesn't ask me to copytorchtrt_runtime.dll, so I'm not even suere if it's properly linking the torchtrt_runtime target!
It crashes when it tries to load the model.

Update: by catching the exception as a  torch::jit::ErrorReport
try {
        model = torch::jit::load(model_path, device);
        model.eval();
        std::cout << "AI model loaded successfully." << std::endl;
    }
    catch (const torch::jit::ErrorReport& e) {
        std::cerr << e.what() << std::endl;
    }

I was able to get the following message:
Unknown type name '__torch__.torch.classes.tensorrt.Engine':
Serialized   File "code/__torch__/segmentation_models_pytorch/decoders/deeplabv3/model.py", line 4
  __parameters__ = []
  __buffers__ = []
  __torch___segmentation_models_pytorch_decoders_deeplabv3_model_DeepLabV3Plus_trt_engine_ : __torch__.torch.classes.tensorrt.Engine
                                                                                ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
  def forward(self_1: __torch__.segmentation_models_pytorch.decoders.deeplabv3.model.DeepLabV3Plus_trt,
    input_0: Tensor) -> Tensor:

So I guess, based on this issue that maybe VS isn't linking the torchtrt_runtime at all, that's probably due to the fact that the "-Wl,--no-as-needed" flag isn't working as expected.
This is the full output fromo VS (compilation + linking)
[1/2] C:\PROGRA~2\MICROS~2\2019\COMMUN~1\VC\Tools\MSVC\1429~1.301\bin\Hostx64\x64\cl.exe   /TP -DUSE_C10D_GLOO -DUSE_DISTRIBUTED -IC:\src\libtorch\include -IC:\src\libtorch\include\torch\csrc\api\include -I"C:\Program Files\NVIDIA Corporation\NvToolsExt\\include" -I"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.5\include" -I"C:\Program Files\NVIDIA Corporation\NvToolsExt\include" -I"C:\Program Files\NVIDIA\CUDNN\v8.4\include" -IC:\src\TensorRT-<IP_ADDRESS>\include /DWIN32 /D_WINDOWS /W3 /GR /EHsc  /MD /Zi /O2 /Ob1 /DNDEBUG /Z7 /EHsc /DNOMINMAX /wd4267 /wd4251 /wd4522 /wd4838 /wd4305 /wd4244 /wd4190 /wd4101 /wd4996 /wd4275 /bigobj /showIncludes /FoTorchTensorRT-Optimization-DEMO\CMakeFiles\example-app.dir\test.cpp.obj /FdTorchTensorRT-Optimization-DEMO\CMakeFiles\example-app.dir\ /FS -c ..\..\..\TorchTensorRT-Optimization-DEMO\test.cpp
  Microsoft (R) C/C++ Optimizing Compiler Version 19.29.30145 for x64
  Copyright (C) Microsoft Corporation.  All rights reserved.

...
...
  [2/2] cmd.exe /C "cd .

And if you check the linking passage ([2/2]) it seems that everything's fine since "C:\src\Torch-TensorRT\out\install\x64-Release\lib\torchtrt_runtime.lib" appears. But still, it doesn't ask me to copy the .dll when I run the program.

That's a very good point! If my understanding is correct, on Linux, torch-tensorRT relies on static initialisation to register the Engine class with torch (see here). That works if you force linking to that library, even when no symbol are used (that's always the case for torchtrt_runtime), so that it's automatically loaded by the consumer executable/library.
Not sure what's the equivalent on windows (or even if there is an equivalent, or if you have to "manually" dlopen the library).
Anyway, a possible (ugly) workaround is to link to torchtrt (and not torchtrt_runtime) and use at least one symbol from that lib (just instentiate a CompileSpec or an Input).
Not sure what the proper design will be, but I guess this will need to be addressed at some point, if the windows support becomes a bit more official, right @narendasan ?

Update:
By manually loading the .dlls the script does work! This of course isn't a proper solution and should be properly adressed in #1058 (maybe it would be beneficial to change the CMake example too @gcuendet)
If we want to optimize a model through TorchTensoRT on Windows make sure to manually load torchtrt_plugins.dll:
(you should probably manually copy the torchtrt_plugins.dll to your executable's folder)
#include <windows.h>
# ...
int main(){
    HMODULE hLib = LoadLibrary("torchtrt_plugins");
    if (hLib == NULL) {
        std::cerr << "Library torchtrt_plugins.dll not found" << std::endl;
        exit(1);
      }
    #  ...
    return 0;
}

If we want to use an optimized model on Windows make sure to manually load torchtrt_runtime.dll:
(you should probably manually copy the torchtrt_runtime.dll to your executable's folder)
#include <windows.h>
# ...
int main(){
    HMODULE hLib = LoadLibrary("torchtrt_runtime");
    if (hLib == NULL) {
        std::cerr << "Library torchtrt_runtime.dll not found" << std::endl;
        exit(1);
      }
    #  ...
    return 0;
}

Hello @andreabonvini I setup the code and fixed all compile time errors, but now I'm getting weird linking errors for each access of torch_tensorrt:: in my code.  Can you please explain the steps that made the torch_tensorrt work on windows?  I'll be exremely grateful to you

Hi @noman-anjum-retro, can you share your CMakeLists.txt, your code, and the linking errors you're receiving?

Great that you had it working @andreabonvini ! 😃
In my opinion, that issue is independent from the CMake support in itself. What I mean by that is:

The solution is probably not going to be at the CMake level
Something also needs to be done when compiling with Bazel (given that compiling with Bazel works on windows)

Still, that problem puzzled me and I might have a proposal.
I was wondering how that mechanism works in pytorch/vision (aka TorchVision) since there is at least one situation that works similarly to torchtrt_plugins: the library provides additional operator to pytorch that needs to be registered and potentially nothing else (no symbols to be used by the consumer of the library).
From my understanding they rely on "linker" pragmas:
VISION_API int64_t cuda_version();

 namespace detail {
 extern "C" VISION_INLINE_VARIABLE auto _register_ops = &cuda_version;
 #ifdef HINT_MSVC_LINKER_INCLUDE_SYMBOL
 #pragma comment(linker, "/include:_register_ops")
 #endif

 } // namespace detail

So basically, by just including that header (as documented in the README), the library is linked since one symbol is required.
So that could easily be done in torch-tensorRT as well. Moreover that would be consistent with torchvision. What do you think @narendasan ?

Hello @andreabonvini. I started with the basic cmake:
cmake_minimum_required(VERSION 3.0 FATAL_ERROR)
project(custom_ops)

find_package(Torch REQUIRED)

add_executable(example-app example-app.cpp)
target_link_libraries(example-app "${TORCH_LIBRARIES}")
set_property(TARGET example-app PROPERTY CXX_STANDARD 14)

Then I tried to read the module script via following code:
    torch::jit::Module module;
      torch::Device device(torch::cuda::is_available() ? torch::kCUDA : torch::kCPU);
      std::cout << torch::cuda::is_available() << std::endl;
      // Deserialize the ScriptModule from a file using torch::jit::load().
      module = torch::jit::load("\\scriptmodule.pt", torch::kCUDA);
      std::cout << "Loading Complete";
      std::vector<int64_t> input_shape =  {1,3,8,290,290} ;
      torch_tensorrt::core::ir::Input inputs = { { 1,3,8,290,290 } };
std::vector < torch_tensorrt::core::ir::Input> innn = { inputs };
      auto compile_spec = torch_tensorrt::core::CompileSpec(innn);
      torch_tensorrt::core::CompileGraph(module, compile_spec);

Initially code was showing compilation error as I copied it from documentation. But now compilation errors are fixed. When I run the code each reference of torch_tensorrt throughs linking error, I'm sharing one below:
Severity	Code	Description	Project	File	Line	Suppression State
Error	LNK2019	unresolved external symbol "public: __cdecl torch_tensorrt::core::ir::Input::Input(class std::vector<__int64,class std::allocator<__int64> >,enum nvinfer1::DataType,enum nvinfer1::TensorFormat,bool)" (??0Input@ir@core@torch_tensorrt@@QEAA@V?$vector@_JV?$allocator@_J@std@@@std@@W4DataType@nvinfer1@@W4TensorFormat@7@_N@Z) referenced in function "void __cdecl compile(class std::basic_string<char,struct std::char_traits,class std::allocator >)" (?compile@@YAXV?$basic_string@DU?$char_traits@D@std@@V?$allocator@D@2@@std@@@Z)	example-app	D:\Codes\C++\TorchCmake\build\example-app.obj	1

You aren't linking to torch_tensorrt. Supposing that you correctly compiled and installed torch_tensorrt (as explained above) you should have something like this:
target_link_libraries(example-app PRIVATE torch torchtrt)

Thanks I'll take a look to it

How did you build torch_tensorrt on windows can you please explain it. When I'm running bazel build for default workspace file it throws an error
bazel build //:libtorchtrt --compilation_mode opt --distdir D:\BazelDep
BazelDep folder contains zip files of cudnn8.2 and tensorRT 8.4
Error in download_and_extract: java.io.IOException: Error downloading [https://developer.nvidia.com/compute/machine-learning/tensorrt/secure/8.2.4/tars/tensorrt-<IP_ADDRESS>.linux.x86_64-gnu.cuda-11.4.cudnn8.2.tar.gz] to C:/users/nomananjum/_bazel_nomananjum/ebmkavax/external/tensorrt/temp17912101049819068034/tensorrt-<IP_ADDRESS>.linux.x86_64-gnu.cuda-11.4.cudnn8.2.tar.gz: GET returned 403 Forbidden

You have to build and install the package through CMake, you can do that only from this branch.

Alright, that makes sense now. Thanks Alot

Hey @andreabonvini I tried compiling with above mentioned steps. Code runs well with this script:
int main(){     std::string model_path = "path/to/trt_script_module.pt";     const torch::Device device = torch::Device(torch::kCUDA, 0);     torch::jit::script::Module model;     try {         model = torch::jit::load(model_path, device);         model.eval();         std::cout << "AI model loaded successfully." << std::endl;     }     catch (const c10::Error& e) {         std::cerr << e.what() << std::endl;     }   return 0; }
However when I try to compile script_module it throws linking error:
Code:
          model = torch::jit::load(model_path, device);         std::vector<int64_t> input_shape = { 1,3,8,290,290 };         //torch_tensorrt::Input inputs = { input_shape };         std::vector < torch_tensorrt::Input> innn = { input_shape };         auto compile_spec = torch_tensorrt::torchscript::CompileSpec(innn);         torch_tensorrt::torchscript::compile(model, compile_spec);
Link Error:

Any Idea What's Wrong??

It still seems that your are not linking against torch_tensorrt. You should provide more information about your environment and, above all, your CMakeLists.txt file.

So the steps are as follow: I copied this PR into my system and compiled it with command
cmake --build . --target install.
This created a Torch_TensorRT folder in Program Files x86. Secondly I created a torch project using following CmakeList.txt
`
cmake_minimum_required (VERSION 3.8)
project(example-app)
set(TensorRT_ROOT "C:\Program Files\TensorRT\TensorRT-<IP_ADDRESS>\")
set(torchtrt_DIR "C:\Program Files (x86)\Torch-TensorRT\lib\cmake\torchtrt")
find_package(torchtrt REQUIRED)
find_package(Torch REQUIRED)
add_executable(example-app create_trt_module.cpp)
target_link_libraries(example-app PRIVATE torch "${TORCH_LIBRARIES}" "-Wl,--no-as-needed" torchtrt_runtime "-Wl,--no-as-needed")
I then Used command cmake -G "Visual Studio 16 2019" -DCMAKE_PREFIX_PATH=D:\Codes\libtorch .`
which created a visual studio project in the folder.
Additional Step:
When it didn't work I explicitly added include and lib path of torchlib to the project using this

@noman-anjum-retro, as already said, you are not linking againt torch_tensorrt. You are linking against torchtrt_runtime instead, that is a light-weight library that is needed if you just want to load an optimized model through torch::jit::load.

Thank you soo much @andreabonvini. It is working now

Great that you had it working @andreabonvini ! 😃
In my opinion, that issue is independent from the CMake support in itself. What I mean by that is:
1. The solution is probably not going to be at the CMake level

2. Something also needs to be done when compiling with Bazel (given that compiling with Bazel works on windows)

Still, that problem puzzled me and I might have a proposal. I was wondering how that mechanism works in pytorch/vision (aka TorchVision) since there is at least one situation that works similarly to torchtrt_plugins: the library provides additional operator to pytorch that needs to be registered and potentially nothing else (no symbols to be used by the consumer of the library). From my understanding they rely on "linker" pragmas:
VISION_API int64_t cuda_version();

 namespace detail {
 extern "C" VISION_INLINE_VARIABLE auto _register_ops = &cuda_version;
 #ifdef HINT_MSVC_LINKER_INCLUDE_SYMBOL
 #pragma comment(linker, "/include:_register_ops")
 #endif

 } // namespace detail

So basically, by just including that header (as documented in the README), the library is linked since one symbol is required.
So that could easily be done in torch-tensorRT as well. Moreover that would be consistent with torchvision. What do you think @narendasan ?

@gcuendet At first glance seems reasonable

Hello, it is working fine with debug mode in visual studio, however when I switched to Release mode,(I also changed libtorch to release) it is unable to load TrTCompiledEngine and throwing following error
   model = torch::jit::load(model_path, device);
Unknown type name '__torch__.torch.classes.tensorrt.Engine':   File "code/__torch__/movinets/models.py", line 4   __parameters__ = []   __buffers__ = []   __torch___movinets_models_MoViNet_trt_engine_ : __torch__.torch.classes.tensorrt.Engine                                                   ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ <--- HERE   def forward(self_1: __torch__.movinets.models.MoViNet_trt,     input_0: Tensor) -> Tensor:
Any Idea about it?. I need to switch to release mode because openv debug mode is very slow, and it's ruining the gain obtained via trt

@noman-anjum-retro Seems like the runtime is not properly registering. Are you running this in C++? Can you try latest master?

Yeah, It's working now with the latest master. Thanks


Add supported macOS versions to the FAQ

macOS Ventura 13.6.2 user here and I just get "You can’t use this version of the application “Backup Status.app” with this version of macOS."
So I assume you need macOS 14 to run this, should be added into the info block

It's correct that macOS 14 is required. This is listed on both the website and Gumroad.


camlistore-commits email list not receiving mail since April 23

Looks like these emails are sent with mailgun via
https://github.com/perkeep/perkeep/blob/master/website/pk-web/email.go
So might just be a website configuration issue.

thx, i'll look into it

weird, the mailgun interface shows them as delivered

Maybe the mailing list is putting them in the moderation queue?
On Wed, Jun 13, 2018 at 12:36 PM mpl<EMAIL_ADDRESS>wrote:

weird, the mailgun interface shows them as delivered
[image: screenshot]
https://user-images.githubusercontent.com/626071/41373882-e01ddb8a-6f51-11e8-8d60-0c0b21824268.png
—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/perkeep/perkeep/issues/1188#issuecomment-397059608,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAF5yyyeJlmOEIebkA8Mh2xLfRK96Hhtks5t8WnYgaJpZM4UmsQ2
.

yeah, I've asked Brad to make me a manager on there (which I am not yet) so I could check things like that.

It was a weird combination. the sender address was wrong, but mailgun was still happily sending them.
And the messages were not showing up as pending in the google group interface, until i added manually the<EMAIL_ADDRESS>member. Then they showed up as pending, so then I had to reallow that sender again for some reason.
Anyway, this does not seem to be necessary now, but it still probably is the proper thing to do:
https://perkeep-review.googlesource.com/#/c/perkeep/+/17286

Yep, they're showing up again now.


Added Count Sort, Please accept my pull Request

Added Count Sort, Please accept my pull Request

Thank you for your valuable contribution to the community
Let's connect with each other
My profile -> @sahiljawale54


Cannot read property 'getNode' of null

I managed to add react-native easy-dnd to my crna app (without expo) and the drag and drop works perfectly. Just as intended.
However, when I try to navigate to another screen, I'm unable to do that, due to the following error.

What do I change in order to get it to work?
@mohebifar

I believe this issue is fixed in 1.0.2, but it has not been published on npm yet #4

Sorry, CI appears to be have been broken. I just did publish 1.0.2.


Adding test crumb finder to CI

What is the change?
I added a script to our GH CI that checks if the basic unit tests are leaving crumbs.  If they are, the build fails.
Why is the change being made?
@opotowsky recently had to make a PR to remove a ton of test crumbs.  And I have to do this once every few months as well.  This is a constant source of annoying work, because we had no way to track when people added crumby tests to the repo.
This PR aims to solve this issue.

Checklist

[X] This PR has only one purpose or idea.
[X] Tests have been added/updated to verify that the new/changed code works.

[X] The code style follows good practices.
[X] The commit message(s) follow good practices.

[X] The release notes (location doc/release/0.X.rst) are up-to-date with any important changes.
[X] The documentation is still up-to-date in the doc folder.
[X] If any requirements were affected, mention it in the release notes.
[X] The dependencies are still up-to-date in pyproject.toml.

@opotowsky I was able to (accidentally) prove this feature works.
I forgot to exclude the Python egg dir, and the build failed:
https://github.com/terrapower/armi/actions/runs/7531726953/job/20500907118?pr=1582
And then I excluded that dir, and the build passes now:
https://github.com/terrapower/armi/pull/1582/commits/86f9b4a994c6e96fe4b94b416eaac6f8c0b8904d
Just FYI. Having proof is nice.


Motion triggers not working

Hi,
I set up a simple automation rule where a Hue light should turn on if a Hue sensor detects motion. Nothing happens. The Home app shows the sensor as having detected motion but the light stays off. It works if I set it up in the Hue app but not via Home.

If Home shows motion detected, the problem is with HomeKit.
HomeKit automation rules run on your HomeKit hub, see Prerequisites in the README.  Sometimes the sync over iCloud from your iOS device to your HomeKit hub fails.  I find that the following actions typically help: disabling all automations, waiting for these changes to appear on another iOS device, enabling all automations, again waiting for these changes to appear.  Unfortunately, there now way to check the HomeKit configuration on your AppleTV.

I did try that. I'm also noticing an issue with pre-existing rules. Some are ok, some are delayed, and one isn't working at all.

Delayed automation is typically caused by the AppleTV having lost the connection to the accessory.  The changed accessory state is then registered by an iOS device, which syncs it through iCloud to the AppleTV.  In this case, you'd also see that automations only get executed when an iOS device is awake.
You could try disabling HomeKit on you AppleTV and re-enabling it.  Or, more drastically, logout of iCloud on your AppleTV and login again.  Or, when everything else fails, reset your entire HomeKit configuration (delete your home and re-pair all accessories - no fun).
The larger your HomeKit configuration gets, the more likely these issues.  The HomeKit configuration must fit one CKRecord, or the iCloud synchronisation fails.  Typically you'd hit this limit around 150-170 accessories, but your mileage may vary.

Sorry to hijack this, but with the hue motion sensor does it update HomeKit in real time or is there a delay for polling etc?  I have a v1 hub.

On Jun 6, 2017, at 10:21 AM, Erik Baauw<EMAIL_ADDRESS>wrote:
Delayed automation is typically caused by the AppleTV having lost the connection to the accessory. The changed accessory state is then registered by an iOS device, which syncs it through iCloud to the AppleTV. In this case, you'd also see that automations only get executed when an iOS device is awake.
You could try disabling HomeKit on you AppleTV and re-enabling it. Or, more drastically, logout of iCloud on your AppleTV and login again. Or, when everything else fails, reset your entire HomeKit configuration (delete your home and re-pair all accessories - no fun).
The larger your HomeKit configuration gets, the more likely these issues. The HomeKit configuration must fit one CKRecord, or the iCloud synchronisation fails. Typically you'd hit this limit around 150-170 accessories, but your mileage may vary.
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@NorthernMan54: Here's what happens when a Hue motion sensor reports motion:

The Hue motion sensor, which is configured for ZigBee attribute reporting, sends a ZigBee message to the Hue bridge in real-time;
The Hue bridge updates the sensor state and fires any bridge rules in real-time;
On the next heartbeat, homebridge-hue detects the changed sensor state and updates the HomeKit characteristic.  Technically, a HomeKit-enabled iOS or tvOS device maintains a TCP connection to homebridge, and receives the changed characteristic over this connection in realtime;
The HomeKit-enabled iOS or tvOS device syncs the changed characteristic to iCloud;
Any HomeKit-enabled iOS or tvOS device not connected to homebridge receives the changed characteristic on their next iCloud sync.  I'm not sure if this sync is scheduled or triggered, but typically there is a noticeable delay.  Normally, this is needed only for remote devices (not connected to your home network) or for devices out of range of Bluetooth LE accessories.

@jdshkolnik: Depending on whether your HomeKit Hub is connected to homebridge, the HomeKit automation fires on step 3 or step 5.  In my experience, issues with HomeKit automation not firing at all are caused by HomeKit automations not having been synced to the HomeKit hub; whereas issues with HomeKit automation firing with a delay, and/or only when another iOS device is awake are caused by the HomeKit hub having lost the connection with the HomeKit accessory (i.c. homebridge).
The Hue bridge does not support push notifications for changed attributes.  Even though this is the second largest discussion thread on the Hue developers forum (after the power-on defaults), it doesn't look like Philips will change this.  The dresden elektronik gateway deCONZ does support push notifications, and I plan to use these for homebridge-hue, see issue #106.  This would make step 3 real-time as well.
I'm using a 2-second polling interval (heartrate) with homebridge-hue for my v2 Hue bridge.  The v1 Hue bridge is way less powerful than the v2 Hue bridge, so you might need to use a slower rate.  Based on the Hue motion sensor, I turn on the lights using Hue bridge rules and the Sonos speakers using HomeKit automation.  There is a slight but noticeable delay before the speakers turn on, but I guess I learned to live with it.

tks Erik
I was thinking about buying one, to trigger my front door camera’s, but I’m going to see what other options I have for monitor sensors before pulling the trigger.   Thanks for the detailed explanation.
Tks again

On Jun 6, 2017, at 2:24 PM, Erik Baauw<EMAIL_ADDRESS>wrote:
@NorthernMan54 https://github.com/northernman54: Here's what happens when a Hue motion sensor reports motion:
The Hue motion sensor, which is configured for ZigBee attribute reporting, sends a ZigBee message to the Hue bridge in real-time;
The Hue bridge updates the sensor state and fires any bridge rules in real-time;
On the next heartbeat, homebridge-hue detects the changed sensor state and updates the HomeKit characteristic. Technically, a HomeKit-enabled iOS or tvOS device maintains a TCP connection to homebridge, and receives the changed characteristic over this connection in realtime;
The HomeKit-enabled iOS or tvOS device syncs the changed characteristic to iCloud;
Any HomeKit-enabled iOS or tvOS device not connected to homebridge receives the changed characteristic on their next iCloud sync. I'm not sure if this sync is scheduled or triggered, but typically there is a noticeable delay. Normally, this is needed only for remote devices (not connected to your home network) or for devices out of range of Bluetooth LE accessories.
@jdshkolnik https://github.com/jdshkolnik: Depending on whether your HomeKit Hub is connected to homebridge, the HomeKit automation fires on step 3 or step 5. In my experience, issues with HomeKit automation not firing at all are caused by HomeKit automations not having been synced to the HomeKit hub; whereas issues with HomeKit automation firing with a delay, and/or only when another iOS device is awake are caused by the HomeKit hub having lost the connection with the HomeKit accessory (i.c. homebridge).
The Hue bridge does not support push notifications for changed attributes. Even though this is the second largest discussion thread on the Hue developers forum (after the power-on defaults), it doesn't look like Philips will change this. The dresden elektronik gateway deCONZ does support push notifications, and I plan to use these for homebridge-hue, see issue #106 https://github.com/ebaauw/homebridge-hue/issues/106. This would make step 3 real-time as well.
I'm using a 2-second polling interval (heartrate) with homebridge-hue for my v2 Hue bridge. The v1 Hue bridge is way less powerful than the v2 Hue bridge, so you might need to use a slower rate. Based on the Hue motion sensor, I turn on the lights using Hue bridge rules and the Sonos speakers using HomeKit automation. There is a slight but noticeable delay before the speakers turn on, but I guess I learned to live with it.
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There is connectivity and I cleaned the bridge. The Hue sensor triggers Hue rules without any real delay yet that same trigger might get a very delayed response or none at all from Home rules.

I should add that it's only the motion sensors having trouble with the rules. I created a different rule for turning on two Koogeek power outlets when a Wemo switch turns on. It happens right away even though that Wemo switch is enabled via another Homebridge plugin.

I've been doing some testing, and there appears to be bug in HomeKit in tvOS 10.2.1.  To rule out homebridge-hue, I tested using a motion sensor created in the HomeKit Accessory Simulator.  The automation on this sensor fires once, just after being created, but no more.  The value of the sensor gets updated alright in the Home app and I do receive a push notification that motion is detected.
When I disable WiFi on my iPad (so it connects to my AppleTV over 4G), I no longer receive the push notifications when motion is detected.  Also, the motion sensor status no longer gets updated in Home, even though other services still do.
Setting up the iPad as Home Hub (now again connected to WiFi) and disabling Home on the AppleTV, the automation fires every time, as it should.
It would seem the AppleTV doesn't register the change to the motion sensor state.  I've seen a number of people complaining that they didn't receive any motion sensor push notifications over 4G, when I used to receive these.  I don't receive them anymore, so I suspect its a recently introduced bug.
I'm afraid I can only offer a workaround: create a CLIPGenericFlag sensor on the Hue bridge, with Hue bridge rules to set/clear the flag based on the Hue motion sensor.  Expose the flag as switch to HomeKit, and then base the HomeKit automation on this switch.

At least you've confirmed it wasn't my imagination. Is there a channel for reporting this bug to Apple?
On a somewhat related note, is there a way to trigger automation if no motion is detected for a specified interval similar to what we can do in the Hue app?

Is there a channel for reporting this bug to Apple?

Not sure.  I would like to see confirmation using a true HomeKit enabled motion sensor (like Elgato's Eve Motion), but I only have the Hue motion sensors.

How do you create a CLIPGenericFlag sensor on the Hue bridge

Through the Hue API.  I created a little bash script for easier interaction, see https://github.com/ebaauw/ph.sh, so I would issue:
ph_post /sensors '{
    "name": "My Room",
    "type": "CLIPGenericFlag",
    "modelid": "PHCLGF",
    "manufacturername": "Philips",
    "swversion": "1",
    "uniqueid": "/sensors/xxx"
}'

Note that Philips expose it as a "sensor", but it's actually more like a variable on the Hue bridge, which can be read and set through the API and used in Hue bridge rules.  See also my notes on home automation.

is there a way to trigger automation if no motion is detected for a specified interval similar to what we can do in the Hue app

The Hue app actually creates a Hue bridge rule with conditions like:
"conditions": [
  {
    "address": "/sensors/xx/state/presence",
    "operator": "eq",
    "value": "false"
  },
  {
    "address": "/sensors/xx/state/lastupdated",
    "operator": "ddx",
    "value": "PT00:00:15"
  }
]

This causes the rule to fire after the motion sensor reports "no motion" for 15 seconds.  Note that the interval is hard-coded in the rule.  There's no setting for this on the Hue motion sensor (nor on the Hue bridge).  You could use a rule with similar conditions to clear the CLIPGenericFlag sensor on the bridge at the end of the interval.
There is no way to express these conditions in HomeKit automation.  To overcome that, I included the Duration characteristic in homebridge-hue, even though the Hue motion sensor doesn't support it.  Of course, that won't help with the AppleTV not registering the changed Motion state...

First of all, thank you. Your answers are fantastic. Despite that, I'm still getting through the learning curve. I added the new sensor and it appears in the JSON output for list of sensors yet does not appear in the Hue or Home apps. This is what I get in the CLIP API Debugger:
	"20": {
		"state": {
			"flag": false,
			"lastupdated": "none"
		},
		"config": {
			"on": true,
			"reachable": true
		},
		"name": "Stairway Chandelier Flag",
		"type": "CLIPGenericFlag",
		"modelid": "PHCLGF",
		"manufacturername": "Philips",
		"swversion": "1.0",
		"uniqueid": "Stairway Chandelier Flag 1",
		"recycle": false
	}

Is it not expected to appear in the Hue app? Should I just add conditions through the API for the real sensor to trigger the virtual sensor? How to expose that virtual sensor as a switch to HomeKit?

It won't appear in the Hue app.  For it to appear in HomeKit, you need to restart homebridge after creating the sensor, see issue #4.  Before that, you might want to double-check your config.json, in particular "sensors": true and "excludeSensorTypes", which should not contain "CLIP" (nor "CLIPGenericFlag").
You can create the rules using the CLIP API debugger (POST /rules), with the conditions like in my previous post and actions to set or clear this sensor:
"actions": [
  {
    "address": "/sensors/20/state",
    "method": "PUT",
    "body": {
      "flag": true
    }
  }
]

@ebaauw If I have my iPhone or iPad open to the Home app when the motion sensor is triggered, the flag turns on and correctly sets off the switch via a Home automation rule. If I don't have the Home app open, the flag turns on but doesn't set off the Home automation rule.

Typically this happens when the AppleTV has lost the connection to the accessory (i.c. homebridge).  In that case, if one of the iOS devices running Home (or another HomeKit app) connects to the accessory, it receives the new state which is then synced to the AppleTV through iCloud.
Typically, this is remedied by:

Disable all rules on one iOS device;
Wait for this to be synced to the other devices.  This might take several minutes;
Re-enable all rules on the iOS device;
Wait for this to be synched to the other iOS devices (and the AppleTV).

Isn't it related to the bug you found?

No.  There's (at least) three different issues with HomeKit automations, with different symptoms and different resolutions:

Issue The bug is related to the HomeKit Motion Sensor service, when you expose the Hue motion sensor to HomeKit and create a HomeKit automation triggered by the Motion Detected characteristic.  Symptoms: Motion Detected state is updated and notification is received over WiFi, but not over 3G/4G.  Automations triggered by Motion Detected never fire; other automations do.  Resolution: none; Workaround: create a CLIPGenericFlag, which is exposed as Switch so the HomeKit automation is triggered by Power instead of by Motion Detected.
Issue Automation config isn't synced to the AppleTV, see https://github.com/ebaauw/homebridge-hue/issues/118#issuecomment-306110826.  Symptoms: Automation isn't fired, ever.  Resolution: Disable/re-enable automations.
Issue AppleTV lost connection to the accessory (i.c. homebridge) and doesn't receive the change of the characteristic, so it doesn't fire the automation, see https://github.com/ebaauw/homebridge-hue/issues/118#issuecomment-306501332.  Symptoms: Automation is only fired when HomeKit app on iOS device is active; automation is delayed.  Resolution: disable/re-enable HomeKit on the AppleTV, or logout from iCloud on the AppleTV and login again.

If I understand correctly, in your case, you've implemented the workaround for 1) and are now seeing 3).

I have two AppleTV's and an iPad Pro 12.9 acting as hubs so there is great coverage. I think it might have something to do with the triggering device being a flag exposed via Homebridge. It looks like everything registered via Homebridge (including the Homebridge) show as "Updating" every so often before showing as "No Response" and then returning to normal. Slow polling or something?

@ebaauw For issue #1, have you seen this hack in HAP-Nodejs? To resolve issues with IOS unregistering motion sensors from events?
https://github.com/jspv/HAP-NodeJS/commit/932ef587bee27cd3788c066d52cfd559ab556b3a
It is discussed here
https://github.com/KhaosT/HAP-NodeJS/issues/418
I have been using it for months with my Motion sensors, and are working fine.   These aren't hue sensors though, just ancient X10 Motion Sensors.  If I mentioned this before, please excuse me.

Thanks @NorthernMan54.  Yes, you did mention this in https://github.com/ebaauw/homebridge-hue/issues/125#issuecomment-310899566, and I had a look at it.  Not sure I fully understand the issue, see also my reply in the other issue.
I haven't yet tried the hack.  Even if it works, I'm not sure how I would publish it as HAP-NodeJS is provided through homebridge instead of being a direct dependency.

@jdshkolnik I don't think this is related to homebridge.  Similar issues are reported in the Hue developers forum when Hue lights are being exposed by the v2 Hue bridge, see https://developers.meethue.com/content/homekit-no-response-issue.

That doesn't seem to be the same thing because it's intermittent whereas mine fails to trigger 100% of the time without the app open.

@NorthernMan54 I can confirm that this is the same issue as https://github.com/KhaosT/HAP-NodeJS/issues/418.  The AppleTV unsubscribes from Motion Detected events.  After that, the Motion Detected event is sent to connected iOS devices, but not to the AppleTV.  Consequently, remote iOS devices (connected to the AppleTV over 4G) don't receive the updates and automations on the AppleTV do not fire.
I still got a notification on my iPhone over 4G, but probably because the notification received by my iPad was synced over iCloud.
If memory serves, I didn't get any Motion Detected notifications over WiFi on iOS 10.2.  I suspect due to the same issue, which Apple fixed in iOS 10.3, but not in tvOS 10.2.
I patched HAP-NodeJS v0.4.26's lib/Accessory.js to ignore the unsubscribe message, as per @jsvp's hack.  After restarting homebridge, Motion Detected is updated over 4G.
As I said before, I have no clue as to how to publish this hack.  Also, I'm a bit concerned by @KhaosT's reservation to merge this hack into HAP-NodeJS.  I'd like an additional check that the event actually originates from an AppleTV.

Ultimately publishing the hack would be Tian's call, as he manages the hap-nodejs repository.  For me I added this to my personal version, as well as my Amazon Alexa hack, so all my devices have the fix, and anyone using my version of hap-nodejs ( actually quite a few ).  For those watching this, instructions for my version of homebridge with this fix and Alexa support are here
https://github.com/NorthernMan54/homebridge-alexa
I would hope that Apple is aware of the defect and fixes it in one of the upcoming release, if not already.
Sent from my iPad

On Jul 2, 2017, at 7:24 AM, Erik Baauw<EMAIL_ADDRESS>wrote:
@NorthernMan54 I can confirm that this is the same issue as @NorthernMan54 I can confirm that this is the same issue as KhaosT/HAP-NodeJS#418. The AppleTV unsubscribes from Motion Detected events. After that, the Motion Detected event is sent to connected iOS devices, but not to the AppleTV. Consequently, remote iOS devices (connected to the AppleTV over 4G) don't receive the updates and automations on the AppleTV do not fire.
I still got a notification on my iPhone over 4G, but probably because the notification received by my iPad was synced over iCloud.
If memory serves, I didn't get any Motion Detected notifications over WiFi on iOS 10.2. I suspect due to the same issue, which Apple fixed in iOS 10.3, but not in tvOS 10.2.
I patched HAP-NodeJS v0.4.26's lib/Accessory.js to ignore the unsubscribe message, as per @jsvp's hack. After restarting homebridge, Motion Detected is updated over 4G.
As I said before, I have no clue as to how to publish this hack. Also, I'm a bit concerned by @khaost's reservation to merge this hack into HAP-NodeJS. I'd like an additional check that the event actually originates from an AppleTV.
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No change in tvOS 10.2.2 as far as I can see.

What's weird, my parents have an Eve Motion installed in the bathroom and it triggers the lights without any iOS device on except their Apple TV4. I tested it yesterday. Now I wonder where is the difference?

The most obvious difference is that the Eve Motion uses Bluetooth instead of WiFi.

True, didn't know that a different way of connecting might cause problems.

" I would like to see confirmation using a true HomeKit enabled motion sensor (like Elgato's Eve Motion)..."
Gotcha covered. I have an Eve Motion and Caseta dimmers and a bunch of AppleTVs. Motion events do register in the home app, and the home app can control the light. But the rule won't turn the light on. Configure an iPad to be an additional home hub and put it within range of everything and the rules work as expected.

Installing the tvOS 11 public beta on our living room AppleTV seems to have fixed it.

That is good news, indeed!  I don't have a USB-C cable, and only one AppleTV, so haven't been able to test this myself.  Shouldn't be long before the production releas of tvOS 11 is out, though...

You can install the beta over-the-air. Go to the public beta site and look for instructions. You may need to sign out of iCloud and back in, but you get a toggle under software update to install beta releases.

I previously had some problems with motion sensors triggering automation sequences with iOS/tvOS 10, but as ebaauw has noted, this seemed mainly related to the AppleTV’s poor handling of updated configurations, as the sensor events were still firing in homekit, just failing to trigger automations. iOS/tvOS 11 has been rock solid with zero issues, aside from needing to repair my homebridge with homekit once after updating (renew identity).
I believe this issue can be closed, bearing in mind that iOS 11 should generally be considered a requirement of any stable homekit/homebridge automation setup.

Indeed, running on tvOS 11, an automation based on the Hue motion sensor detecting motion is triggered.


Implement mark and unmark for tasks

The MarkTask Command
The marktask command mark tasks as done. The command has the following format:
marktask TASK_INDEX

Parameter: TASK_INDEX

Must be a numeric string representing a number between 1 and total number of tasks.
If the value is not acceptable, the error message The task index provided is invalid is displayed.

If the task is already marked, the command is still accepted and succeeds.
Things to note

marktask does not remove the task from the person.

The UnmarkTask Command
The unmarktask command mark tasks as undone. The command has the following format:
unmarktask TASK_INDEX

Parameter: TASK_INDEX

Must be a numeric string representing a number between 1 and total number of tasks.
If the value is not acceptable, the error message The task index provided is invalid is displayed.

If the task is already unmarked, the command is still accepted and succeeds.
This PR is linked to #6.

LGTM!

Looks good to me!


Release version 3.0.0-RC1

Coverage decreased (-0.17%) to 97.14% when pulling cc4ffcf3dc60507a1be8ef72708755d219013b15 on akkie:master into ead4231f95ad705c02db5450cc2cf19dbd0303f0 on mohiva:master.


Infowindow attributes don't show properly with a hidden layer

Steps to reproduce:

Have a viz with two layers with different datasets / column names
Enable infowindows on both layers
Hide layer 1
Try to see the infowindow of the enabled layer 2 on the embed map

It shows "No data available", however the attributes call to the map api fetches the attributes, it seems like it is using the fields from the hidden layer.
(see related issue)

This has already been fixed!


feat: improve middleware scroller

Codecov Report
Patch coverage has no change and project coverage change: +0.02% :tada:

Comparison is base (4781931) 5.44% compared to head (eef66ff) 5.46%.
Report is 26 commits behind head on main.

:exclamation: Your organization needs to install the Codecov GitHub app to enable full functionality.
Additional details and impacted files
@@           Coverage Diff            @@
##            main    #212      +/-   ##
========================================
+ Coverage   5.44%   5.46%   +0.02%
========================================
  Files         60      60
  Lines       2775    2764      -11
  Branches     544     541       -3
========================================
  Hits         151     151
+ Misses      2088    2080       -8
+ Partials     536     533       -3

Flag
Coverage Δ

unittests
5.46% <0.00%> (+0.02%)
:arrow_up:

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packages/core/src/middleware/scroller/util.ts
0.00% <0.00%> (ø)

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Pass isNewUser?

I know on the Android side on the FirebaseUI Auth activity result you can check if the user was a new signup or not. Are you able to do that somehow with iOS? I don't know if the same API is supported but if so it would be nice to pass that data through to the callback so I can do something special in my app if the sign-in created a new user.

I know on the Android side on the FirebaseUI Auth activity result you can check if the user was a new signup or not. Are you able to do that somehow with iOS? I don't know if the same API is supported but if so it would be nice to pass that data through to the callback so I can do something special in my app if the sign-in created a new user.

That is a great idea, let me check please

I know on the Android side on the FirebaseUI Auth activity result you can check if the user was a new signup or not. Are you able to do that somehow with iOS? I don't know if the same API is supported but if so it would be nice to pass that data through to the callback so I can do something special in my app if the sign-in created a new user.

@achuinard  Done! please check the readme and let me know.

@oijusti You are a legend, thank you. I'll add this into my project and let you know how it goes.

@achuinard My pleasure

It worked really well, the only thing that tripped me up just a little was that IntelliJ thought these properties existed on the return object but they don't:

The uid, email, and isNewUser property are all directly accessible on the returned object. Perhaps the typings for this need to be updated?

@achuinard , yes, It needs to be completed. Thanks for reminding me of this 😃

@achuinard I added some types if you want to give it a try


Make Large allocations naturally aligned

This makes all large allocations aligned to their size next power of two size.
This introduces a new strategy for aligning blocks on platforms without a way to fetched aligned virtual memory (e.g. VirtualAlloc2, or mmap with MAP_ALIGNED).
To aid in debugging also uses mprotect to switch off unused pages in debug on posix platforms. This enables better testing of the Commit/Decommit code from Posix platforms.

#114 needs this.


microk8s.enable promethius not working on 1.19

Hey folks, looks like the promethius add-on isn't working on the latest version. Let me know if I'm doing something obvious wrong or really where to start troubleshooting. There's no real feedback given to the user.
eflee@rpi-4-1:~/k8s$ microk8s.kubectl get node -o wide
NAME             STATUS   ROLES    AGE    VERSION                     INTERNAL-IP     EXTERNAL-IP   OS-IMAGE             KERNEL-VERSION     CONTAINER-RUNTIME
rpi-4-2.epf.li   Ready    <none>   4h7m   v1.19.0-34+ff9309c628eb68   <IP_ADDRESS>   <none>        Ubuntu 20.04.1 LTS   5.4.0-1021-raspi   containerd://1.3.7
rpi-4-4.epf.li   Ready    <none>   10h    v1.19.0-34+ff9309c628eb68   <IP_ADDRESS>   <none>        Ubuntu 20.04.1 LTS   5.4.0-1021-raspi   containerd://1.3.7
rpi-4-3.epf.li   Ready    <none>   10h    v1.19.0-34+ff9309c628eb68   <IP_ADDRESS>   <none>        Ubuntu 20.04.1 LTS   5.4.0-1021-raspi   containerd://1.3.7
rpi-4-1.epf.li   Ready    <none>   28h    v1.19.0-34+ff9309c628eb68   <IP_ADDRESS>   <none>        Ubuntu 20.04.1 LTS   5.4.0-1021-raspi   containerd://1.3.7
eflee@rpi-4-1:~/k8s$ microk8s.status
microk8s is running
high-availability: yes
  datastore master nodes: <IP_ADDRESS>:19001 <IP_ADDRESS>:19001 <IP_ADDRESS>:19001
  datastore standby nodes: <IP_ADDRESS>:19001
addons:
  enabled:
    ha-cluster           # Configure high availability on the current node
  disabled:
    dashboard            # The Kubernetes dashboard
    dns                  # CoreDNS
    helm                 # Helm 2 - the package manager for Kubernetes
    helm3                # Helm 3 - Kubernetes package manager
    host-access          # Allow Pods connecting to Host services smoothly
    ingress              # Ingress controller for external access
    metallb              # Loadbalancer for your Kubernetes cluster
    metrics-server       # K8s Metrics Server for API access to service metrics
    rbac                 # Role-Based Access Control for authorisation
    registry             # Private image registry exposed on localhost:32000
    storage              # Storage class; allocates storage from host directory
eflee@rpi-4-1:~/k8s$ microk8s.enable promethius
Nothing to do for promethius
eflee@rpi-4-1:~/k8s$ microk8s.disable promethius
Addon promethius is already disabled.

Please run microk8s inspect and attach the generated tarball to this issue.
We appreciate your feedback. Thank you for using microk8s.

inspection-report-20201020_035743.tar.gz

Hi @eflee for now prometheus addon isn't available on arm arch.  That's why it says "Nothing to do ..."


Main Body Backbone

Outline the following:

BIG BOLD ANNOUNCEMENT OF COOL FEATURES
Announce features of the web app.
pricing
FAQ
Future Feature Timeline (go wild)

I'll be honest I completely forgot to change branches before pushing this. I don't believe I did any damage, but won't happen again.

I'm going to add more content to the sections.


[DOC] Improve documents related to Helium

What is this PR for?
What I did for the documents:

Highlight codes
Follow JSON syntax
Remove white spaces

And in my opinion, here is ambiguous:

"Normally, you can add any dependencies in package.json however Zeppelin Visualization package only allows two dependencies: zeppelin-vis and zeppelin-tabledata."

Does it want to say "you can add any dependencies in package.json, but you must include two dependencies: zeppelin-vis and zeppelin-tabledata."?
What type of PR is it?
[Documentation]
Questions:

Does the licenses files need update? NO
Is there breaking changes for older versions? NO
Does this needs documentation? NO

@tae-jun Thanks for the improvement.

You can add any dependencies in package.json, but you must include two dependencies: zeppelin-vis and zeppelin-tabledata.

Yeah I think you're right.

@AhyoungRyu Thanks for the review!
I changed the sentence, and now it looks like this:

You can add any dependencies in package.json, but you must include two dependencies: zeppelin-vis and zeppelin-tabledata.

I marked it as bold, since I think it's important 😄

@tae-jun Looks GOOD to merge :)

@AhyoungRyu Thanks! 👍

Merge into master if there are no more comments on this.


Unmarshal access to "meta"

It'd be great to have access to an annotation type "meta" or some other way to easily access the Meta information from a JSON API document.
Currently I'm unmarshaling twice: once into OnePayload via encoding/json and again via the jsonapi unmarshal methods. It'd be wonderful to button this up.

The point of meta is to describe the response.. What's the point of submitting a request with meta to your api?  If its a required field, it should be in attributes or another object?  Not disagreeing, just wondering what the use-case is?

My use case is actually for a response, I'd like to extract that meta result. Currently I'm unmarshaling twice to get it since the tags don't support getting it directly.

Ahhh. Totally get it!!
On Tue, Apr 11, 2017 at 6:43 PM Mitchell Hashimoto<EMAIL_ADDRESS>wrote:

My use case is actually for a response, I'd like to extract that meta
result. Currently I'm unmarshaling twice to get it since the tags don't
support getting it directly.
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Hi there. Is there any update on this issue or the related #95 ?
My use-case requires creating a go JSON API server and client, meaning I will need to marshal and unmarshal the data. More specifically, I would like access to the "meta" for a relationship, which seems to be already supported for marshalling (see https://github.com/google/jsonapi/blob/master/node.go#L59).
My current options seem to be:

Unmarshal twice, as @mitchellh has done. I believe that this would require a little work to map the data to the appropriate relationship.
Unmarshal exclusively using encoding/json.

If anyone has any other potential workarounds, I'd be extremely grateful!

func setDataIntoTarget(data *Data, target interface{}) error {} is missing following chunk of code which will resolve meta part of unmarshaling
if data.Meta != nil {
err = json.Unmarshal(data.Meta, castedTarget)
if err != nil {
return err
}
}


Expose abstract base class for Git source plugin

See original issue on GitLab
In GitLab by [Gitlab user @cs-shadow] on Oct 30, 2018, 14:37
Background
As discussed during the recent BuildStream Gathering, there is demand for extending the Git source plugin. Sometimes, these changes will be such that they will not belong in BuildStream core for whatever reason. In the long run, it may make sense to think about allowing plugins to be extended in general. Since that is comparatively more challenging, a short-term solution will be to provide an abstract base class for the Git plugin.
Obviously, this will only work for the Git plugin but this is kind of fine as we haven't really had many requests to extend other  plugins.
Task description

[ ] There is a publicly available abstract base class for Git-based source plugins.
[ ] The git source plugin in Core is derived from the above base class.

Acceptance Criteria
Plugin developers are able to create custom Git-based plugins without having to copy-paste the git plugin in Core.

In GitLab by [Gitlab user @jjardon] on Oct 31, 2018, 17:08
[Gitlab user @coldtom] this can be of interest for http://buildstream.gitlab.io/bst-external/sources/git_tag.html

In GitLab by [Gitlab user @cs-shadow] on Oct 31, 2018, 17:27
changed the description

In GitLab by [Gitlab user @jjardon] on Nov 8, 2018, 10:17
This is important as seems the http://buildstream.gitlab.io/bst-external/sources/git_tag.html is broken when using buildstream master:
10:08 <valentind> jjardon, what the git_tag plugin does is to inherit from the git plugin from buildstream.
10:09 <valentind> what it should do is just copy the version from 1.2 and inherit from that.
10:10 <[[Gitlab user @jjardon]](https://gitlab.com/jjardon)> valentind: maybe I'm wrong, but if a plugin works with 1.2.x, but it doesn't with master, then somehow buildstream is breaking API?
10:10 <valentind> jjardon, It uses non API stuff.
10:10 <valentind> jjardon, the git plugin is not API.
10:11 <valentind> And git_tag inherits from the git plugin.
10:11 <valentind> The git plugin however uses API. So you could copy it.
10:12 <valentind> I mean you could copy the git plugin from 1.2 and make it run on 1.4.
10:12 <[[Gitlab user @jjardon]](https://gitlab.com/jjardon)> right, I guess this would be solved when we fix https://gitlab.com/BuildStream/buildstream/issues/739 ?
10:13 <valentind> jjardon, If they are stable yes.
10:13 <valentind> jjardon, for the time being, just copy the plugin from 1.2

In GitLab by [Gitlab user @jjardon] on Nov 12, 2018, 09:38
[Gitlab user @coldtom] let's have a chat and see if we (freedesktop-sdk) can implement this and propose it to buildstream

In GitLab by [Gitlab user @jjardon] on Nov 12, 2018, 09:38
assigned to [Gitlab user @coldtom] and [Gitlab user @jjardon]

In GitLab by [Gitlab user @jjardon] on Nov 13, 2018, 10:32
unassigned [Gitlab user @jjardon]

In GitLab by [Gitlab user @juergbi] on Dec 4, 2018, 05:05
From https://mail.gnome.org/archives/buildstream-list/2018-November/msg00034.html

Side note is that we have a goal to expose an abstract class or utility
module to implement git oriented sources. It will be better to not
land this in 1.4 and to land that in the plugins package which will
contain the git plugin instead.

In GitLab by [Gitlab user @cs-shadow] on Dec 13, 2018, 19:56
[Gitlab user @juergbi] [Gitlab user @tristanvb] Since we have to manually rebase our git-based plugins currently, we'd quite like to have the abstract base class available sooner rather than later. Do you think there's any hope for this making the cut for 1.4?

In GitLab by [Gitlab user @sstriker] on Dec 13, 2018, 20:04
Why can't this land on master?  If we don't want it in 1.4, at the time of
branch back it out.  We really should not preventing forward progress
waiting for a release.
Cheers,
Sander

In GitLab by [Gitlab user @juergbi] on Dec 13, 2018, 21:08
With the plan to move the git plugin (among others) to a separate repository, the whole git functionality should be moved there and thus the abstract base class should be exposed in that new repository. I.e., this isn't about 1.4 vs. 1.6/master. As I see it, this should never become public API in the core repository.
If this is needed before the plugin migration, an option could be to create the abstract base class in the core repository but don't mark it as public API (i.e., use a leading underscore). This would still allow other projects to use it, but without any guarantees from the BuildStream side. At the point of git plugin migration we could then make it public (in the new repository).

In GitLab by [Gitlab user @sstriker] on Dec 13, 2018, 21:31
I think that is a reasonable compromise, unless we envision making a move
on splitting out plugins real-soon-now(tm).

In GitLab by [Gitlab user @jjardon] on Dec 18, 2018, 12:04
mentioned in merge request freedesktop-sdk/freedesktop-sdk!777

In GitLab by [Gitlab user @cs-shadow] on Dec 19, 2018, 20:06
mentioned in commit 2d4566624f2b363772e5d29f0a579147e6fd6bf1

In GitLab by [Gitlab user @cs-shadow] on Dec 19, 2018, 20:07
mentioned in merge request !1019

In GitLab by [Gitlab user @cs-shadow] on Dec 19, 2018, 20:10
Based on the discussion above, I have submitted https://gitlab.com/BuildStream/buildstream/merge_requests/1019.

In GitLab by [Gitlab user @cs-shadow] on Dec 20, 2018, 12:50
mentioned in commit 9835b7f145686f71f0a132d8e1c19ce4ad6f0b3c

In GitLab by [Gitlab user @cs-shadow] on Dec 20, 2018, 13:34
closed via merge request !1019

In GitLab by [Gitlab user @cs-shadow] on Dec 20, 2018, 13:34
mentioned in commit 14da6955f9dd7ed820992a49af3eda8fe8092890


[WIP] Make streamed_from follow the source

Hey @akariv, here is an issue https://github.com/BCODMO/frictionless-usecases/issues/10 and I'm not sure whether it's a bug in DPP or an incorrect issue. It should be one of those:

issue is incorrect and it's how the streamed_from has to behave
issue is partially incorrect and it's how the streamed_from has to behave BUT it has to be removed on the dump step as it happens to streaming prop
issue is correct and this PR fixes it

Pull Request Test Coverage Report for Build 1075

2 of 2 (100.0%)  changed or added relevant lines in 1 file are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 25.649%

Totals

Change from base Build 1073:
0.0%

Covered Lines:
1729

Relevant Lines:
6741

💛  - Coveralls

This is indeed a bug, and your fix solves it.
I've been a bit partial on exposing the streamedFrom property in datapackages as it might expose private information (e.g. db connection strings). However, as it's being actively used, removing it now will break things...

@akariv
Thanks. I still don't fully understand why we set it for all resources not only for the loaded one. Is it intended?

It's not for all resources - just for the new ones.
also, when load is used with a datapackage it might load more than one resource (so it's not necessarily just the last one)


[BUG] Widget for Public Holidays not showing all results

Environment
Self-Hosted (Docker)
System
Rasperry Pi , Docker, Portainer v2.16.1
Version
2.1.1
Describe the problem
Dashy widget for Public Holidays only ever shows these two results.
Sun, 14 May 2023 Mother's Day
Sun, 3 Sept 2023 Father's Day
Compared this to the Enrico url http://holidays.kayaposoft.com/public_holidays.php?year=2023&country=aus&region={mystate}
which shows all results.
My conf.yml code is as below:
  "widgets": [
    {
      "type": "clock",
      "options": {
        "timeZone": "Australia/{mycity}",
        "format": "en-AU",
        "hideDate": false,
        "hideSeconds": true
      },
      "id": "0_513_clock"
    },
    {
      "type": "public-holidays",
      "options": {
        "country": "aus",
        "region":"{mystate}",
        "holidayType": "all",
        "monthsToShow": 12
      },
      "id": "1_513_publicholidays"

`
Additional info

Please tick the boxes

[X] You have explained the issue clearly, and included all relevant info
[X] You are using a supported version of Dashy
[X] You've checked that this issue hasn't already been raised
[X] You've checked the docs and troubleshooting guide
[X] You agree to the code of conduct

It appears there's a typo in the documentation.
https://github.com/Lissy93/dashy/blob/master/docs/widgets.md#public-holidays
The example shown is incorrect.
I got this working by changing the "region" field (as shown in the example)
to "state" as defined in the options.


Upgrade :db_connection to remove System.stacktrace/0 warning, is it possible?

warning: System.stacktrace/0 is deprecated, use __STACKTRACE__ instead
   lib/db_connection/connection.ex:72

warning: System.stacktrace/0 is deprecated, use __STACKTRACE__ instead
   lib/connection.ex:429

https://github.com/elixir-ecto/db_connection/issues/225#issue-720840851
:db_connection ~> 2.3
Btw,
the connection - https://github.com/fishcakez/connection
is redirected to
the db_connection - https://github.com/elixir-ecto/db_connection.

PR approved. Thank you!


source_id -- correction to the native_nominal_resolution of MIROC*, again

I'm so sorry that recently I've made wrong requests to modify native_nominal_resolution in source_id, because of  mis-understanding and mis-communication in our team members.
Please fix native_nominal_resolution of MIROC* models as follows:
MIROC-ES2H:
aerosol: "250 km"
atmos: "250 km"
atmosChem: "500 km"
land: "250 km"
MIROC-ES2H-NB
aerosol: "250 km"
atmos: "250 km"
atmosChem: "500 km"
land: "250 km"
MIROC-ES2L
aerosol: "500 km"
land: "500 km"
MIROC6
aerosol: "250km"
land: "250km"

@tinoue70 thanks for following this up. Those changes are now in place, please review the details are CMIP6_source_id.html and let me know of any further tweaks required


Data file not in the correct format

Find the place and change the name of trackpad.json

DataConversionException e, Line 85 in MainApp


Add PSL Catalog JSON File

This PR proposes adding a JSON file containing the data needed to generate a webpage for OG-USA on the PSL website. Documentation describing how this works can be found here. @hdoupe opened a similar PR in Tax-Calculator and you can see what the Tax-Calculator page looks like here.
@rickecon and @jdebacker, y'all's review would be especially helpful to make sure I got all of the information correct.

Thanks for your comments, @jdebacker. I'll go through them and update this PR accordingly.

@jdebacker @rickecon, can y'all take a look at my latest commits and see if they're more accurate?

LGTM

Great. Would it be possible to get this merged in today so we can update the PSL website accordingly?


Uncaught TypeError: Cannot read property 'func' of undefined

Hi There,
I am facing the below error:
Uncaught TypeError: Cannot read property 'func' of undefined
at eval (selectionPanels.js:46)
at Object../node_modules/react-listbox/build/selectionPanels.js (bundle.js:13285)
at webpack_require (bundle.js:727)
at fn (bundle.js:101)
at eval (index.js:12)
at Object../node_modules/react-listbox/build/index.js (bundle.js:13261)
at webpack_require (bundle.js:727)
at fn (bundle.js:101)
at eval (exception-data.tsx:14)
at Module../src/components/search/exception-data.tsx (bundle.js:15668)
I suspect that it's the error related to the prop-types which is moved as a different package. So, I imported that and then tried, but unfortunately, it wasn't fixed. Please help me in this.
Thanks,
Shubham

Issue is fixed in 1.2.10


Enable progressive JPEG

According to the sharp JPEG output options, the default option is baseline, not progressive JPEG. Could you enable progressive and possibly optimiseScans as well for faster loading images? Thanks!

I like the of "progressive JPEG" as well. I think the GIF equivalent would be interlaced. On extremely low bandwidth systems, having the interlaced provides a placeholder sooner and a quicker clue to the final image. You could potentially load 50% of a progressive JPEG a blurred image to save a lot of bandwidth.

Enabled progressive and optimizeScans options.

how to do this ?
Enabled progressive and optimizeScans options.


Set "Include Mdn Panels" for webapps boilerplate

This seems to have broken specs that don't have mdn annotations yet? I.e. FileAPI is now failing on https://travis-ci.com/github/w3c/FileAPI/builds/155915673 with "FATAL ERROR: Couldn't find the MDN data for 'fileapi' nor 'fileapi'."

This seems to have broken specs that don't have mdn annotations yet? I.e. FileAPI is now failing on https://travis-ci.com/github/w3c/FileAPI/builds/155915673 with "FATAL ERROR: Couldn't find the MDN data for 'fileapi' nor 'fileapi'."

With https://github.com/tabatkins/bikeshed/commit/10e72f6737dc1fe4c290989e3c14e73014bf1894 there should no longer be build failures. See the updated docs at https://tabatkins.github.io/bikeshed/#metadata-include-mdn-panels:

If your spec is not yet in MDN, but you’d like the panels to be added when it shows up, you can pass one of the "maybe" values of a soft boolish to allow it to silently upgrade when possible; otherwise, if directly turned on, it will emit a fatal error if it can’t find your spec.

Apologies for the breakage caused by me not having thought to code it that way from the get-go.