[Bug]: habana_main - Chatglm3-6b fail on graph compile failed.

Your current environment
The output of `python collect_env.py`

🐛 Describe the bug
# VLLM_SKIP_WARMUP=true PT_HPU_ENABLE_LAZY_COLLECTIVES=true VLLM_RAY_DISABLE_LOG_TO_DRIVER=1

from vllm import LLM, SamplingParams
from time import sleep
import traceback

def test_llm_model(model):

    tp_size = 1

    llm = LLM(model=model,
              tensor_parallel_size=tp_size,
              block_size=128,
              trust_remote_code=True,
              enforce_eager=True,
             )

    prompts = [
        "The future of AI is",
    ]
    sampling_params = [
        SamplingParams(temperature=0.0, max_tokens=128,)
        for _ in prompts
    ]

    output = llm.generate(prompts, sampling_params=sampling_params, use_tqdm=False)
    del llm
    return output

if __name__ == "__main__":
    model_list = ['THUDM/chatglm3-6b']
    for model in model_list:
        try:
            output = test_llm_model(model=model)
            print(f"- {model} succeed")
            print(f"output is", output)
        except Exception as e:
            print(f" - {model} faied!")
            print(f"Error info: {e}")
            print(traceback.format_exc())

error log
---------------------------: System Configuration :---------------------------                                                                              Num CPU Cores : 152                                                                                CPU RAM       :<PHONE_NUMBER> KB                                                                                ------------------------------------------------------------------------------                                                                              INFO 08-28 22:51:09 selector.py:85] Using HabanaAttention backend.                                                                                INFO 08-28 22:51:09 loader.py:284] Loading weights on hpu ...                                                                                INFO 08-28 22:51:09 weight_utils.py:224] Using model weights format ['*.safetensors']                                                                       Loading safetensors checkpoint shards:   0% Completed | 0/7 [00:00<?, ?it/s]
Loading safetensors checkpoint shards:  14% Completed | 1/7 [00:00<00:02,  2.08it/s]
Loading safetensors checkpoint shards:  29% Completed | 2/7 [00:00<00:02,  2.42it/s]
Loading safetensors checkpoint shards:  43% Completed | 3/7 [00:01<00:01,  2.54it/s]
Loading safetensors checkpoint shards:  57% Completed | 4/7 [00:01<00:01,  2.53it/s]
Loading safetensors checkpoint shards:  71% Completed | 5/7 [00:01<00:00,  3.12it/s]
Loading safetensors checkpoint shards:  86% Completed | 6/7 [00:02<00:00,  2.96it/s]
Loading safetensors checkpoint shards: 100% Completed | 7/7 [00:02<00:00,  2.91it/s]
Loading safetensors checkpoint shards: 100% Completed | 7/7 [00:02<00:00,  2.77it/s]
                                                                                INFO 08-28 22:51:12 habana_model_runner.py:472] Pre-loading model weights on hpu:0 took 11.63 GiB of device memory (11.64 GiB/94.62 GiB used) and 289 MiB of host memory (77.96 GiB/1008 GiB used)                                                                                INFO 08-28 22:51:12 habana_model_runner.py:517] Wrapping in HPU Graph took 0 B of device memory (11.64 GiB/94.62 GiB used) and 0 B of host memory (78.35 GiB/1008 GiB used)                                                                                INFO 08-28 22:51:12 habana_model_runner.py:521] Loading model weights took in total 11.63 GiB of device memory (11.64 GiB/94.62 GiB used) and 686.8 MiB of host memory (78.35 GiB/1008 GiB used)                                                                                - THUDM/chatglm3-6b faied!
Error info: Graph compile failed. synStatus=synStatus 26 [Generic failure].                                                                                Traceback (most recent call last):
  File "/workspace/script/test_llm_generate_modellist.py", line 49, in <module>
    output = test_llm_model(model=model)
  File "/workspace/script/test_llm_generate_modellist.py", line 14, in test_llm_model
    llm = LLM(model=model,
  File "/workspace/vllm/vllm/entrypoints/llm.py", line 155, in __init__
    self.llm_engine = LLMEngine.from_engine_args(
  File "/workspace/vllm/vllm/engine/llm_engine.py", line 456, in from_engine_args
    engine = cls(
  File "/workspace/vllm/vllm/engine/llm_engine.py", line 266, in __init__
    self._initialize_kv_caches()
  File "/workspace/vllm/vllm/engine/llm_engine.py", line 365, in _initialize_kv_caches
    self.model_executor.determine_num_available_blocks())
  File "/workspace/vllm/vllm/executor/habana_executor.py", line 77, in determine_num_available_blocks
    return self.driver_worker.determine_num_available_blocks()
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/workspace/vllm/vllm/worker/habana_worker.py", line 142, in determine_num_available_blocks
    self.model_runner.profile_run()
  File "/workspace/vllm/vllm/worker/habana_model_runner.py", line 1141, in profile_run
    self.warmup_scenario(max_batch_size,
  File "/workspace/vllm/vllm/worker/habana_model_runner.py", line 1203, in warmup_scenario
    self.execute_model(inputs, kv_caches, warmup_mode=True)
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/workspace/vllm/vllm/worker/habana_model_runner.py", line 1652, in execute_model
    output = self.model.sample(
  File "/workspace/vllm/vllm/worker/habana_model_runner.py", line 241, in sample
    return self.model.sample(*args, **kwargs)
  File "/workspace/vllm/vllm/model_executor/models/chatglm.py", line 386, in sample
    next_tokens = self.sampler(logits, sampling_metadata)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1535, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1585, in _call_impl
    result = forward_call(*args, **kwargs)
  File "/workspace/vllm/vllm/model_executor/layers/sampler.py", line 138, in forward
    sample_results, maybe_sampled_tokens_tensor = _sample(
  File "/workspace/vllm/vllm/model_executor/layers/sampler.py", line 711, in _sample
    return _sample_with_torch(
  File "/workspace/vllm/vllm/model_executor/layers/sampler.py", line 592, in _sample_with_torch
    sample_results = _greedy_sample(seq_groups, greedy_samples)
  File "/workspace/vllm/vllm/model_executor/layers/sampler.py", line 336, in _greedy_sample
    samples_lst = samples.tolist()
RuntimeError: Graph compile failed. synStatus=synStatus 26 [Generic failure].

Fixed with https://github.com/HabanaAI/vllm-fork/pull/245


README Updates to improve clarity

This PR aims to improve the description text available in the README.md file. With better hierarchy structure for the text, community members receive more/better information and are able to use the tool without much further help. The README will continue to improve as RN macOS becomes more distinct from React Native itself, and this creates a better structure for improvements.

Thanks, that's a good start. I'm planning to also add Real World Examples or "Built with RN for MacOS" section.

@ptmt I would actually say to add both sections in there. Real World Examples can be any source code repo of actual idiomatic applications built with RN for macOS and Built with RN for macOS can be implemented/added when we have actual applications in production. I'm working on a simple app that demonstrates how to use RN for macOS (still working on figuring out routing solution with ReactNavigation or another library of the sort) so we can add that to the Examples lists too.


using svg for chevron to work on windows

What does this PR do?
This uses an svg for the custom drop-down chevron because on windows the font that is being used to render the character ^ is super skinny, and does not look anything like the standard select dropdowns with the down arrow.
BEFORE ON WINDOWS.

AFTER ON WINDOWS.
https://user-images.githubusercontent.com/599418/106965041-4e860900-6700-11eb-87b4-8f4d8c9c05cb.mov
AFTER ON MAC

What issues does this PR fix or reference?
@W-8852383@

I'm fixing this in the PR to remove the magnifying glass.  @jonnyhork


[FEATURE]: Support PowerScale in CSM Observability

Describe the solution you'd like
Support PowerScale in CSM Observability, e.g. performance metrics, capacity metrics, topology and dashboards.

All the PRs are merged, close this issue.


apigatewayv2 controller v0.0.6 has problems for to run the pods

Describe the bug
I'm try install the version v0.0.6 (This was release yesterday) for apigatewayv2 controller, but it is'not working for me.
helm install works fine, but the pods never starts, and the pod describe command (kubectl describe pod $POD_NAME -n $NAMESPACE) show an error.

Steps to reproduce
I'm installing using this guide https://aws-controllers-k8s.github.io/community/docs/user-docs/install/.
export SERVICE=apigatewayv2
export RELEASE_VERSION=v0.0.6
export CHART_REF=$SERVICE-chart
export CHART_REPO=public.ecr.aws/aws-controllers-k8s/$CHART_REF
export CHART_PACKAGE=$CHART_REF-$RELEASE_VERSION.tgz
mkdir -p $CHART_EXPORT_PATH
helm pull oci://$CHART_REPO --version $RELEASE_VERSION -d $CHART_EXPORT_PATH
tar xvf $CHART_EXPORT_PATH/$CHART_PACKAGE -C $CHART_EXPORT_PATH
helm install ack-${SERVICE}-controller
$CHART_EXPORT_PATH/$SERVICE-chart
--namespace $NAMESPACE
--set serviceAccount.create=false
--set aws.region=$AWS_REGION
Environment

Kubernetes version: 1.19
Using EKS (yes/no), if so version?: eks.6
AWS service targeted (S3, RDS, etc.): apigatewayv2

Hi @estebancatano! Would you mind pasting any log output from the failed controller Pod please? Thank you!

Hi @estebancatano , Thanks for reaching out.
We have PR out for updating the install doc which shall be merged soon, But I can recommend you two updates that will make the controller install successfully for you.

Please use --set aws.account_id flag during helm install
Please also remove serviceAccount.create=False unless your default user has permission to read/write on APIGatewayv2 CRDs.

Again, apologies for the friction you faced because of our docs getting out of date. We are going to fix it ASAP.

Hi @vijtrip2 thanks for your answer, the problem was resolved with the flag --set aws.account_id
Thanks!


Actions - send Email on Success/Failure

Feature Description
On GitHub, I get emails every time a run succeeds or fails:

In Gitea, even though emails are set up (and working), I'm not getting any emails when a job runs (whether successful or failed).
Would it be possible to be able to set that up?
If that could be a setting in the YAML file, even better!
Thank you very much!
Screenshots
No response

I would like a more general 'event driven messaging system', as I also would like to get an email when a pull request is created, or when a pull request results in a merge conflict.

I needed notifications for job failures so I added this step to most of my workflows:
- name: Send mail
    if: failure()
    uses: https://github.com/dawidd6/action-send-mail@v3
    with:
        to: ${{ secrets.MAIL_TO }}
        from: Gitea <gitea@hostname>
        subject: ${{ gitea.repository }} ${{gitea.workflow}} ${{ job.status }}
        priority: high
        convert_markdown: true
        html_body: |
            ### Job ${{ job.status }}

            ${{ github.repository }}: [${{ github.ref }}@${{ github.sha }}](${{ github.server_url }}/${{ github.repository }}/actions)

I tried to create a link to the failed action by adding runs/${{ github.run_id }} to the url, but it didn't work

Thanks @GammaGames
How do you make it run this only at the end of the workflow, whether it was successful or failed?
If we don't make it dependent, it might run in parallel with the rest, but if we make it dependent, then only if everything else succeeds, the email will be sent.
Also, "success()", "failure()", etc, seem to be per Job, and not per Action/Workflow.
Or am I missing something? :)
Thank you!

I believe you are correct, having built-in notifications would be the best solution anyway. But for anyone else with simple workflows, my solution might work for now!

Should be a per-user setting to get notified only for their own pushes:
https://docs.github.com/en/account-and-profile/managing-subscriptions-and-notifications-on-github/setting-up-notifications/configuring-notifications#github-actions-notification-options

If the pusher's email address is made available to the action, it shouldn't be too hard to write a action that sends the actual mail, I assume. That should bridge us over until a propert notification system is in place.

This could work, for sending an email to the user who broke the build:

add a step at the end of the job

name: OnFailure
if: ${{ failure() }}
env:
PUSHER_ID: "${{ gitea.event.pusher.id }}"
PUSHER_EMAIL: "${{ gitea.event.pusher.email }}"
run: echo FAILED $PUSHER_ID $PUSHER_EMAIL

that prints FAILED 2<EMAIL_ADDRESS>in my case. since I don't allow email addresses to be public.

extend that, to use the ID and curl to access the email address of the user:

curl -X 'GET'
'https://git.yourdomain.com/api/v1/admin/emails'
-H 'accept: application/json'
-H 'authorization: Basic xyz' \    <<<< needs to be for an admin user
| jq ...

extend it again to send mail using your favorite bash method, e.g. with ssmtp

/attempt #23725


DSET-3951: Log also amount of transferred bytes

🥅 Goal
It looks that the commands for pulling dataset-latest does not work quite well. Let's update them.
🛠 Solution
It looks to me, that the least error prone solution is to delete that branch first before we try to pull it. Then we can check it out and pull.
🏫 Testing

Go to the repository - dataset-exporter-opentelemetry
Update it - git pull; make submodule-pull
Go to the directory dataset-go and switch to the current branch - git checkout DSET-3951-benchmarking-log-transferred-bytes-and-throughput
Go to the root directory of that folder.
Build docker image - make docker-build
Go to reliability directory - scripts/reliability
Run test - ./test.sh
You can see, that log line showing amount of transferred bytes is there:

dataset-collector-rel     | 2023-05-30T15:42:42.093Z      info    client/client.go:320    Buffers' Queue Stats:   {"kind": "exporter", "data_type": "logs", "name": "dataset/logs", "processed": 1, "enqueued": 1, "dropped": 0, "waiting": 0}
dataset-collector-rel     | 2023-05-30T15:42:42.093Z     info    client/client.go:331    Events' Queue Stats:{"kind": "exporter", "data_type": "logs", "name": "dataset/logs", "processed": 3963, "enqueued": 3963, "waiting": 0}
dataset-collector-rel     | 2023-05-30T15:42:42.093Z      info    client/client.go:345    Transfer Stats: {"kind": "exporter", "data_type": "logs", "name": "dataset/logs", "bytesSentMB": 0.47244739532470703, "bytesAcceptedMB": 0.06749248504638672, "throughputMBpS": 0.0005624237685745855, "perBufferMB": 0.06749248504638672, "successRate": 0.14285887306771525}

Codecov Report

Merging #27 (dea7c71) into main (eca25cb) will decrease coverage by 0.75%.
The diff coverage is 94.29%.

@@            Coverage Diff             @@
##             main      #27      +/-   ##
==========================================
- Coverage   72.03%   71.29%   -0.75%
==========================================
  Files          10       10
  Lines        1298     1320      +22
==========================================
+ Hits          935      941       +6
- Misses        303      318      +15
- Partials       60       61       +1

Impacted Files
Coverage Δ

pkg/client/add_events.go
80.67% <60.00%> (-2.17%)
:arrow_down:

internal/pkg/os_util/os_util.go
100.00% <100.00%> (ø)

pkg/buffer_config/buffer_config.go
52.07% <100.00%> (ø)

pkg/client/client.go
81.07% <100.00%> (-2.44%)
:arrow_down:

pkg/config/config.go
88.61% <100.00%> (+3.80%)
:arrow_up:

From the demo instance:
otel-col                 | 2023-05-30T16:29:22.433Z     info    client/client.go:328    Buffers' Queue Stats:   {"kind": "exporter", "data_type": "logs", "name": "dataset/bbb", "processed": 5, "enqueued": 5, "dropped": 0, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.433Z     info    client/client.go:339    Events' Queue Stats:    {"kind": "exporter", "data_type": "logs", "name": "dataset/bbb", "processed": 1816, "enqueued": 1816, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.433Z     info    client/client.go:353    Transfer Stats: {"kind": "exporter", "data_type": "logs", "name": "dataset/bbb", "bytesSentMB": 1.7470026016235352, "bytesAcceptedMB": 1.7470026016235352, "throughputMBpS": 0.029113767424345235, "perBufferMB": 0.34940052032470703, "successRate": 1}
otel-col                 | 2023-05-30T16:29:22.433Z     info    client/client.go:328    Buffers' Queue Stats:   {"kind": "exporter", "data_type": "traces", "name": "dataset/aaa-tracing", "processed": 3, "enqueued": 3, "dropped": 0, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.433Z     info    client/client.go:339    Events' Queue Stats:    {"kind": "exporter", "data_type": "traces", "name": "dataset/aaa-tracing", "processed": 1335, "enqueued": 1335, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.434Z     info    client/client.go:353    Transfer Stats: {"kind": "exporter", "data_type": "traces", "name": "dataset/aaa-tracing", "bytesSentMB": 0.6831750869750977, "bytesAcceptedMB": 0.6831750869750977, "throughputMBpS": 0.011385420406876193, "perBufferMB": 0.22772502899169922, "successRate": 1}
otel-col                 | 2023-05-30T16:29:22.434Z     info    client/client.go:328    Buffers' Queue Stats:   {"kind": "exporter", "data_type": "traces", "name": "dataset/ccc-tracing", "processed": 3, "enqueued": 3, "dropped": 0, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.434Z     info    client/client.go:339    Events' Queue Stats:    {"kind": "exporter", "data_type": "traces", "name": "dataset/ccc-tracing", "processed": 1335, "enqueued": 1335, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.434Z     info    client/client.go:353    Transfer Stats: {"kind": "exporter", "data_type": "traces", "name": "dataset/ccc-tracing", "bytesSentMB": 0.6831750869750977, "bytesAcceptedMB": 0.6831750869750977, "throughputMBpS": 0.011385838934378157, "perBufferMB": 0.22772502899169922, "successRate": 1}
otel-col                 | 2023-05-30T16:29:22.467Z     info    client/client.go:328    Buffers' Queue Stats:   {"kind": "exporter", "data_type": "traces", "name": "dataset/bbb", "processed": 3, "enqueued": 3, "dropped": 0, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.467Z     info    client/client.go:339    Events' Queue Stats:    {"kind": "exporter", "data_type": "traces", "name": "dataset/bbb", "processed": 1335, "enqueued": 1335, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.467Z     info    client/client.go:353    Transfer Stats: {"kind": "exporter", "data_type": "traces", "name": "dataset/bbb", "bytesSentMB": 0.6831750869750977, "bytesAcceptedMB": 0.6831750869750977, "throughputMBpS": 0.011379832774586363, "perBufferMB": 0.22772502899169922, "successRate": 1}
otel-col                 | 2023-05-30T16:29:22.471Z     info    client/client.go:328    Buffers' Queue Stats:   {"kind": "exporter", "data_type": "logs", "name": "dataset/ccc-tracing", "processed": 5, "enqueued": 5, "dropped": 0, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.471Z     info    client/client.go:339    Events' Queue Stats:    {"kind": "exporter", "data_type": "logs", "name": "dataset/ccc-tracing", "processed": 1816, "enqueued": 1816, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.471Z     info    client/client.go:353    Transfer Stats: {"kind": "exporter", "data_type": "logs", "name": "dataset/ccc-tracing", "bytesSentMB": 1.7470026016235352, "bytesAcceptedMB": 1.7470026016235352, "throughputMBpS": 0.029115542837839785, "perBufferMB": 0.34940052032470703, "successRate": 1}
otel-col                 | 2023-05-30T16:29:22.476Z     info    client/client.go:328    Buffers' Queue Stats:   {"kind": "exporter", "data_type": "logs", "name": "dataset/aaa-tracing", "processed": 5, "enqueued": 5, "dropped": 0, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.476Z     info    client/client.go:339    Events' Queue Stats:    {"kind": "exporter", "data_type": "logs", "name": "dataset/aaa-tracing", "processed": 1816, "enqueued": 1816, "waiting": 0}
otel-col                 | 2023-05-30T16:29:22.476Z     info    client/client.go:353    Transfer Stats: {"kind": "exporter", "data_type": "logs", "name": "dataset/aaa-tracing", "bytesSentMB": 1.7470026016235352, "bytesAcceptedMB": 1.7470026016235352, "throughputMBpS": 0.029113305790744823, "perBufferMB": 0.34940052032470703, "successRate": 1}


Displaying FugitiveHead with icons

I have the following configuration
let g:lightline = {
      \ 'component_function': {
      \   'gitbranch': 'FugitiveHead' },
(...)
      \ 'active': {
      \   'left': [
      \     [ 'mode', 'filesymb', 'paste' ],
      \     [ 'gitbranch', 'readonly', 'filename', 'modified' ] ],
(...)
      \  }

It works fine but it doesn't have icons although I have devicons. Do people usually use another function or?

Yes, create a function component and prepend your favorite icon string.

Yes, create a function component and prepend your favorite icon string.

Oh ok I thought that there might be some other function with icons, thanks

Oh ok I thought that there might be some other function with icons, thanks


Unable to close search view

When visiting /search URL directly, there is no visible way to cancel search and return to the world view.
Cc @oliverroick

Hi @vgeorge is this open to contributions? I would like to work on this issue.

Hi @SehrishHussain, currently we don't have capacity to take external contributions for this project. We really appreciate the offer and hope to collaborate in the future when we're able to support community involvement.

@vgeorge Thanks for the update! I’ll keep an eye on this project and would love to be one of the first to contribute if you ever need a hand. Just tag me anytime!


add cronjob to run the ndmis performance report job every morning at 3am

What does this pull request do?
add cronjob to run the ndmis performance report job every morning at 3am
What is the intent behind these changes?
run the report using automated cronjob

PLEASE DO NOT MERGE

PLEASE DO NOT MERGE

We could, if it's behind a {{- if not .Values.env_details.production_env -}}

Tested with
helm template --set image.tag=my.fake.release hmpps-interventions-service hmpps-interventions-service --values=values-preprod.yaml | yq e -


Confusion with Min recommendation vs System Information in Performance docs

Description:
Add additional information when MI is used as a centralised server, which is recommended to have at least 2 cores instead of 0.5 cores

Fixed in MI docs https://mi.docs.wso2.com/en/latest/install-and-setup/install/installation-prerequisites/


Default 16:9 aspect ratio in image component is no longer working

Check the bottom of this page:
https://equinor.sanity.studio/global/desk/topicContent;a3180c05-7e7b-4c6d-807f-76bea24ba44b
16:9 (default) and selected Original aspect ratio gives the same result.
https://equinor.sanity.studio/global/desk/topicContent;a3180c05-7e7b-4c6d-807f-76bea24ba44b
(We've had #1752 for this earlier)

@meols Can you take another look now?

Thanks @BorghildSelle - looks good, and approved :smile:


Add .gitignore file for default project

That is to say, thanks, but I don't want to merge this now.


Optmize for thousands of test cases

I have 2600+ test cases, and the generated mochawesome.html file needs 14 seconds to be opened by Chrome.
Is there any idea to optmize it?
PS: The generated mochawesome.html file is 10MB and mochawesome.json is 8.2MB

I'm certainly open to any ideas you have for reducing size.

I just released v3.0.0 which includes enhancements to reduce the overall file sizes and improve perceived rendering.


Fix non-existent method

Description
Chef runs using the latest release complain with and fail on
NoMethodError: undefined method `starts_with' for "ALL":String

Presumably because it should be start_with?.  I haven't gone the full nine yards to check if this is a complete fix, sorry - just trying to get the ball rolling for a patch.
Issues Resolved
[List any existing issues this PR resolves]
Check List

[ ] All tests pass. See https://github.com/chef-cookbooks/community_cookbook_documentation/blob/master/TESTING.MD
[ ] New functionality includes testing.
[ ] New functionality has been documented in the README if applicable
[ ] All commits have been signed for the Developer Certificate of Origin. See https://github.com/chef-cookbooks/community_cookbook_documentation/blob/master/CONTRIBUTING.MD

I just pushed this one to master. I'll have a release in a few seconds


Fix 1.0.2 heartbeat test

Checklist

[x] tests are added or updated
[x] CLA is signed

Description of change

The heartbeat_test reaches into the internals of libssl and calls some internal functions. It then checks the return value to check its what it expected. However commit fa4c374 changed the return value of these internal functions, and now the test is failing.
The solution is to update the test to look for the new return value.

Merged. Thanks.


ENH: Make cython_special actual code, not autogenerated

The intention is to update cython_special to go along with our general modernisation of special
Back in https://github.com/scipy/scipy/pull/20260, we updated the ufunc machinery so that there was no longer any need for autogenerated loop functions for ufuncs. This PR handles the complementary Cython generation. For cython_special, however, the process is way simpler. The functions in cython_special just provide Cython-level access to the scalar kernels. There is no need for any autogeneration really, hence we can just paste in the current autogenerated Cython file (cython_special.pyx and cython_special.pxd) and start modifying them.
This will allow us to start deleting ufuncs from _generate_pyx.py, meaning we will no longer be duplicating ufuncs. We will also not need to maintain all these C wrappers for each scalar kernel, which are being wrapped in Cython anyway. The goal is cython_special should be wrapping the functions directly, in a way that is easy to modify. It may be possible to ultimately turn cython_special into a pxd file, which would also take it out of the binary size.

This is, in fact, done. @steppi What do you think?
This PR makes _generate_pyx.py generate only the ufuncs, everything else has been removed from it.

As an interim measure, this sounds like a good idea. I haven't considered things carefully yet though and want to hear feedback from others too. We need to update the documentation here: https://docs.scipy.org/doc/scipy/dev/api-dev/special_ufuncs.html; It needs updating anyway. I can submit a PR to your branch with an update to that doc page tomorrow if you like.

_cython_special_custom.pxi

Great ideas! Done. Your suggested update to meson.build also fixed a build issue with scipy.special, which now is as is before.

Yep, that's https://github.com/scipy/scipy/pull/20422#issuecomment-2045980635, should be fixed soon.

I believe this broke scikit-learn
      [199/249] Compiling Cython source /home/tcaswell/source/p/scikit-learn/scikit-learn/sklearn/tree/_criterion.pyx
      FAILED: sklearn/tree/_criterion.cpython-312-x86_64-linux-gnu.so.p/sklearn/tree/_criterion.pyx.c
      cython -M --fast-fail -3 '-X language_level=3' '-X boundscheck=False' '-X wraparound=False' '-X initializedcheck=False' '-X nonecheck=False' '-X cdivision=True' '-X profile=False' --include-dir /home/tcaswell/source/p/scikit-learn/scikit-learn/.mesonpy-tqmycukf /home/tcaswell/source/p/scikit-learn/scikit-learn/sklearn/tree/_criterion.pyx -o sklearn/tree/_criterion.cpython-312-x86_64-linux-gnu.so.p/sklearn/tree/_criterion.pyx.c

      Error compiling Cython file:
      ------------------------------------------------------------
      ...

      import numpy as np
      cimport numpy as cnp
      cnp.import_array()

      from scipy.special.cython_special cimport xlogy
      ^
      ------------------------------------------------------------

      /home/tcaswell/source/p/scikit-learn/scikit-learn/sklearn/tree/_criterion.pyx:23:0: 'scipy/special/cython_special.pxd' not found

Reverting to ad0edb9 makes sckit-learn build again.

Right, thanks for flagging @tacaswell and thanks for answering @lucascolley. Looks like there is already a fix in the works! Not sure how that happened, but we've been discovering quite a lot of untested things in SciPy special.


Add basic support for HMIP-eTRV (Homematic IP Thermostat)

This is super basic support for the new Homematic IP thermostat HMIP-eTRV. It enables pyhomematic to read the current temperature and read/write the set point temperature.
For usage with Home Assistant, additional changes in the components' source of home assistant have to be done:
components/homematic.py:65 - Add IPThermostat to list of supported devices
DISCOVER_CLIMATE: [
        'Thermostat', 'ThermostatWall', 'MAXThermostat', 'ThermostatWall2',
        'MAXWallThermostat', 'IPThermostat'],

/components/climate/homematic.py:90 - HMIP uses another key for the set point temp, so we need to handle it without breaking compatibility:
@property
    def target_temperature(self):
        """Return the target temperature."""
        if not self.available:
            return None
        if self._data.get('SET_POINT_TEMPERATURE'):
            return self._data.get('SET_POINT_TEMPERATURE', None)
        else:
            return self._data.get('SET_TEMPERATURE', None)

/components/climate/homematic.py:125 - Add the new key to the data dict
def _init_data_struct(self):
        """Generate a data dict (self._data) from the Homematic metadata."""
        # Add state to data dict
        self._data.update({"CONTROL_MODE": STATE_UNKNOWN,
                           "SET_TEMPERATURE": STATE_UNKNOWN,
                           "SET_POINT_TEMPERATURE": STATE_UNKNOWN,
                           "ACTUAL_TEMPERATURE": STATE_UNKNOWN})

I'm wondering if it wouldn't make sense to hide internal differences instead of adding another class for the same device type with internal differences.
I'm not critizing this pull request. I thought about it while I added a temperature sensor to the max wall thermostat.

I totally agree but you know how things are when you just want stuff to work rather soon.

@jannau
You're correct that that's not nice. But we're doing that for pretty much every device where minor differences are present. After all, pyhomematic just presents an interface for external usage by other apps (HASS for that matter). And HASS in the end takes care of slipping one single platform (climate in this case) over a bunch of technically different devices with similar functionality.
Hiding the internal differences would make the classes more complex, and we'd possibly lose some flexibility as well. So in my opinion the separate classes for different devices (or simliar with internal differences) keep us on the safe side to ensure functionality won't be affected when making changes to just one class.

Ich schreibe mal deutsch, dann bin ich etwas schneller.
Ich denke der Code hier ist Okay. Ich werde es in HASS so umbauen, dass es schaut welche der zwei Datenpunkte vorhanden ist und entsprechend handelt.

Eigentlich gibt es ja sogar noch eine dritte variante, siehe hier: https://github.com/danielperna84/pyhomematic/issues/43#issuecomment-276750682
Aber das kann in einem weiteren Schritt behandelt werden. Kernaussage soll sein: wenn in HASS umgebaut wird, dann so, dass es beliebig viele Varianten / Implementierungen geben könnte. SO switch/case-mäßig.

Sollte dynamisch gehen.

Ok, dann merge ich das mal.


feat: removing unused variable

Feature or Bugfix

Feature

Detail

Removing unused variable in local graphql server pointing to a fixed AWS region

Relates
N/A
Security
N/A
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

@dlpzx anything blocking to merge this?

Merged to release branch. We just wanted to make sure that the issue shown by npm has been addressed (closed in #816)


feat: users profile page

Header view:

Nice work! I think we could have the overlapping between the logo box and the avatar later. I rather having more support to API right now.


Updates playground version

I am not sure about package-lock.json update though

I have updated the TinyGo extension (with a commit I had already prepared locally and with some extra changes), so this PR is now basically done. Thank you for the reminder though!

@aykevl Do you mean you've updated extension from off-tree? I was playing with this extension and wanted to have latest preview implementation.


How we can use a lib features either New or Old without explaining them in the DOCS !
You've a very Good library but the Docs are poor !

That being said.
What are your pain points? How can we help?

PS: We are working hard on our libraries, and documentation should evolve with them.

I am new in dependency injection.
I did a search of the best and the easiest DI frameworks and I liked Kodein the problem is the documentation are out dated to learn from and there's no rich blog posts to learn from too !

This might be resolved on the mid-term. don't hesitate to raise issues or asking questions on our slack channel if you need help.


Hacktoberfest-2022

Please add my file to in your repository with label Hacktoberfest

Kindly star the repository on above top right :)


Double COB

I have yet to narrow down the when or how that this is happening, but some carb entries made using the pump (seen this on 722 and 723 pumps so far) have been read as double and used by OpenAPS as double...so far these have been entered using pump bolus wizard and have not been "backed out" of before bolus.
If there's some suggestions that you have to help gather useful info (command lines to run? and when?) that would help troubleshoot this...I'm happy to implement.
Sometimes the double COB sticks around affecting temp basals (first screen shot), and other times I've seen it resolve (second screen shot did eventually resolve the COB to the correct number, unsure of time frame, but probably 15-20 min?)

Looking at this one more in detail....over time, here's the info from the pills
You can see the problem start.  The careportal somehow has a double COB already.  OpenAPS pill during this time is reporting COB=0.  Shows carbs entered at 9:22

At 9:25, same situation.  OpenAPS pill showing COB=0, NS COB pill showing same doubled carbs.

At 9:28, OpenAPS still COB=0

At 9:30, OpenAPS pill starts to show the problem

I think this is just an issue with entering carb details twice. A Bolus Wizard record is created when you enter BG and carbs (when the recommendation is made), so if you back out of it the "BolusWizard" record is already there. This means that if you enter it again, you get a second record.
These bolus wizard records are separate from bolus records, which are created when the bolus is actually delivered.
The easiest way to avoid this problem is to only enter carbs in to the bolus wizard once, and to not back out of it once you've started. It's difficult to remove these records automatically, because you can't tell the difference between a mistaken double entry, and someone putting in carbs and deliberately not bolusing.

My concern is that these are not where someone is backing out of bolus wizard.  They are following the bolus wizard all the way through.  Enter the bolus wizard, they give no BG, they enter carbs, they get the recommended bolus and confirm to deliver.
What about that would cause a double entry?

@Kdisimone it sounds like most of these self resolve a few minutes later, too - can you confirm the typical time period where COB re-normalizes, or is this not always happening in every case?

Have you looked at the Nightscout treatments API (https://yournightscout/api/v1/treatments.json) to see what is actually present in the DB?  Could you share a copy-paste excerpt from there, or PM one of us the Nightscout URL to take a look?

This one today is ongoing.  Not self resolving

I will pull up the treatments API now

this covers the time frame of the 9:22 bolus today
{"_id":"5898b847bd4bf2dc76c9dfc8","duration":30,"raw_duration":{"_type":"TempBasalDuration","_description":"TempBasalDuration 2017-02-06T09:48:48 head[2], body[0] op[0x16]","timestamp":"2017-02-06T09:48:48-08:00","_body":"","_head":"1601","duration (min)":30,"_date":"30b0094611"},"timestamp":"2017-02-06T09:48:48-08:00","absolute":0.575,"rate":0.575,"raw_rate":{"_type":"TempBasal","temp":"absolute","_description":"TempBasal 2017-02-06T09:48:48 head[2], body[1] op[0x33]","timestamp":"2017-02-06T09:48:48-08:00","_body":"00","_head":"3317","rate":0.575,"_date":"30b0094611"},"eventType":"Temp Basal","medtronic":"mm://openaps/mm-format-ns-treatments/Temp Basal","created_at":"2017-02-06T09:48:48-08:00","enteredBy":"openaps://medtronic/723","carbs":null,"insulin":null},{"_id":"5898b439bd4bf2dc76c9dfc2","duration":30,"raw_duration":{"_type":"TempBasalDuration","_description":"TempBasalDuration 2017-02-06T09:28:48 head[2], body[0] op[0x16]","timestamp":"2017-02-06T09:28:48-08:00","_body":"","_head":"1601","duration (min)":30,"_date":"309c094611"},"timestamp":"2017-02-06T09:28:48-08:00","absolute":1.6,"rate":1.6,"raw_rate":{"_type":"TempBasal","temp":"absolute","_description":"TempBasal 2017-02-06T09:28:48 head[2], body[1] op[0x33]","timestamp":"2017-02-06T09:28:48-08:00","_body":"00","_head":"3340","rate":1.6,"_date":"309c094611"},"eventType":"Temp Basal","medtronic":"mm://openaps/mm-format-ns-treatments/Temp Basal","created_at":"2017-02-06T09:28:48-08:00","enteredBy":"openaps://medtronic/723","carbs":null,"insulin":null},{"_id":"5898b2aebd4bf2dc76c9dfba","duration":30,"raw_duration":{"_type":"TempBasalDuration","_description":"TempBasalDuration 2017-02-06T09:25:32 head[2], body[0] op[0x16]","timestamp":"2017-02-06T09:25:32-08:00","_body":"","_head":"1601","duration (min)":30,"_date":"2099094611"},"timestamp":"2017-02-06T09:25:32-08:00","absolute":0.575,"rate":0.575,"raw_rate":{"_type":"TempBasal","temp":"absolute","_description":"TempBasal 2017-02-06T09:25:32 head[2], body[1] op[0x33]","timestamp":"2017-02-06T09:25:32-08:00","_body":"00","_head":"3317","rate":0.575,"_date":"2099094611"},"eventType":"Temp Basal","medtronic":"mm://openaps/mm-format-ns-treatments/Temp Basal","created_at":"2017-02-06T09:25:32-08:00","enteredBy":"openaps://medtronic/723","carbs":null,"insulin":null},{"_id":"5898b2aebd4bf2dc76c9dfbb","duration":0,"bolus":{"_type":"Bolus","_description":"Bolus 2017-02-06T09:22:04 head[8], body[0] op[0x01]","timestamp":"2017-02-06T09:22:04-08:00","_body":"","appended":[{"_type":"UnabsorbedInsulinBolus","_description":"UnabsorbedInsulinBolus unknown head[17], body[0] op[0x5c]","_body":"","_head":"5c11105d04066704167b0414b11416d914","data":[{"amount":0.4,"age":93},{"amount":0.15,"age":103},{"amount":0.55,"age":123},{"amount":0.5,"age":433},{"amount":0.55,"age":473}],"_date":""}],"programmed":1.05,"duration":0,"amount":1.05,"unabsorbed":0.6,"_head":"01002a002a001800","type":"normal","_date":"0496490611"},"timestamp":"2017-02-06T09:22:03-08:00","created_at":"2017-02-06T09:22:03-08:00","carbs":14,"ratio":"13","wizard":{"_type":"BolusWizard","bg":0,"_description":"BolusWizard 2017-02-06T09:22:03 head[2], body[15] op[0x5b]","timestamp":"2017-02-06T09:22:03-08:00","_body":"0e500082645a00002a000000002a5a","appended":[{"_type":"UnabsorbedInsulinBolus","_description":"UnabsorbedInsulinBolus unknown head[17], body[0] op[0x5c]","_body":"","_head":"5c11105c04066604167a0414b01416d814","data":[{"amount":0.4,"age":92},{"amount":0.15,"age":102},{"amount":0.55,"age":122},{"amount":0.5,"age":432},{"amount":0.55,"age":472}],"_date":""}],"bg_target_high":90,"sensitivity":100,"carb_input":14,"carb_ratio":13,"food_estimate":1.05,"unabsorbed_insulin_total":0,"correction_estimate":0,"bg_target_low":90,"_head":"5b00","bolus_estimate":1.05,"_date":"0396090611"},"eventType":"Meal Bolus","insulin":1.05,"notes":"Normal bolus with wizard.\nProgrammed bolus 1.05\nDelivered bolus 1.05\nPercent delivered:  100%\nFood estimate 1.05\nCorrection estimate 0\nBolus estimate 1.05\nTarget low 90\nTarget high 90\nHypothetical glucose delta -105","medtronic":"mm://openaps/mm-format-ns-treatments/Meal Bolus","enteredBy":"openaps://medtronic/723"},{"_id":"5898b2aebd4bf2dc76c9dfbc","carbs":14,"ratio":"13","wizard":{"_type":"BolusWizard","bg":0,"_description":"BolusWizard 2017-02-06T09:21:18 head[2], body[15] op[0x5b]","timestamp":"2017-02-06T09:21:18-08:00","_body":"0e500082645a00002a000000002a5a","carb_input":14,"bg_target_high":90,"sensitivity":100,"carb_ratio":13,"food_estimate":1.05,"unabsorbed_insulin_total":0,"correction_estimate":0,"bg_target_low":90,"_head":"5b00","bolus_estimate":1.05,"_date":"1295090611"},"timestamp":"2017-02-06T09:21:18-08:00","created_at":"2017-02-06T09:21:18-08:00","eventType":"Carb Correction","notes":"Food estimate 1.05\nCorrection estimate 0\nBolus estimate 1.05\nTarget low 90\nTarget high 90\nHypothetical glucose delta 0","medtronic":"mm://openaps/mm-format-ns-treatments/Carb Correction","enteredBy":"openaps://medtronic/723","insulin":null},{"_id":"5898b113bd4bf2dc76c9dfb2","duration":30,"raw_duration":{"_type":"TempBasalDuration","_description":"TempBasalDuration 2017-02-06T09:18:38 head[2], body[0] op[0x16]","timestamp":"2017-02-06T09:18:38-08:00","_body":"","_head":"1601","duration (min)":30,"_date":"2692094611"},"timestamp":"2017-02-06T09:18:38-08:00","absolute":1,"rate":1,"raw_rate":{"_type":"TempBasal","temp":"absolute","_description":"TempBasal 2017-02-06T09:18:38 head[2], body[1] op[0x33]","timestamp":"2017-02-06T09:18:38-08:00","_body":"00","_head":"3328","rate":1,"_date":"2692094611"},"eventType":"Temp Basal","medtronic":"mm://openaps/mm-format-ns-treatments/Temp Basal","created_at":"2017-02-06T09:18:38-08:00","enteredBy":"openaps://medtronic/723","carbs":null,"insulin":null},

I confirm this issue with my 522 pump

Sent the treatments link to you @scottleibrand.  Happy to send to you @cjo20 too, if you want?

this would appear to be the problem...but what is causing that?

Here is a more readable version of those two records:
[
  {
    "enteredBy": "openaps://medtronic/723",
    "medtronic": "mm://openaps/mm-format-ns-treatments/Meal Bolus",
    "notes": "Normal bolus with wizard.\nProgrammed bolus 1.05\nDelivered bolus 1.05\nPercent delivered:  100%\nFood estimate 1.05\nCorrection estimate 0\nBolus estimate 1.05\nTarget low 90\nTarget high 90\nHypothetical glucose delta -105",
    "insulin": 1.05,
    "eventType": "Meal Bolus",
    "_id": "5898b2aebd4bf2dc76c9dfbb",
    "duration": 0,
    "bolus": {
      "_date": "0496490611",
      "type": "normal",
      "_head": "01002a002a001800",
      "unabsorbed": 0.6,
      "_type": "Bolus",
      "_description": "Bolus 2017-02-06T09:22:04 head[8], body[0] op[0x01]",
      "timestamp": "2017-02-06T09:22:04-08:00",
      "_body": "",
      "appended": [
        {
          "_date": "",
          "data": [
            {
              "age": 93,
              "amount": 0.4
            },
            {
              "age": 103,
              "amount": 0.15
            },
            {
              "age": 123,
              "amount": 0.55
            },
            {
              "age": 433,
              "amount": 0.5
            },
            {
              "age": 473,
              "amount": 0.55
            }
          ],
          "_head": "5c11105d04066704167b0414b11416d914",
          "_body": "",
          "_description": "UnabsorbedInsulinBolus unknown head[17], body[0] op[0x5c]",
          "_type": "UnabsorbedInsulinBolus"
        }
      ],
      "programmed": 1.05,
      "duration": 0,
      "amount": 1.05
    },
    "timestamp": "2017-02-06T09:22:03-08:00",
    "created_at": "2017-02-06T09:22:03-08:00",
    "carbs": 14,
    "ratio": "13",
    "wizard": {
      "_date": "0396090611",
      "sensitivity": 100,
      "bg_target_high": 90,
      "appended": [
        {
          "_date": "",
          "data": [
            {
              "age": 92,
              "amount": 0.4
            },
            {
              "age": 102,
              "amount": 0.15
            },
            {
              "age": 122,
              "amount": 0.55
            },
            {
              "age": 432,
              "amount": 0.5
            },
            {
              "age": 472,
              "amount": 0.55
            }
          ],
          "_head": "5c11105c04066604167a0414b01416d814",
          "_body": "",
          "_description": "UnabsorbedInsulinBolus unknown head[17], body[0] op[0x5c]",
          "_type": "UnabsorbedInsulinBolus"
        }
      ],
      "_body": "0e500082645a00002a000000002a5a",
      "timestamp": "2017-02-06T09:22:03-08:00",
      "_description": "BolusWizard 2017-02-06T09:22:03 head[2], body[15] op[0x5b]",
      "bg": 0,
      "_type": "BolusWizard",
      "carb_input": 14,
      "carb_ratio": 13,
      "food_estimate": 1.05,
      "unabsorbed_insulin_total": 0,
      "correction_estimate": 0,
      "bg_target_low": 90,
      "_head": "5b00",
      "bolus_estimate": 1.05
    }
  },
  {
    "insulin": null,
    "enteredBy": "openaps://medtronic/723",
    "medtronic": "mm://openaps/mm-format-ns-treatments/Carb Correction",
    "_id": "5898b2aebd4bf2dc76c9dfbc",
    "carbs": 14,
    "ratio": "13",
    "wizard": {
      "_date": "1295090611",
      "bolus_estimate": 1.05,
      "_head": "5b00",
      "bg_target_low": 90,
      "correction_estimate": 0,
      "unabsorbed_insulin_total": 0,
      "food_estimate": 1.05,
      "carb_ratio": 13,
      "_type": "BolusWizard",
      "bg": 0,
      "_description": "BolusWizard 2017-02-06T09:21:18 head[2], body[15] op[0x5b]",
      "timestamp": "2017-02-06T09:21:18-08:00",
      "_body": "0e500082645a00002a000000002a5a",
      "carb_input": 14,
      "bg_target_high": 90,
      "sensitivity": 100
    },
    "timestamp": "2017-02-06T09:21:18-08:00",
    "created_at": "2017-02-06T09:21:18-08:00",
    "eventType": "Carb Correction",
    "notes": "Food estimate 1.05\nCorrection estimate 0\nBolus estimate 1.05\nTarget low 90\nTarget high 90\nHypothetical glucose delta 0"
  }
]

@cjo20 are you thinking that's what a "back out" would look like in treatments log?  @ceben80 can you go back to your treatment logs and look?

 ;)

Shall I try deleting from NS and see if this helps OpenAPS?

Before deleting, let's look at the pumphistory.json and see if it shows up twice there, or if it's getting the second one from NS...

They should be able to do that when he's picked up from school

I think the fact that both are from "openaps://medtronic/723" suggests that it's originating from the pump. I have a vague recollection of something about mmhistorytools combining dual entries of carbs in some cases. I think that the same functionality was added to oref0 a couple of releases ago?
This is a pure speculation without having looked at code yet: It's possible that 723 pumps generate a "Carb Correction" entry when the bolus wizard is started, and the "Meal Bolus" when the bolus is given. If the event-combining code looks for two events in the same minute then whether they get removed or not would depend on whether both events happened in the same minute or not.

The next bolus and carb entry were done by same school nurse and no double entry happened.  Perhaps those were same minute reading for that entry in pump.  I'll make a note about that time too.

But, I also think this is happening on 722 pumps.  Have another rig/pump/openaps user on 722 that I've seen this not self-resolve on.

Having looked at the code, I don't think the de-duplication stuff was actually merged, hence deleting my comment.

Perhaps someone would like to test https://github.com/openaps/oref0/pull/375 and see if it fixes this?

I can test that...might take a couple days to see if the negative can be proven, but happy to try.

It's worth trying, but I don't think it will fix it. The de-duplication checks for two events with the same carb total with the same timestamp. The two entries here are 45 seconds apart.
https://github.com/openaps/oref0/pull/375/files#diff-060f20ba122b5ef0476eec300d40eeacR55

Afaik the earlier OpenAPS behavior was to always read these as two separate events but only consider the carbs from one of them. The current pump read logic has an issue where the pump can be read during the time the bolus is being administered, so there's a time slot between user having entered the carbs and not having yet confirmed the bolus that'll create a Wizard event with carbs but no bolus and another where during the bolus the pump record will show the carbs and the part of the bolus that's been administered so far but not the entire amount (to ensure the record contains up to date information on bolus given even if the power is cut in the middle of the bolus).
IMO entering carb events without bolusing using the wizard should not be a supported feature and we should change the logic to not consider the carb event without the bolus event (do not sync to Nightscout / do not add to COB). Additionally the pump history read for the ongoing bolus should not be supported; I recall Scott had a reason for wanting to read history even if we detect a bolus is ongoing but can't remember what the rationale was. (There's separate event logic in some pump models to enter log entries, which could be used for additional carbs in addition to NS logging?)
I have a Node based tool I've used as a replacement for the shell script based pump log rewriter the default loop uses, which has logic for merging / detecting the carb event without bolus; I can check how to apply this to reading the log into COB and we could replace parts of the current NS sync with a node based one with more logic on what gets synced.
(Also reminds me, decocare doesn't correctly label all the events with a BG value with the correct BG units on mmol pumps - anyone with python skills wanna help?)

I agree we should unsupport carb-only bolus wizard entries, and ignore carbs entered without at least a 0.1U bolus.
Only reason I can remember for wanting to read pumphistory while bolusing is for extended boluses.
In the SMB branch I've re-done the pump-loop aliases as a single shell script (based on some stuff @cjo20 did): that could have a bolusing check before pulling pumphistory, if that's important.  We already can't enact temps if bolusing, so it only matters for uploading to NS I think.

I agree we should unsupport carb-only bolus wizard entries, and ignore carbs entered without at least a 0.1U bolus.

AFAIK, the bolus wizard is the only way to enter carbs in offline mode. If we require insulin to be delivered, it would be impossible to enter carb corrections or any other carbs that don't correspond to a bolus when offline. If that's the case, I think it should be supported. Is there a way to distinguish between failed/cancelled bolus wizard records vs ones that are intentionally entered without carbs?
BTW, a while ago I looked into a case where carbs were being logged after cancelling the bolus wizard. To confirm the expected behavior, I uploaded my pump data to carelink.minimed.com and the carbs were in fact being logged there as well. So at least according to Medtronic, the current behavior is "correct". Not sure if we care about parity with Medtronic (and potentially Tidepool), but it's something to consider.

I don't know of any way to tell the difference between canceled bolus wizard entries and entries where zero bolus was selected.  Given that, I would prefer to force users to enter a 0.1U bolus with their carbs if they want them considered by oref0, so there is no ambiguity or chance of misinterpretation.

If you're going to force a bolus to enter carbs, please can the check be >0 insulin (rather than >= 0.1)

Ok, yeah.  For 523s you can do 0.025U instead of 0.1U like you have to do on 522s, so that would be better.

523 still requires bolus to be >= 0.1 (but basal rate can be as low as .025/hr).
@scottleibrand If you're going to change the behavior to ignore bw entries without insulin, can you make it an optional feature? It's not feasible for small children to get 0.1U along with a carb correction in order for carb logging to work offline.

@moomoobloo 554 allows 0.025u boluses.

I just tested and was able to deliver a 0.025U bolus on a non-loopable 523 with 2.5B.  I presume loopable 523s are the same, but maybe not.

Hi all - we have a 754 pump and have had issues with the COB report.  The APS will often report more carb than was actually given.  The NS number when we hover over the pill looks as we would expect.  We have not determined cause.  It is NOT double entries - we no longer use careportal for any entries that involve insulin (basically any entry that goes through the pump).  We do use careportal for carb corrections (w/o insulin, of course).  Instead our DS enters a note at school when he eats so we have info we need - in the note he indicates insulin given, any corrections, and carb total etc.  We have him do this in the event that the APS isn't working or pump info isn't populated for some reason so we will still have a notion about what he's got for IOB and COB.  This elimiated the double entry issue but did not stop the weird carb numbers that appear.  The 'extra; COB will sometimes resolve itself, but often can be a long time (i.e. hours).

One thought - we were just reviewing our COB issues - we can't recall ever seeing this issue except in the evenings.  DS also almost always has a very big spike in the evenings - shortly after he falls asleep, which seems to correspond to the spike.  Admittedly, as we've always had to be 'on' because of the spike, we are usually both watching and it is possible we haven't noticed the same COB issues during the day (though usually at least one of us is watching, most of the day)therefore we may have the impression it doesn't happen any other time and that could be erroneous....
We had theorized that  APS, when seeing the large rise is assuming COB that is not accounted for and then was estimating COB instead of using the actual COB, which is why we end up with greater COB than he has actually eaten or sometimes end up with a sudden change to a bigger number of COB hours after he has been asleep.  Short of that, we have not had a great understanding.  Because of this, though, we tend to watch more carefully in the evenings in case a large COB were to cause the APS to not respond properly to a low and then we intervene if we need to.  I'm sure several of you can debunk our working theory :)

Our 723 goes 0.025 for boluses.

and thank you all so much for looking into this today!  much appreciated!

It seems our 754 only does 0.1 - am surprised that the 754 and 554 aren't the same in this regard...

@JELCRAWFORD which "COB report" are you talking about?  Do you have the Nightscout COB pill enabled?

yes, both NS and APS so that when we hover we can see NS COB.  Display defaults to APS number

And are you seeing it switch back and forth sometimes, or is it always the OpenAPS COB that you're seeing unexpected numbers with?  If it's the latter, you might want to check your treatments collection to see if you're seeing double carb entries, or if it might be something else.  @Kdisimone how did you get that screenshot of the carb entries?  Is that the mlab interface?

Prior to this moment, I'd have said it is always OpenAPS, however, as it stands, we are showing 3 carbs in OpenAPS COB pill from a 6:15 supper of 60 carbs, but 44 carbs according to NS.  In this instance, I'd be inclined to go with OpenAPS number...  Admittedly, at least the 44 is less than the 60 as we'd expect a decaying number of carbs...

Can you try disabling the NS COB pill for awhile and just use the OpenAPS pill's COB number?  I don't like the way the NS COB pill switches back and forth between the OpenAPS data and its own calculation.  We might need to do some work on a way to disable that, so it always displays the last OpenAPS COB number, and never displays it own calculation.  That would be a different issue, though.  For this issue, we just need to figure out if you're seeing double COB or something different.

yup, can do.

Carb entries screen shot were from NS reports, treatment tab. @scottleibrand

Thanks.  @JELCRAWFORD can you also check your NS reports, treatment tab the next time you see an issue, and see if there are duplicate treatments there?

yup.  can do.

@scottleibrand I had checked it there on previous times I've seen this happen, and there were double entries in there on those times too.

@Kdisimone Yeah, I think we have a pretty good handle on what's happening in your case, just not why or what to do about it.  Maybe https://github.com/openaps/oref0/pull/375 will prove a decent fix; if not we'll need to look at some other options to filter out carb-only treatments like we discussed earlier, or maybe figure out some way to deduplicate them.

Here...this one happened to us on Jan 30th.

Ok - I hope these come out ok.  First set of images - NS screen shot - Jan 4th.  2nd and 3rd images are of the treatment reports - I think on looking it is somehow summing all of the COB w/o decay over a long period of time....

Sorry, first image was meant to be 2nd set of data.  Please refer to this image below of NS that corresponds with treatment data above.

I don't see any doubled carb entries there, so looks like your issue is different. Can you open a new issue so we can troubleshoot the COB decay separately?

NOW 2nd set - Jan 3rd - note the time - 1:12AM  - no way we should have 26 COB (beautiful line though, so that made up for it in some regard!)

maybe.....  I might need help with how to do that from here...

I'm new to OpenAPS. Got setup last weekend and ran it for maybe 8 hours. Just started again tonight. Each time I bolus through our 522, NS shows COB as doubled. (OpenAPS pill and NS COB pill) I've tried bolusing with a fake BG (in range) and without. It still happens. I've tried using the easy bolus (B button) and through the bolus wizard and it still happens.  Last weekend, it resolved itself within an hour. Tonight, I just deleted the treatment. You can see from the treatment report, both show up at 6:03. I did not back out of a bolus or double enter carbs.

Adding this pic. Can't seem to get a pic showing when it was entered at 6:03, so the doubled carbs showed 80, but you can see this one has 76 - still more than the 40 it should have been.

I was able to determine the double carb entries appear in OpenAPS COB pill and NS COB pill if bolusing through pump, but Loop app is enabled on (either in open or closed Loop mode). When bolusing through Loop app (again either in closed or open Loop mode), double carb entries do not appear in NS COB or OpenAPS COB pills. The solution seems to be either to close Loop app entirely and bolus through pump or bolus through Loop app.

Sounds like for Loop/OpenAPS dual rig users, it was Loop uploading to NS causing the double entries. I wrote up info in the docs (https://github.com/openaps/docs/pull/650) about the suggestion to turn off loop's ability to upload to NS to resolve this if people want to use Loop to bolus but OpenAPS for looping. Additional PRs to that welcome, but will close this issue in next few days and consider it resolved if we don't hear of any other users for which this solution does not resolve.

My original issue did generate from Loop app use...it was only during OpenAPS use.  @scottleibrand Do you think that #375 will solve it?  I can use that I guess...problem seems to be so intermittent that I'm not sure how long it would take to prove the negative (no more double COBs).

I'm seeing the issue show up again immediately after my rig and pump lost connection then were reconnected. Something in that process is causing a problem.

My girlfriend experienced the same issue. She was using bolus wizard and enter 55 carbs but then went back and modified it to 65. Pumphistory shows both entries for some reason.
She is using Veo 554.
I've digged into pumphistory.json and found this
[
  {
    "_type": "BolusWizard",
    "bg": 0,
    "bg_target_high": 6.1,
    "_description": "BolusWizard 2017-04-22T19:49:02 head[2], body[15] op[0x5b]",
    "timestamp": "2017-04-22T19:49:02",
    "_body": "419000501e2c00014400000001443d",
    "_head": "5b00",
    "unabsorbed_insulin_total": 0,
    "correction_estimate": 0,
    "_date": "4231131611",
    "bolus_estimate": 8.1,
    "appended": [
      {
        "_type": "UnabsorbedInsulinBolus",
        "_description": "UnabsorbedInsulinBolus unknown head[11], body[0] op[0x5c]",
        "data": [
          {
            "amount": 1,
            "age": 30
          },
          {
            "amount": 0.5,
            "age": 250
          },
          {
            "amount": 2.7,
            "age": 380
          }
        ],
        "_body": "",
        "_head": "5c0b281ec014fac06c7cd0",
        "_date": ""
      },
      {
        "_body": "",
        "_head": "3108",
        "_type": "Base",
        "_date": "4231131611",
        "_description": "Base (2017, 4, 22, 19, 49, 2) head[2], body[0] op[0x31]"
      }
    ],
    "bg_target_low": 4.4,
    "carb_ratio": 8,
    "food_estimate": 8.1,
    "carb_input": 65,
    "sensitivity": 3
  },
  {
    "_type": "BolusWizard",
    "bg": 0,
    "bg_target_high": 6.1,
    "_description": "BolusWizard 2017-04-22T19:48:28 head[2], body[15] op[0x5b]",
    "timestamp": "2017-04-22T19:48:28",
    "_body": "379000501e2c00011000000001103d",
    "_head": "5b00",
    "unabsorbed_insulin_total": 0,
    "correction_estimate": 0,
    "_date": "5c30131611",
    "bolus_estimate": 6.8,
    "bg_target_low": 4.4,
    "carb_ratio": 8,
    "food_estimate": 6.8,
    "carb_input": 55,
    "sensitivity": 3
  }
]

Brief analysis shows that the one that we want to ignore doesn't have appended field. I've modified oref0-meal code yesterday to check forappended field. After 24h it seems that with this small change it is working fine. Anyone knows what appended field is used for?

That field represents the data from the pump, which Nightscout doesn't do anything with.
You can't edit the immutable records in the pump, so editing in NS just results in duplicating it. On one level, the fix is "don't do that", but we probably also need more comprehensive code to detect and deal with duplicates. Unfortunately, there are many different ways for users to enter boluses and carbs, so there are a lot of different cases to deal with. To date, no one has decided to take on that task, and we all just learn to stick to input methods that don't generate duplicates.

In our case we have medtronic cgm so we rely on openaps to upload the data to nightscout.
The solution in this case would be to ignore bolus wizard entries that doesn't have appended field when uploading to NS and when calculating meal.json.
In https://github.com/openaps/oref0/issues/387#issuecomment-277803122 the second entry also doesn't have the appended field.

Seems to be resolved through a number of solutions. please reopen or create a new issue if this arises in another setup.


IdentityPopover: wrong numbers

user: /rmrk/u/DSdZVzpW6MZgYw2ajxXLmDYox17X8SnNzSz5rGyZ6niiA8j
see screenshot

SOLD: 0
Sold: 68
could be joined with #3160
edit:
In local env, still wrong numbers

related to

https://github.com/kodadot/nft-gallery/pull/3175


Subsequent Auth Fails with Token

Hi Tom,
Neat project. I noticed something weird. I am using a FastAPI app, in my app.py I always make a connection and instantiate the Q object (= Questrade(refresh_token='XX') ).
The first time I run the code it works fine, and a restart causes 400 bad requests. It only works if I change the refresh token from the dashboard or have Q = Questrade()  (without the refresh token).
I figure this might be an issue with the API maybe.

This code works fine  BUT you must authenticate with the token first and only once. Thereafter use the cached OAuth credentials.

I'm running into the same issue.  How can we validate if the access_token in ~/.questrade.json is still valid and if not use the refresh_token to get a new access_token

I admit that managing the life cycle is not intuitive. You can check my fork of this repository to see where I added some behavior that removes OAuth state caching from the file system. Also look at my Python Connection class to see how it handles the API logic. For my application I didn't want files lying around that had valid OAuth credentials.
Possibly another way to do this without any modification of the API is to generate a new token and immediately delete ~/.questrade.json. Use the presence of ~/.questrade.json as a discriminant to figure out if the connection needs a token parameter.

I would just do this:
try:
    q = Questrade(refresh_token=refresh_token)
except Exception as e:
    print(e)
    q = Questrade()


Integrate Wallet Connect

@S2kael Please describe your plan here:

Work with @Sokol142196 to clarify this task requirement
What you need to implement

From SubConnect
From Wallet

Core feature for Wallet Connect
Extension setting for Wallet Connect: Manage session ...
What design do you need?

Having some problems with eth_sign, eth_signTypedData. Therefore, these methods are not currently supported

Sign message:

Substrate:

polkadot_signTransaction

Evm:

eth_signTransaction
eth_sendTransaction

Core hasn't supported eth_signTransaction. Therefore, these methods are not currently supported.

Version test:
Please check isssues:

[ ] UI

[ ] Add validate for URI field

[ ] Add error message in case pairing already existed.

Actual: Show "failed to add connection"

Expect: Change to message ""

Version test: https://file.cdmteck.com/s/4oimk9zDJ8R5Aai/download?path=%2F&files=./upgrade-ui-pr-1581-build-1.0.12-2023-07-03T11-24-46UTC.zip

[ ] Update UI:

Icon connect on the Connect screen
UI bug when scrolling on the List connection

[ ] Error page when go to the List connection after connected https://paritytech.github.io/polkadot-onboard successfully

Version test: https://file.cdmteck.com/s/4oimk9zDJ8R5Aai/download?path=%2F&files=./upgrade-ui-pr-1581-build-1.0.12-2023-07-04T11-41-49UTC.zip
Validation passed for cases:

Create connection
Disconnect
Sign request

Follow-up case auto-disconnect


[WFLY-10726] (Test) Need to override getParameterValues in SPFormAuth…

…enticationRequestWrapper
JIRA: https://issues.jboss.org/browse/WFLY-10726
Note: This is a test for a fix in picketlink and requires picketlink upgrade containing https://github.com/jbossas/redhat-picketlink-bindings/pull/49
Thanks for submitting your Pull Request!
Please make sure your PR meets the following requirements:

[ ] Pull Request title is properly formatted: [WFLY-XYZ] Subject or WFLY-XYZ Subject
[ ] Pull Request contains link to the JIRA issue(s)
[ ] Pull Request contains description of the issue(s)
[ ] Pull Request does not include fixes for issues other than the main ticket
[ ] Attached commits represent units of work and are properly formatted

For bigger changes, major and minor component upgrades make sure your PR also meets following requirements:

[ ] Pull Request requires a change to the documentation
[ ] Documentation have been updated accordingly
[ ] Tests were added to cover changes

For new features ensure as well:

[ ] Analysis was done
[ ] Test Plan has been done
[ ] Tests were verified in advance

If you are not an active contributor of the WildFly project you can request sponsorship by one of the members to help guide you through the process.

@spyrkob Adding the hold label until we have the upgrade

@spyrkob Why is this PR opened without the required upgrade?

@kabir sorry, I didn't know the process here - in future is it better to wait until the new version of component is released and merged before opening test PRs for it?

Yes

I'm closing this based on the missing picketlink upgrade.


Exporting tilemap PNG cuts off first tile

Looks like if you save a tilemap as a PNG the first tile is empty. This doesn't happen on the json exporter.

This was fixed.


Implement faker.js

Context
We want to start using Faker.js (https://github.com/marak/Faker.js/) for generating fake data in tests.
Acceptance criteria

Faker.js dependency exists in shopware-pwa.
There is an example in codebase on how to use Faker.js.

@mkucmus as you were the 1st one to use that you may write a quick note on that and close the issue. :)

Faker.js dependency exists in shopware-pwa.
faker was installed and it's available under "faker" dependency
There is an example in codebase on how to use Faker.js.

you can use faker by importing it with import faker from "faker" or import only the selected methods which are grouped by functionalities, here is a list of them:

address
commerce
company
database
date
finance
git
hacker
helpers
image
internet
lorem
name
phone
random
system
vehicle

real world example taken from the packages/shopware-6-client/tests/services/CustomerService/register.spec.ts:
``
import { name, address, random, phone, internet } from "faker";
const customerData = {
salutationId: random.uuid(),
firstName: name.firstName(),
lastName: name.lastName(),
password: internet.password(8),
email: internet.email(),
billingAddress: {
countryId: random.uuid(),
street: address.streetName(),
zipcode: address.zipCode(),
city: address.city(),
phoneNumber: phone.phoneNumber()
}
}
``


Hi Martin, Thanks for the this great work. Could you guide me how to login into azure without interactive browser window because I'm trying to explore how to aut0mate this via azure deveops pipeline

Hi Martin, Thanks for the this great work. Could you guide me how to login into azure without interactive browser window because I'm trying to explore how to aut0mate this via azure deveops pipeline

Thanks Martin. Looking forward to see your blog post for a such great work.

Sorry, I didn't get a notification about this issue.
Thanks @Eonasdan for addressing it.


Fix "single comment" behavior for non-official deployments

If updates are made to a pull request and a comment from the bot already exists, that comment should be updated; a new comment should not be added. However, this functionality is broken for non-official deployments -- ie, deployments using a GitHub user other than "pep8speaks". This commit fixes this by using the BOT_PASSWORD env var to check for an existing comment, rather than hardcoding the user ID.

This is a great update, thank you @eeshugerman !


Fix picnicapi search (again)

It seems that the Github API has been changed again. I'm not an expert Python developer, but tried to propose a working solution. Possibly it can be improved. I use it in combination with Home Assistant Picnic integration for which the search function was also broken (https://github.com/home-assistant/core/issues/115351), now it seems to work again.
I have therefore tried to build upon the outstanding pull request from thijmen-j
https://github.com/MikeBrink/python-picnic-api/pull/25
The Picnic API now returns a nested json structure which needs to be search through to find search results. I found this other project that makes use of the git and used their solution as inspiration.
https://github.com/simonmartyr/picnic-api/blob/main/search_page.go

Will this be approved/fixed soon? @corneyl

@popeye1979 I'm afraid I'm not a maintainer for this repo, so there's not much I can do.
@MikeBrink can you have a look or add someone as maintainer (or both)? Or would you advise to start a fork for further maintenance?

works for me as well

I emailed @MikeBrink about maintenance of this repo, but got no response. Maybe we should lean into forking or at least referring to this branch in Home Assistant?
Apart from that, would it be possible to place libraries as this one under the home assistant organization?


Python codes?

Could you add your python codes in this repository? Thanks.

Sorry. I found it in roca directory.


Dubbo GSoC 2023 - Development of Dubbo Admin Dashboard UI Pages

Responsible for the building of the Dubbo Admin console pages.

I am very interested in this task, and I will submit a proposal for this task in the future.

I am interested in this task. My weChart is<PHONE_NUMBER>9 and my email is<EMAIL_ADDRESS>I want to know how to concat you. Thanks !

Check the links below for reference of the scope of this project:
https://qedzyx.axshare.com/#id=2pqh0k&p=admin__&g=1
https://kiali.io/docs/features/

You can leave messages directly here, or join the Dubbo channel on Wechat by ssearching Apache Dubbo, thanks.

I am very interested in this task, My email is<EMAIL_ADDRESS>and my Wechat is<PHONE_NUMBER>1.

I am very interested in this task! i am into graphic designing ,web dev and a know a little ui/ux
my<EMAIL_ADDRESS>

We are quite interested in this task, and we will send a proposal for this task in the future.
My email<EMAIL_ADDRESS>

Check the links below for reference of the scope of this project:
https://qedzyx.axshare.com/#id=2pqh0k&p=admin__&g=1
https://kiali.io/docs/features/

Hello.
After reading the two articles you provided and dubbo-admin-ui, I think the development of Admin Dashboard this time is mainly to increase the visualization of some indicators and to help users perform related operations around the topology map. After comprehensive consideration, I think that by using the @antv/G6 library, both indicator visualization and a large number of topological relationships can be satisfied. Hope to be able to participate in this project.
Thanks!

Check the links below for reference of the scope of this project:
https://qedzyx.axshare.com/#id=2pqh0k&p=admin__&g=1
https://kiali.io/docs/features/

Hello.
After reading the two articles you provided and dubbo-admin-ui, I think the development of Admin Dashboard this time is mainly to increase the visualization of some indicators and to help users perform related operations around the topology map. After comprehensive consideration, I think that the use of @antV/G2 and @antV/G6 libraries can satisfy indicator visualization and a large number of topological relationships. Hope to be able to participate in this project.
Thanks!


[CSFix] Add support for classof for all fixes

Require that all sub-classes of ContextualMismatch provide a specific fix kind;
Add static bool classof(ConstraintFix *) to all fixes that don't currently have it;
Rename fix/diagnostic for checked casts that always succeed;
Fix use of ContextualMismatch in a couple of places where IgnoreContextualType is more appropriate.

@swift-ci please clean test

@swift-ci please smoke test


feat!: automod support

Summary

automod uwu
discord/discord-api-docs#4860
bugs
nextcord.Intents.all() fails
adds

enums.TriggerType
enums.EventType
enums.KeywordPresetRule
Intents.automod_configuration
Intents.automod_execution
Intents.automod
automod.AutoModerationRule
enums.ActionType
enums.KeywordPresetType
enums.EventType
enums.TriggerType
http.HTTPClient.list_guild_automod_rules
http.HTTPClient.get_automod_rules
http.HTTPClient.create_automod_rule
http.HTTPClient.modify_automod_rule
http.HTTPClient.delete_automod_rule
MessageType.automod_action
AuditLogAction.automod_rule_create
AuditLogAction.automod_rule_update
AuditLogAction.automod_rule_delete
AuditLogAction.automod_block_message
Guild.get_automod_rule
Guild.get_automod_rules

edit
changed Intents.all to account for the skip in intents values because discord doesnt like me using 17 18 19 intents bitfield >:(((((
Checklist

[ ] If code changes were made then they have been tested.

[x] I have updated the documentation to reflect the changes.
[x] I have run task pyright and fixed the relevant issues.

[x] This PR fixes an issue.
[x] This PR adds something new (e.g. new method or parameters).
[x] This PR is a breaking change (e.g. methods or parameters removed/renamed)
[ ] This PR is not a code change (e.g. documentation, README, ...)

Could your summary contain more info about what this PR will be adding

This is still a draft, generally people don't review drafts as they're the opposite of being marked for review. Drafts mean it's in progress so any review may comment on very outdated code

And also - even though it's not my library nor am I a big contributor to it - not make your commits as nonsensical as they are?
Take a look at here.

And also - even though it's not my library nor am I a big contributor to it - try to not make your commits as nonsensical as they are?
Take a look at here.

This right here.
It is a reoccurring theme in all of your issues and pull requests that they are generally always nonsensical, and on most if not all of them we tell you the exact same thing.

I am unable to import the nextcord module
This is all in a virtual environment using venv
Code
import nextcord

Traceback
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/__init__.py", line 24, in <module>
    from . import abc, opus, ui, utils
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/ui/__init__.py", line 12, in <module>
    from .button import *
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/ui/button.py", line 34, in <module>
    from .item import Item, ItemCallbackType
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/ui/item.py", line 29, in <module>
    from ..interactions import Interaction
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/interactions.py", line 40, in <module>
    from .message import Attachment, Message
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/message.py", line 55, in <module>
    from .guild import Guild
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/guild.py", line 50, in <module>
    from .automod import AutoModerationRule
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/automod.py", line 89, in <module>
    class AutoModerationRule(Hashable):
  File "/home/mouse/automod-test/venv/lib/python3.10/site-packages/nextcord/automod.py", line 240, in AutoModerationRule
    name: Optional[str] = MISSING,
NameError: name 'MISSING' is not defined

Tried
pip install git+https://github.com/MaskDuck/nextcord@MaskDuck/feat/automod -U --force-reinstall

Output of pip list
Package            Version
------------------ -------
aiohttp            3.8.1
aiosignal          1.2.0
async-timeout      4.0.2
attrs              21.4.0
charset-normalizer 2.1.0
frozenlist         1.3.0
idna               3.3
multidict          6.0.2
nextcord           2.0.0b4
pip                22.0.4
python-dotenv      0.20.0
setuptools         58.1.0
yarl               1.7.2
WARNING: You are using pip version 22.0.4; however, version 22.1.2 is available.
You should consider upgrading via the '/home/mouse/automod-test/venv/bin/python3 -m pip install --upgrade pip' command.

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pip check
No broken requirements found.

yeah but somehow it cant be merged normally.

then you should fix the core issue over flooding notifications and the PR log

@ooliver1 see #general ping

(idk why it needs 2 commit)

i think intents calculation way changed is breaking, not sure through

It makes no frontend api changes for users, Intents.all() for the user does not change. Not every code change is breaking.

ic

It is not completed

Also, I think you replace the automod uwu part in your description with something more informative about this PR.

still awaiting for reviews

still awaiting for reviews

Please do not spam GitHub with this, you've spammed discord enough. You have already had many reviews.

wait wtf

While we appreciate all the work you've put into this PR and the willingness to help, we have unfortunately decided to close the PR and move on with our own due to the continual lack of responsibility put into creating this pull request, especially after being expressly told multiple times what is expected from a contribution. This has become a huge burden on the other maintainers and contributors who are feeling burned out as a result.

Nextcord team


[Internal review] Million-scale Face SDK generated with local swagger branch and related tests.

Updated by local MillionScale Swagger branch.
After getting this reviewed, will first get the Swagger PR merged to azure-rest-api-specs and then generate SDK from its master branch.

The overall looks good. Please make sure it is compatible with both of the old and new services. The only concern is about the wait for training which may be misleading to new comers/customers.

@huxuan Yes. Confirmed this SDK works with our new service as well, in terms of functionalities regardless of faceList/personGroup.


Housekeeping

Just some more small things that I noticed while going over the code some more. I hope they fit your line of thinking and that I didn't add a superfluous noexcept or nodiscard. And you should probably check whether all of the tests run for you.

Yep, I like this! My usage of noexcept and nodiscard were fairly inconsistent, so this makes everything much neater in my opinion.


[Question/Docs]  Rt explodes, despite RMSLE score is low for SEWIR

Summary of question
Dealing with Italy dataset and using S-R trend analysis to compute the phases, we obtain some values that are not realistic when using SEWIR compartmental model to fit the curve. Rt estimation may even explode (even to 1000!). However, RMSLE is quite low.
What tried
I haven't set any further parameter for the trend estimation, it is the "very basic and default" one.
Code is presented here in the following URL, I am running locally on my laptop the rest of parameters estimations.
https://github.com/andrybicio/LDE_Project/blob/main/CovSIRphy_Analysis_v3.ipynb
For estimating the model I used:
National_scenario = cs.Scenario(jhu_data, population_data, country="Italy", province= None, tau=1440)
# Fix the first date of records
National_scenario.first_date = "24Mar2020"
# Fix the last date of records
National_scenario.last_date = "08Jan2021"
National_scenario.trend()
National_scenario.estimate(cs.SEWIRF, timeout = 360)

maybe the timeout is too low? Needs to be increased further since it does not reach convergence?

Using SEWIR-F model for parameter estimation is not recommended because we have only four observed variables (S, I, R, F) and this model needs 6 variables.

Please use SIR/SIR-D/SIR-F model for parameter estimation, or
run parameter estimation with fixed some parameters. (this is not for the above root problem, but may improve the situation.)

Example for the second solution:

Pre-estimate some of the SEWIR-F parameters: kappa/sigma/theta are also included in SIR-F
Estimate all parameter values with some fixed (pre-estimated) parameters

https://gist.github.com/lisphilar/b474c58dd4ae785fbee3d43287aa193f
For quick note, timeout is set to 10 sec.

Using SEWIR-F model for parameter estimation is not recommended because we have only four observed variables (S, I, R, F) and this model needs 6 variables.

Please use SIR/SIR-D/SIR-F model for parameter estimation, or
run parameter estimation with fixed some parameters. (this is not for the above root problem, but may improve the situation.)

Example for the second solution:

Pre-estimate some of the SEWIR-F parameters: kappa/sigma/theta are also included in SIR-F
Estimate all parameter values with some fixed (pre-estimated) parameters

https://gist.github.com/lisphilar/b474c58dd4ae785fbee3d43287aa193f
For quick note, timeout is set to 10 sec.

I will take care and try. I didn't understand this could be done. Thank you

I will take care and try. I didn't understand this could be done. Thank you

As you can see from your notebook (last cell executed), timeseries of newly fitted parameters "rho1", "rho2" and "rho3" is constant and does not change wrt phase. I'm not sure this is correct.
It happened to mine as well.
https://github.com/andrybicio/LDE_Project/blob/main/LDE_Project_Raspberry-Def.ipynb

As you can see from your notebook (last cell executed), timeseries of newly fitted parameters "rho1", "rho2" and "rho3" is constant and does not change wrt phase. I'm not sure this is correct.
It happened to mine as well.
https://github.com/andrybicio/LDE_Project/blob/main/LDE_Project_Raspberry-Def.ipynb

we have only four observed variables (S, I, R, F)

One secondary question on that, what are the actual/observed variables? I am aware that each country for sure announces daily the confirmed, the deaths and the recovered as well. That doesn't give us at most three observed variables? The fourth, the infected is calculated from the other. Is this correct?

we have only four observed variables (S, I, R, F)

One secondary question on that, what are the actual/observed variables? I am aware that each country for sure announces daily the confirmed, the deaths and the recovered as well. That doesn't give us at most three observed variables? The fourth, the infected is calculated from the other. Is this correct?

The susceptible S are extracted from the population dataset for each country/province. But (C, R, F) are indeed announced as you correctly said from the government, and you compute the actual infected (I) by subtracting the number of recovered (R) and fatalities (F) from the confirmed cases (C).
Sometimes it happen, by the way, that also active cases (people in hospital, ICU, quarantined) are announced.

The susceptible S are extracted from the population dataset for each country/province. But (C, R, F) are indeed announced as you correctly said from the government, and you compute the actual infected (I) by subtracting the number of recovered (R) and fatalities (F) from the confirmed cases (C).
Sometimes it happen, by the way, that also active cases (people in hospital, ICU, quarantined) are announced.

Consistent rho1/rho2/rho3:
Thank you for your feedback, I will check it later.
Observed variables:
Yes, the correct variables are "Population" and C/F/R. Because we have one-to-one correspondence rule (S,I) = (Population - C, C - F - R), pseudo observed variables are S/I/F/R.
The number of patients in ICU etc. are reported as mentioned and it will be great to add dataloader for them (but may need auto complement method for some countries..). They may be added to the next ODE model discussed in #379.
Because Exposed and Waiting are not observed, parameter estimation with SEWIR-F model could be deprecated. I expected we can calculate some of rho1/rho2/rho3 using linelist data, but seems not.

Consistent rho1/rho2/rho3:
Thank you for your feedback, I will check it later.
Observed variables:
Yes, the correct variables are "Population" and C/F/R. Because we have one-to-one correspondence rule (S,I) = (Population - C, C - F - R), pseudo observed variables are S/I/F/R.
The number of patients in ICU etc. are reported as mentioned and it will be great to add dataloader for them (but may need auto complement method for some countries..). They may be added to the next ODE model discussed in #379.
Because Exposed and Waiting are not observed, parameter estimation with SEWIR-F model could be deprecated. I expected we can calculate some of rho1/rho2/rho3 using linelist data, but seems not.

Regarding the parameter estimation for serial intervals and so forth using the linelist data, I would suggest the following notebook which I am taking inspiration from too. Some URLs are out-dated however.
https://github.com/micheletizzoni/covid-19/blob/master/Realtime R - MCMC.ipynb

Regarding the parameter estimation for serial intervals and so forth using the linelist data, I would suggest the following notebook which I am taking inspiration from too. Some URLs are out-dated however.
https://github.com/micheletizzoni/covid-19/blob/master/Realtime R - MCMC.ipynb

Today I don't have time for coding, but I agree with the idea

to calculate the period from onset date to confirmation date with linelist data, and
to  estimate the number of  onset (=infected without confirmation and waiting for PCR test, W) cases with the calculated period.

This seems like full complement of recovery data in some countries with recovery period.

Today I don't have time for coding, but I agree with the idea

to calculate the period from onset date to confirmation date with linelist data, and
to  estimate the number of  onset (=infected without confirmation and waiting for PCR test, W) cases with the calculated period.

This seems like full complement of recovery data in some countries with recovery period.

Yes, indeed I tried to take a look at the df of LinelistData.cleaned() and column was not present, therefore I downloaded it manually.
Moreover the distribution of time between onset and confirmed times has too many values present at dt=0, if you run it with values at present times. This does not convince me so much, honestly, but could be due to the fast response of healthcare system.

Yes, indeed I tried to take a look at the df of LinelistData.cleaned() and column was not present, therefore I downloaded it manually.
Moreover the distribution of time between onset and confirmed times has too many values present at dt=0, if you run it with values at present times. This does not convince me so much, honestly, but could be due to the fast response of healthcare system.

I calculated elapsed time (confirmed date - onset date) and get many negative values. As reported by media, many cases shows symptoms after PCR confirmation. I wrote "onset = infected without confirmation and waiting for PCR test", but we may need to revise this definition.
https://gist.github.com/lisphilar/6ded6490b4f902cb16c3dcd30ec776d2

I calculated elapsed time (confirmed date - onset date) and get many negative values. As reported by media, many cases shows symptoms after PCR confirmation. I wrote "onset = infected without confirmation and waiting for PCR test", but we may need to revise this definition.
https://gist.github.com/lisphilar/6ded6490b4f902cb16c3dcd30ec776d2

I would suggest there is an error in methodology (or in the dataset?) since frequence for negative values is way too large...
I'm seeing in the notebook I linked before that it explicitely keeps such "positive" records, I think we should keep only that subset as well:
``
Only keep records where confirmed > onset
patients = patients[patients.Confirmed >= patients.Onset]
``
On the contrary, there are too many values with large negative value (how can a person show symptoms 100-200 AFTER it has been tested positive?). I mean anything could happen in Nature, but they should appear as outliers, which is not our case.

I would suggest there is an error in methodology (or in the dataset?) since frequence for negative values is way too large...
I'm seeing in the notebook I linked before that it explicitely keeps such "positive" records, I think we should keep only that subset as well:
``
Only keep records where confirmed > onset
patients = patients[patients.Confirmed >= patients.Onset]
``
On the contrary, there are too many values with large negative value (how can a person show symptoms 100-200 AFTER it has been tested positive?). I mean anything could happen in Nature, but they should appear as outliers, which is not our case.

Have a look manually in the original csv file in excel. If you confirm these weird dates, then this would probably be an issue in the dataset. Please contact them or open a github issue in their repo.

Have a look manually in the original csv file in excel. If you confirm these weird dates, then this would probably be an issue in the dataset. Please contact them or open a github issue in their repo.

If they from their side collect correct data indeed, then I am afraid the Healthcare records themselves are wrong in the first place as they are filled by the hospitals and published, and in that case we cannot further process these, we will have to exclude them.

yes my issue refers mainly to the quality of data. Sometimes hospitals wait for some time to record the number of recovered people, in Italy I know this occurs quite often. Unfortunately this data has to be "corrected", "filtered" and/or "completed" somehow. Moreover it happened also that the daily number of cases was negative, due to some corrections applied on the following day, therefore these imprecisions must be accounted for somehow.
When daily number of cases was negative, I used to set it to zero, but this was my choice.

If they from their side collect correct data indeed, then I am afraid the Healthcare records themselves are wrong in the first place as they are filled by the hospitals and published, and in that case we cannot further process these, we will have to exclude them.

yes my issue refers mainly to the quality of data. Sometimes hospitals wait for some time to record the number of recovered people, in Italy I know this occurs quite often. Unfortunately this data has to be "corrected", "filtered" and/or "completed" somehow. Moreover it happened also that the daily number of cases was negative, due to some corrections applied on the following day, therefore these imprecisions must be accounted for somehow.
When daily number of cases was negative, I used to set it to zero, but this was my choice.

With some reasons (bias or statiscally-unexpected method in data collection), outliers could be removed from our analysis. However, I can say the histograms indicate random distribution, not normal distribution and so on. Stratification may helps us, but it will be difficult to get representative values from them.

With some reasons (bias or statiscally-unexpected method in data collection), outliers could be removed from our analysis. However, I can say the histograms indicate random distribution, not normal distribution and so on. Stratification may helps us, but it will be difficult to get representative values from them.

As discussed in #573, SIR-F model is the final model for parameter estimation at this time. Parameter estimation with SEWIR-F will raise NotImplementedError: SEWIR-F cannot be used for parameter estimation because we do not have records of Exposed and Waiting. Please use SIR-F model with covsirphy.SIRF class.


Uh oh...starting the app now just opens Messenger.com in Safari.

Reproduced on a friend's computer. Running 10.10.3. Opening the app simply opens Messenger.com in a new tab in Safari, and the app window remains blank with the loading spinner indefinitely.

+1

Looks like Facebook recently changed something. However, I can not reproduce this bug. There is a list of URLs that are loaded inside of Goofy (https://github.com/danielbuechele/goofy/blob/master/Goofy/AppDelegate.swift#L156) and it looks like we need to add something here.

+1, redefining safari to "whatever is your default browser"

Should be fixed in 2.0.3

confirmed. thanks Daniel :)

This is happening for me again with 2.1.1.

Can't reproduce with 2.1.1. Try reinstalling the app?

As a side note (having previously worked at Facebook) they do a ton of experiments where they test new code on randomly selected people. New code that might break Goofy, for example. So if it's broken for someone, that doesn't necessarily mean it will be broken for everyone (although it's a good indicator that it might be soon!)


Add resource for topmode CustomContentPane minimum width

Description

Adds themeresource for ContentPane minimum width in top displaymode
Motivation and Context

Closes #2890
How Has This Been Tested?

Tested manually
Screenshots (if appropriate):

/azp run

/azp run

/azp run

/azp run


Fix camera shifting in example demo

Removed second keypress listener for KeyL.

Fixes #3

@kensonjohnson Thanks. I missed the lines. I thought there was a mistake in the formula.


updated  js feature in index.html

close issue -> #403
https://github.com/codervivek5/VigyBag/assets/114687502/3d37d2c1-5857-4a5a-afde-d6ee91020f43

Thankyou for contribution

NO need to add JS. It's affected user experience but appreciate your work :)