Subtype Incompatibility Error with Predicate Term Types

Subject of the issue
When a predicate is defined with a type and is called in other places such as an action precondition with a subtype as a term it fails due to the assert in:
Predicate.__call__
I just started getting my hands on PDDL so I'm not sure if it is a good practice to utilize the hierarchy of the types. However, PDDL allows me so it should also be allowed. Please let me know what you think.
Your environment

OS: Ubuntu Focal
Python version: 3.8.10
Package Version 0.4.0

Steps to reproduce

Define a predicate, at, that expects two terms of type location.
Define a variable, l_city, of type city.
Attempt to use the at predicate with the term l_city.

p = Variable("p", ["person"])
l = Variable("l", ["location"])
l_city = Variable("l_city", ["city"])
at= Predicate("at", p, l)
...
work = Action(
    "work",
    parameters=[p, l_city],
    precondition=**at(p, l_city)**,
    effect=working(p),
)

Expected behaviour
The at predicate should allow the use of the l_city term because city is a subtype of location in the type hierarchy.
Actual behaviour
The library raises an error, indicating that the predicate terms' types are incorrect. It does not recognize that city is a subtype of location in the type hierarchy, resulting in an incorrect type check.
AssertionError: Types of replacements is not correct.

@mgkwon thank you very much for your interest in using pddl. I'm going to have a look at your issue and provide a fix asap!

Hi! I'm facing the same issue and was wondering if there are any updates regarding this. Is there any quick workaround to make subtypes compatible with predicates?
Thanks!

Hrmz...from the first example, it doesn't look like you have any sub-type information put in. Here's an example of how sub-typing can be done:

https://github.com/AI-Planning/pddl/blob/8e3be082c0c2142288ffb14a9766f66bd9b1febf/tests/test_domain.py#L214

That said, it doesn't look like the Variable object is associated with the domain (similar with the predicate).
@marcofavorito should the Domain object (containing type hierarchy) be used in some way for the validation of parameters?

Thanks @haz
While going through the code I stumbled upon the syntax you shared, but if I use it, and assuming I want A to be a subtype of B, and B to be a subtype of C, then it translates it simply into:
(define (domain dining-general)
    (:requirements :negative-preconditions :strips :typing)
    (:types A B C)

My understanding is that it should translate into:
(define (domain dining-general)
    (:requirements :negative-preconditions :strips :typing)
    (:types A - B - C)

the dash symbolizing a subtype relation (?) - unless I have misunderstood this (if so, would appreciate any resource I can look into to understand this).
For the second point, yes I believe this is the main issue - even when I manage to have a type hierarchy (cf. below), if a Predicate's parameter is supposed to have type C, then a parameter of type B will be rejected and return an error because it is understood as a separate/independent type (regardless of type hierarchy in the domain).
My current workaround (yikes, brace yourselves):
I've edited the regex used to parse the types to include the space. This allows me to express the type hierarchy with dashes.
https://github.com/AI-Planning/pddl/blob/8e3be082c0c2142288ffb14a9766f66bd9b1febf/pddl/custom_types.py#L30
Then disabled ( :grin: ) the lines that validate the types used in Predicates.
https://github.com/AI-Planning/pddl/blob/8e3be082c0c2142288ffb14a9766f66bd9b1febf/pddl/logic/predicates.py#L73-L76
Doing this, I obtained a correct PDDL description of the domain/problem and was solvable.

Hi,
@fenjenahwe the types argument in the Domain class constructor is of type Dict[namelike, Optional[namelike], see https://github.com/AI-Planning/pddl/blob/8e3be082c0c2142288ffb14a9766f66bd9b1febf/pddl/core.py#L53C19-L53C68
Hence, in your example, you should write:
types={
    "objects": "world",
    "location": "world",
    "hypothesis": "world",
    "agent": "objects",
    "furniture": "objects",
    "consumable": "objects",
}

Regarding @mgkwon's issue, yes there should be a check in the Domain instantiation. Will try to provide a fix (this time for real 😅 ).

Thanks!
If do write it this way, I get this:
(define (domain dining-general)
    (:requirements :negative-preconditions :strips :typing)
    (:types agent consumable furniture hypothesis location objects)

My understanding is that these are just types that are independent from each other? Or am I missing something..

Hi,
@fenjenahwe the types argument in the Domain class constructor is of type Dict[namelike, Optional[namelike], see https://github.com/AI-Planning/pddl/blob/8e3be082c0c2142288ffb14a9766f66bd9b1febf/pddl/core.py#L53C19-L53C68
Hence, in your example, you should write:
types={
    "objects": "world",
    "location": "world",
    "hypothesis": "world",
    "agent": "objects",
    "furniture": "objects",
    "consumable": "objects",
}

Regarding @mgkwon's issue, yes there should be a check in the Domain instantiation. Will try to provide a fix (this time for real 😅 ).

Thanks! If do write it this way, I get this:
(define (domain dining-general)
    (:requirements :negative-preconditions :strips :typing)
    (:types agent consumable furniture hypothesis location objects)

My understanding is that these are just types that are independent from each other? Or am I missing something..

This is another issue (different from the original one); I will make sure this is documented in another GH issue, and then addressed. Thank you very much for the report!

Regarding @mgkwon's issue, I think a good solution would be to pass the type hierarchy definition inside the Predicate constructor, e.g.:
p = Variable("p", ["person"])
l = Variable("l", ["location"])
l_city = Variable("l_city", ["city"])
at= Predicate("at", p, l, types={...})

Basically, the argument types is of the same Python type as the argument types in the Domain constructor. This adds a bit more complexity in the initialization of Predicate's instances, but I guess it is a necessary evil to preserve the "composability", bottom-up style of our APIs (that is, first I initialize variables, then predicates, etc.).
The change is less straightforward than previously thought, and since a lot work has been done in this work-in-progress PR (https://github.com/AI-Planning/pddl/pull/84) I suggest to include the fix to this issue in that line of work.

Should likely have a default for the types parameter so we don't need to specify it, ya?

@marcofavorito This wasn't ever handled, was it? The equality here doesn't quite make sense (as highlighted by @ctpelok77 separately) in type-checking an instance of a predicate:
https://github.com/AI-Planning/pddl/blob/main/pddl/logic/predicates.py#L74
Should it be a check for a non-empty intersection?


Add unit tests

This is a WIP to add unit tests to parts of the pipeline. In its current state it's mostly a prototype to ease adding more tests in the future as I believe it would help a lot:

I started by adding some unit tests for the new api since the code was still fresh in my mind. I discovered that I had missed during the review that tokens should be globally unique, which might cause some confusion if we treat tokens as passwords (?) Also I think that the unit tests could be simpler if the validation logic was not so dependent on Cohttp. @punchagan > Do you mind taking a look? :)

Then I added some tests to the Json_stream parser since I already know it's not perfect... but this revealed an unexpected bug when the log output starts directly with a json. I plan to add a lot more tests to this module now!

The main issue for writing unit tests is that we perform a lot of side effects (via ocurrent and postgresql), so I added a "mock" Postgresql module which allow the unit tests to simulate the sql server by specifying the expected queries and their outcome. I'm not yet satisfied with the sql "string" validation, so I'm open to any ideas!

In order to run the tests, you have to be inside the pipeline/ directory and execute dune runtest or dune exec tests/test.exe. @gs0510 > Do you know if this something we could automatically run on new PR?
The overall idea is that the tests/dune imports the code from pipeline/*.ml so that the modules tests/*_test.ml can access the internal functions (that would otherwise be painful to expose in the pipeline library). This also allow us to "override" a library to mock it (see tests/postgresql.ml and the missing dependency to postgresql in tests/dune). I think we should be able to do something similar for modules that depend on ocurrent.

Adding unit tests is a great idea! I was wondering about this today, while going through the json_stream code and wanting to tweak it and play around with it. I'll take a look at the tests tomorrow. :)

We'd need to update the API tests slightly with #292 merged. I'd be happy to do that @art-w !

I was going to do it to not bother you, but I would love if you could try the unit tests! I added you on github to the collaborators of my current-bench fork, so you should be able to push to this PR by adding commits on the test branch (let me know if it doesn't work, I'm not very familiar with this)

I have run the tests already in the current state, and they run well. I will update them to work with the latest changes on main. Also, I think if you enable the "Allow edits from maintainers" flag on this PR, I should be able to push to this branch without access to your fork. Could you edit the PR to enable that option?  If that doesn't work, I'll use your invitation to be a  collaborator on your fork.

Hmm the checkbox "Allow edits from maintainers" was already checked, but I'm not sure if we have the required write access.

I'll check tomorrow, and confirm. If not, I'll use the invite you shared. :)

I'll check tomorrow, and confirm. If not, I'll use the invite you shared. :)

I was able to push onto this branch, without being added as a collaborator on your fork. I'll try and update this PR with improved tests.

I've updated this PR to

updated tests to work on the code in main
updated opam file to install alcotest and alcotest-lwt to be able to run tests locally. It still doesn't help with running tests in ocaml-ci. Could you help with that, @art-w @gs0510 ?
added a make file target to run tests locally
Removed -t flag on opam install in production docker container

updated opam file to install alcotest and alcotest-lwt to be able to run tests locally. It still doesn't help with running tests in ocaml-ci. Could you help with that, @art-w @gs0510 ?

I updated the pipeline.opam file before for running tests locally. Updating the current-bench.opam file fixed the missing deps issue on ocaml-ci! :tada:

Rebased this on the lastest main to see if tests pass

Thanks! I added a version for cmdliner in pipeline.opam to fix the deployability failure :)

CI is passing 🎉 ! cc @art-w, @punchagan  :) I'll redeploy once this is also merged 😁

I think we can merge this, now? @art-w @gs0510 ? We can work on follow-ups (clean up of API functions/tests) in a separate PR, I think.

Yes, sounds good! :)


Add Persistent Volume Claim For Maven/OWASP Dependency Check Caching

Add a PVC to the CI/CD project which can be used as part of a containerTemplate in a Jenkinsfile so that Maven and OWASP Dependency Check data can be cached to improve build performance.
The Jenkinsfile changes would look like:
pipeline {
    agent {
        kubernetes {
            label 'jenkins-slave-cached'
            podTemplate {
                label 'jenkins-slave-cached'
                inheritFrom 'jenkins-slave-mvn'
                ttyEnabled true
                command 'cat'
                volumes: [
                    persistentVolumeClaim {
                        claimName 'maven-cache'
                        mountPath '/home/jenkins/.m2/repository'
                    }
                ]
            }
        }
    }
... SNIP ...

The PVC definition would look like:
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  annotations:
    volume.beta.kubernetes.io/storage-class: glusterfs-storage
    volume.beta.kubernetes.io/storage-provisioner: kubernetes.io/glusterfs
  name: maven-cache
  namespace: labs-ci-cduser1
spec:
  accessModes:
  - ReadWriteMany
  resources:
    requests:
      storage: 5Gi
status:
  accessModes:
  - ReadWriteMany
  capacity:
    storage: 5Gi

@InfoSec812 why are you enforcing the use of Gluster for this backend? Also hardcoding the storageclass name is not a good idea, we should leave this open as we do for other templates so the user can use their existing default storageclass if this exist or use any available PV

@haithamshahin333 FYI


NPM package seems not to be published.

Hi!
I am not finding the react-native-androidprogressbar package in the NPM repository.
Is it possible that the package has not yet been published in the repository?
Thx!

any updates on this?

@cpojer
If this package is in need for a maintainer to publish the package, I'd like to volunteer to be a maintainer. Would that be possible? :)

That sounds great! Could you send me your npm username to<EMAIL_ADDRESS>

@cpojer
Thanks! I just sent the email to you with my npm username :)

Successfully published this package :tada:


Musa dev fp16

merge again

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you all sign our Contributor License Agreement before we can accept your contribution.0 out of 5 committers have signed the CLA.:x: wzx:x: gliangMT:x: gonggqing:x: zehan-mt:x: qiyulei-mtwzx seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.


Nutri-Score is broken on the scan card.

https://barcode.tec-it.com/en/EAN13?data=3350033032361

@deniger could it be related to Nutri-Score display refactoring ?

Yes it could ...I will have a look tomorrow
---- On Sun, 07 Apr 2019 21:41:35 +0200<EMAIL_ADDRESS>wrote ----
@deniger could it be related to Nutri-Score display refactoring ?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub, or mute the thread.

Fixed by @deniger in a8e2de0c2a49159341b1cc333429fa9648b7edf2


DocsArchive-<IP_ADDRESS>Auto archive content

Please don't merge this PR until target archive repo PR https://github.com/OPS-E2E-PPE/docs-archive-test-target_28e785d3-6c87-4ff9-8f2e-830779ee78e4/pull/1 is merged into live branch.
Auto archive content to https://github.com/OPS-E2E-PPE/docs-archive-test-target_28e785d3-6c87-4ff9-8f2e-830779ee78e4.git

Docs Build status updates of commit bfce246:
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For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


problem description error

when question is scrapped from lc, number with powers were used to be sth like 10^5
However, with latest commit, it is copied sth like 105 which is same as naive copy version.

@all-contributors please add @sungho-joo for bug


Hello ... ??

Anyone here ??

yeah but I am no longer maintaining this project, I am doing more react native development lately and am no longer writing swift daily

:'( but the idea was great. fastlane make no fun no more ...

fastlane also gained support for writing your lanes in Swift so I would recommend using that instead


Add test for date range in License file

Fixes #50
Checklist

[x] I have made a material change to the repo (functionality, testing, spelling, grammar)
[x] I have read the [Contribution Guide] and my PR follows them.
[x] I updated my branch with the master branch.
[ ] I have added tests that prove my fix is effective or that my feature works
[ ] I have added necessary documentation about the functionality in the appropriate .md file
[ ] I have added in line documentation to the code I modified

Short description of what this PR does:

Adds test via command line to check if the License file has a correct date range. Also allows for standalone current year - for example, only the year 2017 is also valid at the time of commit.

If you have questions, please send an email to Sendgrid, or file a Github Issue in this repository.

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

 Thank you for your submission, we really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

#53 breaks this as of now. Updating.

This is a really creative way to solve this problem. Thank you!!

Hahaha, thanks !
I figured a shell script was probably better than introducing a nodejs check :)

@anshuman73
We have not been able to merge your Pull Request, but because you are awesome - we wanted to make sure you could still get a SendGrid Hacktoberfest shirt.
Please go fill out our swag form before Nov 5th and we will send the shirt! (We know that you might have tried this before and it didn’t work, sorry about that!)
You have till Nov 5th to fill out this form in order to get the Hacktoberfest shirt!
Thank you for contributing during Hacktoberfest! We hope to see you in the repos soon! Just so you know, we always give away a SendGrid shirt for your first ever non-Hacktoberfest PR that gets merged.

Hey !
I filled out the form again. Hope it worked fine this time.
Sure, as Sendgrid customer, I'd love to help make improvements in the product I use :)

Thank you @anshuman73!

Hello @anshuman73,Thanks again for the PR! We appreciate your contribution and look forward to                                              continued collaboration. Thanks!                                             Team SendGrid DX

If you are interested, we would love the opportunity to talk to you about Hacktoberfest and our API libraries.
Our agenda would be: Explore what you liked and is there anything we can do to improve?
You can grab a time on my calendar that works for you and we can have a chat on Google Hangout or Skype. If you prefer, you can email me using my GitHub username at my company’s domain.
Thank you so much,
Matt Bernier - @mbernier - SendGrid Developer Experience Product Manager
Elmer Thomas - @thinkingserious - SendGrid Developer Experience Engineer
@SendGrid


Dark mode theme

Environment

Python version: N/A
Nautobot version: N/A

Proposed Functionality
Dark mode theme for Nautobot

Use Case
Configurable option per user to enable a dark mode theme
Possibly by matching the system theme to light/dark mode

Database Changes
Storage option per user to hold theme value

External Dependencies
N/A

I know @tbotnz started this at some point

I know @tbotnz started this at some point

They did! But it wasn't quite complete and we still need some other UI elements to toggle between them and save them in preferences. Need to dig that back up!
@UnityDG Thanks for putting this on the backlog. :)

@UnityDG you could try this for now https://github.com/tbotnz/nautobot-dark-css Personally i think itd be cool to focus efforts on  reworking the UI into something completley different & modern(er) looking

Closed via #1554.


why norm by row?

hi,dear
In the line,
    scaled_verts = scale*rays_vertices
    scaled_verts /= np.linalg.norm(scaled_verts,axis = 1, keepdims=True)

if every column is the feature, why you norm by row ?
confused ahout that, should be the down ??
    scaled_verts = scale*rays_vertices
    scaled_verts /= np.linalg.norm(scaled_verts,axis = 0, keepdims=True)

could you pls help me ?
thx

Hi,
the vertiex array has shape (n_verts,3), with the rows being the 3 cartesian coordinates. As we want to norm each vertex vector to unity norm, we need to divide by the norm compute over the last (row) axis.
Hope that helps,
M


chore: arch diagram - replace nested numbering

Merging without cft tests and lint tests passing as this PR doesn't add new functionality and the lint tests were failing already (fixed in #PR11)


Search page doesn't handle server errors gracefully

Issue #261 described how a server error on the search page could result in a nested 500 page appearing in the search results area. This was fixed on the backend in #263, but the general problem still remains: if the search endpoint fails somehow, the error isn't handled and the 500 page gets embedded.
See the search JS code here and here. This code takes the response from the search query and sticks it into the page without verifying that the response code is 200. If something other than 200, an error message should be displayed instead.
(Aside: it'd be nice if this retrieval/display code was combined instead of duplicated.)
Current behavior
Server errors (500s) result in embedded error page as displayed in #261.
Expected behavior
Error message displayed to the user or other graceful handling.
Steps to replicate behavior (include URLs)
This is a little hard to replicate without being about to reliably trigger a server error. We can't guarantee there'll never be a server error on the backend; for example, Elasticsearch could fail or there could be some other unexpected problem.
One way to reproduce this is to run your Django server locally, access the search page, then stop your database service (to simulate the DB going down). Then try entering a query on the search page, and you'll see the error:

@chosak I've updated the javascript to use the same error handling as eRegs here. I also combined the code like you requested.

Thanks @nbucknor! I can confirm that this error no longer appears. Thanks also for the code cleanup.
It would be nice if there was some kind of message displayed to the user when this happens, but I've seen you've added a TODO here.


Bold makes all colors bright

It looks like onefetch -c 0 8 uses BrightBlack for both colors, even though it actually doesn't.
onefetch -b -c 0 8 properly looks like it uses Black for primary color and BrightBlack for secondary color.
This appears to be a limitation with ANSI, since echo -e "\e[0;30;1mBlack\e[0m" and echo -e "\e[0;90;1mBrightBlack\e[0m" both look the same in xterm.
Perhaps the bold flag should default to off instead of on? Or at least some warning in the help message for -c regarding this. Not sure the best way to fix this would be, but users are being limited to half of the available color options.

I fail to see any clever way to approach this, It's important to have a consistent behavior across terminals. So maybe, we should consider using only 8 colors instead of 16; I think we should keep the bold format as default.
BTW, Thanks for pointing that out @spenserblack :+1:

Yeah, I think that may be the best way. The only other way I could think of would be giving the user the option to select 16-color mode, which would automatically disable bold. But that might be behavior users would find confusing.
Tested this in Powershell too, recently, same behavior seems to apply.
So I guess the best way would be to remove half the color options and color blocks :crying_cat_face:


Decoding with transformer_moe hangs before it starts on libcudnn.so.7

Description
Decoding hangs on Successfully opened dynamic library libcudnn.so.7. Occurs even on a new VM instance (Azure) with all the requirements just installed. Using CUDA-10.1 and a Tesla K80 GPU. Reduced batch_size to just 1 which takes a couple of minutes on CPU, but seems to last indefinitely on GPU (at least an hour and a half, not waited longer).
Environment information
OS: Ubuntu 18.04

$ pip freeze | grep tensor

mesh-tensorflow==0.0.5
tensor2tensor==1.13.4
tensorboard==1.14.0
tensorflow==1.14.0
tensorflow-datasets==1.2.0
tensorflow-estimator==1.14.0
tensorflow-metadata==0.14.0
tensorflow-probability==0.7.0

$ python -V

Python 3.7.3

For bugs: reproduction and error logs
# Steps to reproduce:

CUDA_VISIBLE_DEVICES=0 t2t-decoder \
  --t2t_usr_dir=$USR_DIR \
  --data_dir=$DATA_DIR \
  --problem=mimic_discharge_summaries \
  --model=transformer_moe \
  --hparams_set=transformer_moe_base \
  --output_dir=$OUTPUT_DIR \
  --decode_hparams="beam_size=3,alpha=0.6,batch_size=1" \
  --decode_from_file=$DIR/src-test.txt \
  --decode_to_file=output.txt &

# Error logs:

WARNING: Logging before flag parsing goes to stderr.
W0821 20:58:49.202146<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/expert_utils.py:68: The name tf.variable_scope is deprecated. Please\
 use tf.compat.v1.variable_scope instead.

W0821 20:58:49.964024<PHONE_NUMBER>96864 lazy_loader.py:50]
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
  * https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.

W0821 20:58:51.827588<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/adafactor.py:27: The name tf.train.Optimizer is deprecated. Please u\
se tf.compat.v1.train.Optimizer instead.

W0821 20:58:51.827997<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/multistep_optimizer.py:32: The name tf.train.AdamOptimizer is deprec\
ated. Please use tf.compat.v1.train.AdamOptimizer instead.

W0821 20:58:51.838359<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/mesh_tensorflow/ops.py:4237: The name tf.train.CheckpointSaverListener is deprecated. Pl\
ease use tf.estimator.CheckpointSaverListener instead.

W0821 20:58:51.838499<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/mesh_tensorflow/ops.py:4260: The name tf.train.SessionRunHook is deprecated. Please use \
tf.estimator.SessionRunHook instead.

W0821 20:58:51.867746<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/rl/gym_utils.py:219: The name tf.logging.info is deprecated. Please use tf\
.compat.v1.logging.info instead.

W0821 20:58:51.894030<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/trainer_lib.py:109: The name tf.OptimizerOptions is deprecated. Plea\
se use tf.compat.v1.OptimizerOptions instead.

W0821 20:58:52.270897<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/bin/t2t-decoder:16: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity i\
nstead.

W0821 20:58:52.271061<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/bin/t2t-decoder:16: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.

W0821 20:58:52.271208<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/bin/t2t-decoder:17: The name tf.app.run is deprecated. Please use tf.compat.v1.app.run instead.

W0821 20:58:52.271745<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/trainer_lib.py:780: The name tf.set_random_seed is deprecated. Pleas\
e use tf.compat.v1.set_random_seed instead.

I0821 20:58:52.272333<PHONE_NUMBER>96864 usr_dir.py:43] Importing user module transformer_moe from path /home/aa5118/project/text-generation
W0821 20:58:52.273171<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/data_generators/text_encoder.py:938: The name tf.gfile.Exists is deprecate\
d. Please use tf.io.gfile.exists instead.

W0821 20:58:52.273323<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/data_generators/text_encoder.py:940: The name tf.gfile.Open is deprecated.\
 Please use tf.io.gfile.GFile instead.

W0821 20:58:52.382671<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/trainer_lib.py:121: The name tf.GraphOptions is deprecated. Please u\
se tf.compat.v1.GraphOptions instead.

W0821 20:58:52.382863<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/trainer_lib.py:127: The name tf.GPUOptions is deprecated. Please use\
 tf.compat.v1.GPUOptions instead.

W0821 20:58:52.383047<PHONE_NUMBER>96864 deprecation.py:323] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/trainer_lib.py:240: RunConfig.__init__ (from tensorflow.contrib.learn.python\
.learn.estimators.run_config) is deprecated and will be removed in a future version.
Instructions for updating:
When switching to tf.estimator.Estimator, use tf.estimator.RunConfig instead.
I0821 20:58:52.383207<PHONE_NUMBER>96864 trainer_lib.py:263] Configuring DataParallelism to replicate the model.
I0821 20:58:52.383281<PHONE_NUMBER>96864 devices.py:76] schedule=continuous_train_and_eval
I0821 20:58:52.383338<PHONE_NUMBER>96864 devices.py:77] worker_gpu=1
I0821 20:58:52.383389<PHONE_NUMBER>96864 devices.py:78] sync=False
W0821 20:58:52.383465<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/devices.py:139: The name tf.logging.warn is deprecated. Please use t\
f.compat.v1.logging.warn instead.

W0821 20:58:52.383523<PHONE_NUMBER>96864 devices.py:141] Schedule=continuous_train_and_eval. Assuming that training is running on a single machine.
I0821 20:58:52.383700<PHONE_NUMBER>96864 devices.py:170] datashard_devices: ['gpu:0']
I0821 20:58:52.383759<PHONE_NUMBER>96864 devices.py:171] caching_devices: None
I0821 20:58:52.383882<PHONE_NUMBER>96864 devices.py:172] ps_devices: ['gpu:0']
I0821 20:58:52.384373<PHONE_NUMBER>96864 estimator.py:209] Using config: {'_task_type': None, '_task_id': 0, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fdf92277cc0>, '_master'\
: '', '_num_ps_replicas': 0, '_num_worker_replicas': 0, '_environment': 'local', '_is_chief': True, '_evaluation_master': '', '_train_distribute': None, '_eval_distribute': None, '_experimental_max_worker_delay\
_secs': None, '_device_fn': None, '_tf_config': gpu_options {
  per_process_gpu_memory_fraction: 1.0
}
, '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_secs': None, '_log_step_count_steps': 100, '_protocol': None, '_session_config': gpu_options {
  per_process_gpu_memory_fraction: 0.95
}
allow_soft_placement: true
graph_options {
  optimizer_options {
    global_jit_level: OFF
  }
}
isolate_session_state: true
, '_save_checkpoints_steps': 1000, '_keep_checkpoint_max': 20, '_keep_checkpoint_every_n_hours': 10000, '_model_dir': '../data/t2t_experiments/transformer_moe/full_context/data', 'use_tpu': False, 't2t_device_i\
nfo': {'num_async_replicas': 1}, 'data_parallelism': <tensor2tensor.utils.expert_utils.Parallelism object at 0x7fdf92277e48>}
W0821 20:58:52.384535<PHONE_NUMBER>96864 model_fn.py:630] Estimator's model_fn (<function T2TModel.make_estimator_model_fn.<locals>.wrapping_model_fn at 0x7fdf92c0ae18>) includes params argument, but params are no\
t passed to Estimator.
I0821 20:58:52.384735<PHONE_NUMBER>96864 decoding.py:415] Performing decoding from file (../data/preprocessed/src-test.txt).
I0821 20:58:52.384802<PHONE_NUMBER>96864 decoding.py:860] Getting sorted inputs
I0821 20:58:52.535063<PHONE_NUMBER>96864 estimator.py:612] Could not find trained model in model_dir: ../data/t2t_experiments/transformer_moe/full_context/data, running initialization to predict.
I0821 20:58:52.539939<PHONE_NUMBER>96864 decoding.py:673]  batch 5727
I0821 20:58:52.540030<PHONE_NUMBER>96864 decoding.py:675] Decoding batch 0
W0821 20:58:52.551722<PHONE_NUMBER>96864 deprecation.py:323] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/decoding.py:617: py_func (from tensorflow.python.ops.script_ops) is deprecat\
ed and will be removed in a future version.

Instructions for updating:
tf.py_func is deprecated in TF V2. Instead, there are two
    options available in V2.
    - tf.py_function takes a python function which manipulates tf eager
    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to
    an ndarray (just call tensor.numpy()) but having access to eager tensors
    means `tf.py_function`s can use accelerators such as GPUs as well as
    being differentiable using a gradient tape.
    - tf.numpy_function maintains the semantics of the deprecated tf.py_func
    (it is not differentiable, and manipulates numpy arrays). It drops the
    stateful argument making all functions stateful.

W0821 20:58:52.555120<PHONE_NUMBER>96864 deprecation.py:323] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/decoding.py:950: to_int32 (from tensorflow.python.ops.math_ops) is deprecate\
d and will be removed in a future version.
Instructions for updating:
Use `tf.cast` instead.
W0821 20:58:52.560892<PHONE_NUMBER>96864 estimator.py:1000] Input graph does not use tf.data.Dataset or contain a QueueRunner. That means predict yields forever. This is probably a mistake.
I0821 20:58:52.561223<PHONE_NUMBER>96864 estimator.py:1145] Calling model_fn.
I0821 20:58:52.562110<PHONE_NUMBER>96864 t2t_model.py:2172] Setting T2TModel mode to 'infer'
I0821 20:58:52.562382<PHONE_NUMBER>96864 t2t_model.py:2172] Setting hparams.dropout to 0.0
I0821 20:58:52.562463<PHONE_NUMBER>96864 t2t_model.py:2172] Setting hparams.label_smoothing to 0.0
I0821 20:58:52.562537<PHONE_NUMBER>96864 t2t_model.py:2172] Setting hparams.layer_prepostprocess_dropout to 0.0
I0821 20:58:52.562601<PHONE_NUMBER>96864 t2t_model.py:2172] Setting hparams.symbol_dropout to 0.0
I0821 20:58:52.562671<PHONE_NUMBER>96864 t2t_model.py:2172] Setting hparams.attention_dropout to 0.0
I0821 20:58:52.562731<PHONE_NUMBER>96864 t2t_model.py:2172] Setting hparams.relu_dropout to 0.0
W0821 20:58:52.626073<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/t2t_model.py:243: The name tf.summary.text is deprecated. Please use\
 tf.compat.v1.summary.text instead.

I0821 20:58:52.789595<PHONE_NUMBER>96864 t2t_model.py:2172] Beam Decoding with beam size 3
W0821 20:58:52.852554<PHONE_NUMBER>96864 deprecation.py:323] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/beam_search.py:744: to_float (from tensorflow.python.ops.math_ops) is deprec\
ated and will be removed in a future version.
Instructions for updating:
Use `tf.cast` instead.
I0821 20:58:53.508420<PHONE_NUMBER>96864 api.py:255] Using variable initializer: uniform_unit_scaling
W0821 20:58:53.544848<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensorflow/python/autograph/converters/directives.py:117: The name tf.summary.scalar is \
deprecated. Please use tf.compat.v1.summary.scalar instead.

I0821 20:58:53.820600<PHONE_NUMBER>96864 t2t_model.py:2172] Transforming feature 'inputs' with symbol_modality_32895_512.bottom
I0821 20:58:53.841698<PHONE_NUMBER>96864 t2t_model.py:2172] Transforming feature 'targets' with symbol_modality_32895_512.targets_bottom
W0821 20:58:53.926082<PHONE_NUMBER>96864 deprecation.py:506] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/models/research/transformer_moe.py:194: calling dropout (from tensorflow.python.op\
s.nn_ops) with keep_prob is deprecated and will be removed in a future version.
Instructions for updating:
Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.
W0821 20:58:54.023731<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/layers/common_layers.py:3106: The name tf.layers.Dense is deprecated. Plea\
se use tf.compat.v1.layers.Dense instead.

W0821 20:58:54.594940<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/layers/common_layers.py:556: The name tf.layers.Conv2D is deprecated. Plea\
se use tf.compat.v1.layers.Conv2D instead.

I0821 20:58:58.462035<PHONE_NUMBER>96864 t2t_model.py:2172] Transforming body output with symbol_modality_32895_512.top
W0821 20:58:58.584813<PHONE_NUMBER>96864 deprecation.py:323] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensorflow/python/ops/math_ops.py:2403: add_dispatch_support.<locals>.wrapper (from tensorflow.p\
ython.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
W0821 20:58:58.689076<PHONE_NUMBER>96864 deprecation_wrapper.py:119] From /home/aa5118/anaconda3/lib/python3.7/site-packages/tensor2tensor/utils/t2t_model.py:1734: The name tf.saved_model.signature_constants.DEFAU\
LT_SERVING_SIGNATURE_DEF_KEY is deprecated. Please use tf.saved_model.DEFAULT_SERVING_SIGNATURE_DEF_KEY instead.

I0821 20:58:58.689570<PHONE_NUMBER>96864 estimator.py:1147] Done calling model_fn.
I0821 20:58:59.073214<PHONE_NUMBER>96864 monitored_session.py:240] Graph was finalized.
2019-08-21 20:58:59.073555: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2019-08-21 20:58:59.082555: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2019-08-21 20:58:59.085153: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55d8a72a1be0 executing computations on platform Host. Devices:
2019-08-21 20:58:59.085179: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): <undefined>, <undefined>
2019-08-21 20:58:59.087430: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1
2019-08-21 20:59:05.611072: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x55d8a9ba6c40 executing computations on platform CUDA. Devices:
2019-08-21 20:59:05.611116: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): Tesla K80, Compute Capability 3.7
2019-08-21 20:59:05.611986: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties:
name: Tesla K80 major: 3 minor: 7 memoryClockRate(GHz): 0.8235
pciBusID: 3a40:00:00.0
2019-08-21 20:59:05.612276: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.1
2019-08-21 20:59:05.614128: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10
2019-08-21 20:59:05.615971: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10
2019-08-21 20:59:05.616280: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10
2019-08-21 20:59:05.618149: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10
2019-08-21 20:59:05.619244: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10
2019-08-21 20:59:05.623303: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-08-21 20:59:05.624801: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-08-21 20:59:05.624856: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.1
2019-08-21 20:59:05.627788: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-08-21 20:59:05.627809: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0
2019-08-21 20:59:05.627817: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N
2019-08-21 20:59:05.629403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 11596 MB memory) -> physical GPU (device: 0, nam\
e: Tesla K80, pci bus id: 3a40:00:00.0, compute capability: 3.7)
2019-08-21 20:59:06.866570: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1412] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set.  If yo\
u want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU.  To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLA\
GS) or set the envvar XLA_FLAGS=--xla_hlo_profile.
I0821 20:59:06.885300<PHONE_NUMBER>96864 session_manager.py:500] Running local_init_op.
I0821 20:59:06.933789<PHONE_NUMBER>96864 session_manager.py:502] Done running local_init_op.
2019-08-21 20:59:08.180917: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10
2019-08-21 20:59:08.816787: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7

Might be related to tensorflow/tensorflow#32017

Thanks @cantwbr , possibly - will keep an eye on it. But this doesn't even get to checkpoint

Thanks @cantwbr , possibly - will keep an eye on it. But this doesn't even get to checkpoint
@amin-nejad: You are right! I think the title of issue tensorflow/tensorflow#32017 is a bit misleading. The execution reported there actually stalls after opening libcublas - just like in the execution you reported.


The "projects" page needs some content

This is resolved through https://github.com/uwescience/DSSG2016/pull/15


fix problems with recent jupyter?

This works for sure! Thanks

I just encountered the same problem and thank you so much for the timely fix. Had to use iron.vim when nvim-ipy was down and the user experience is incomparable.


Time lag in the result

thanks for the work for this great tool and it works like a charm.
Just realized that the result from the API has a few minutes lag compare to the result directly form the tradingview.
I am a premium user of tradingview. From the website you can't do much as a guest, which is the API's role fetching the data.
No sure what cause the lag. If we need to login to get realtime result, can the tool add this feature in the future? Thanks.

The code already mentioned this subject and this worked for me:
import browser_cookie3
cookies = browser_cookie3.chrome(domain_name='.tradingview.com')
rows, max_cap = (Query()
.select('name', 'close', 'volume','market_cap_basic')
.where(
Column('market_cap_basic') > 1_000_000_000, # cap > 1B
)
.order_by('market_cap_basic', ascending=False)
.limit(10)
.get_scanner_data(cookies=cookies))
print(rows,max_cap)

Hi! I can see about 15-minute delay too.
So without a paid TV subscription, there is no way to get non-delayed data from this screener?
Do you have only a TV plan or an additional US market data package too?

No, you have to pay to get realtime data. You need both trandingview plan and data pacakge.

No, you have to pay to get realtime data. You need both trandingview plan and data pacakge.

I just checked again, we don't need a paid subscription, realtime quotes are available on TV website with a simple user login (without paid sub), but when I sign out - quotes become 15 minutes delayed on the website. As for the Python screener, your solution above didn't help me to get realtime data with browser_cookie3... don't know why...
@shner-elmo maybe you can please take a look into that?

@Stail7 I'm not sure on which stocks you get real-time data for free, but you might want to have a look at this.
https://www.tradingview.com/data-coverage/
Now, if you notice that the data on the Screener is different from your browser, its because you need to sign in before you perform the request to the API, you do that by passing the cookies.
You can use the same cookies you are currently using in your browser with the browser_cookie3 library (thanks to Darwin for sharing this).
Try this:
from tradingview_screener import Query, Column
import browser_cookie3

# type the name of your browser instead of 'chrome'
cookies = browser_cookie3.chrome(domain_name='.tradingview.com')

query = Query().select(
    'update_mode',
    'update_mode|1',
    'update_mode|5',
    'update_mode|15',
    'update_mode|30',
    'update_mode|60',
    'update_mode|120',
    'update_mode|240',
    'update_mode|1W',
    'update_mode|1M',
)

Without passing the cookies:
query.get_scanner_data()

(17774,
           ticker  ...         update_mode|1M
 0    NASDAQ:NVDA  ...  delayed_streaming_900
 1       AMEX:SPY  ...  delayed_streaming_900
 2    NASDAQ:AAPL  ...  delayed_streaming_900
 3    NASDAQ:TSLA  ...  delayed_streaming_900
 4     NASDAQ:QQQ  ...  delayed_streaming_900
 5    NASDAQ:AMZN  ...  delayed_streaming_900
 6     NYSE:BRK.A  ...  delayed_streaming_900
 7     NASDAQ:AMD  ...  delayed_streaming_900
 8    NASDAQ:MSFT  ...  delayed_streaming_900
 9    NASDAQ:META  ...  delayed_streaming_900
 10      AMEX:IWM  ...  delayed_streaming_900

And with the cookies:
query.get_scanner_data(cookies=cookies)

(17773,
           ticker update_mode  ... update_mode|1W update_mode|1M
 0    NASDAQ:NVDA   streaming  ...      streaming      streaming
 1       AMEX:SPY   streaming  ...      streaming      streaming
 2    NASDAQ:AAPL   streaming  ...      streaming      streaming
 3    NASDAQ:TSLA   streaming  ...      streaming      streaming
 4     NASDAQ:QQQ   streaming  ...      streaming      streaming
 5    NASDAQ:AMZN   streaming  ...      streaming      streaming
 6     NYSE:BRK.A   streaming  ...      streaming      streaming
 7     NASDAQ:AMD   streaming  ...      streaming      streaming
 8    NASDAQ:MSFT   streaming  ...      streaming      streaming
 9    NASDAQ:META   streaming  ...      streaming      streaming
 10      AMEX:IWM   streaming  ...      streaming      streaming

As you can see, we have successfully signed-in, and we are getting streaming data.
Let me know if this worked for you.

@shner-elmo Thanks a lot for the detailed explanation! On a free TV subscription API data is delayed in both cases (with and without cookies). But the website screener page shows real-time data when I signed in with a free sub. Website data is delayed only if I sign out completely. It seems like an API response is different from what we can see on the website, which is a shame...

delayed in both cases (with and without cookies). But the website screener page shows real-time data when I signed in with a free account.

So something is wrong with your cookies.
By passing the cookies you are logging in, and you should get the same exact data as in the browser (when logged in).

It seems like an API response is different from what we can see on the website

Wrong, the website performs the same exact API request as the TV screener (to the same endpoint, with the same headers and cookies)

Or the free account cookies sent through API don't let me be signed in

Yeah, it's gotta be this.

@Stail7 Can you please show me the output of the query I wrote above (with passing your cookies)?
Also, print the cookies and make sure its not empty, like this (don't share them tho):
<CookieJar[]>

Nice! I'm glad you got it working.
On a side note, maybe you are using Chromium instead of Chrome? If so try the chromium function.

On a side note, maybe you are using Chromium instead of Chrome? If so try the chromium function.

No, Chrome, I tried chromium function - didn’t work for me, firefox did. Thank you again and have a great weekend!

So I guess we have found a solution so I will close the issue.
The library will always allow users to pass their cookies and headers if they choose so, for cases like this.
However, it would be nice to document it, by adding some examples of how to check if your data is streaming, and how to log in by passing your cookies...
(As a side note, I noticed that TradingView's browser cookies last almost a year, before you need to log in again. So this is a very reliable method.)


Add contact email to advisers

Also:

Changes the label for email to be username. Discussed renaming the model field as well with @jim68000 but leant towards not for now (also there would be migration impact)
Sets the default Faker locale to en_GB

Codecov Report

Merging #495 into develop will increase coverage by <.01%.
The diff coverage is 100%.

@@             Coverage Diff             @@
##           develop     #495      +/-   ##
===========================================
+ Coverage    96.48%   96.49%   +<.01%
===========================================
  Files          115      115
  Lines         3646     3647       +1
  Branches       335      335
===========================================
+ Hits          3518     3519       +1
  Misses          87       87
  Partials        41       41

Impacted Files
Coverage Δ

datahub/company/admin.py
88.88% <ø> (ø)
:arrow_up:

datahub/company/models/adviser.py
84.74% <100%> (+0.26%)
:arrow_up:

datahub/search/company/serializers.py
98.94% <0%> (ø)
:arrow_up:

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Read>Format>Write on one swipe.

Is it possible to on one swipe read card > check if one of techTypes is android.nfc.tech.NdefFormatable and if is, format card > and then write card?
Is it possible both on Android and IOS?

@Damian333 Yes, It should be possible, but we will have to implement this for different NfcTechs.
For the most used NfcA (Mifare) tags, we have already implemented in this project, you can search for NfcProxy.js which has an eraseNfcA function does this.
Thanks!


Error occured while using the lib for server side rendering

I`m using React server side rendering features and ES6.
Using ES6 importing style like
import draggable from 'draggable';
has issue with document object:
/node_modules/draggable/src/draggable.js:43
var style = document.body.style;
^
ReferenceError: document is not defined.

The issue related with attemption to refer to the document object, which is absent on server side.
It can be solved by using require('draggable') importing style in componentDidMount section (used only onclient side).
Maybe it will be good to inform the lib users to avoid ES6 import style or make some additional environment checks.

This is a browser library. To run it on the server you will need jsdom or another DOM shim.


⚠ Community has degraded performance

In 0b79978, Community (https://community.wrk.com/health) experienced degraded performance:

HTTP code: 200
Response time: 210 ms

Resolved: Community performance has improved in a68c772.


Added options to README

I had to dig a little to find the team option and was thankful to find it built in. I just wanted to make others aware of it as well.
Nice work on this.

Thanks, @iwasrobbed!


Absolute positioning of dropdown can cause problems

I integrated choices in our application and had a problem with the internal structure of this library:
The ".choices" div is relative positioned, but the ".choices__list--dropdown" child-div has a absolute position.
There are several places in our app where the box is inside a relative positioned container. The dropdown cannot be displayed outside of the container-div then, so it is partially hidden.
The "workaround" is to make the ".choices" div also absolute and set its position manually. But that's not really nice and has several edge cases...
Is it possible to change this structure in a future-release?

Have you tried setting, via CSS, "overflow: visible" to the container that you use? That should let your dropdowns flow outside of it
Example, first half without overflow: visible on the container (a modal in this case), the second half the same modal and same dropdown but with overflow: visible set.

Thanks for the tip, it worked. Changing the overflow of the containers fixed all our issues with the dropdown!

Unfortunately that does not work if a further-up parent is setting overflow:hidden.
In our solution the combo is in a form that has div that must clip its children if "collapsed". Therefore I cannot remove the overflow:hidden on the form parent (3 parents of the select box).
Other libraries solve this by having the dropdown div as a child of "body" and position it manually.
I might have to do this in case there is no easier workaround

If you have collapsed functionality you could set overflow hidden when collapsed and overflow visible when not collapsed? I assume you use some JS to trigger collapsing?

That would work for the collapsing group but not for the "card" the collapsible group is in. Which is in another DIV representing a group of cards (divs) that again are overflow:hidden.
The only way is to use "fixed" and position the dropdown "somewhere". For Phones I am thinking about moving the dropdown to the bottom of the screen anyway, but for Desktop browsers should the dropdown be close to the field.


Core Texture Added

Temp texture added, but needs a more finalized one.

Model used as opposed to texture.


Update plugin-bevigil-ci.yml

Description
https://github.com/jenkinsci/bevigil-ci-plugin
Pull Request to eanble CD for this plugin: https://github.com/jenkinsci/bevigil-ci-plugin/pull/1

Submitter checklist for adding or changing permissions

Always

[x] Add link to plugin/component Git repository in description above

When enabling automated releases (cd: true)

[x] Add a link to the pull request, which enables continous delivery for your plugin or component.
Follow the documentation to ensure, your pull request is set up properly.

When adding new uploaders (this includes newly created permissions files)

[ ] Make sure to @mention an existing maintainer to confirm the permissions request, if applicable
[ ] Use the Jenkins community (LDAP) account name in the YAML file, not the GitHub account name
[ ] Make sure to @mention the users being added so their GitHub account names are known if they require GitHub merge access (see below).
[ ] All newly added users have logged in to Artifactory and Jira at least once

Reviewer checklist (not for requesters!)

[ ] Check this if newly added person also needs to be given merge permission to the GitHub repo (please @ the people/person with their GitHub username in this issue as well). If needed, it can be done using an IRC Bot command
[ ] Check that the $pluginId Developers team has Admin permissions while granting the access.
[ ] In the case of plugin adoption, ensure that the Jenkins Jira default assignee is either removed or changed to the new maintainer.
[ ] If security contacts are changed (this includes add/remove), ping the security officer (currently @Wadeck) in this pull request. If an email contact is changed, wait for approval from the security officer.

There are IRC Bot commands for it

Hey, please add a link to your PR enabling CD.
Thanks!

@NotMyFault Added Please check

@NotMyFault Updated with the PR link.


Update g_stands_for.md on v1.39.x branch

I mistakenly left this out of #26596

python basic tests: https://github.com/grpc/grpc/issues/26611
interop c2p: https://github.com/grpc/grpc/issues/26595


fix/tests on windows

build: enable win32 build/testing
test: ensure consistency between spec printing across platforms

this has been fixed in #1460


add support for mongodbatlas provider

Allows to get resources related to MongoDBAtlas

projects works without any issues. However I am having issues with team and cluster,
$ terraform --version
Terraform v1.1.1
on darwin_amd64
+ provider registry.terraform.io/mongodb/mongodbatlas v1.1.1

$ ./terraformer import mongodbatlas --resources=cluster --verbose
2022-01-06T16:53:38.481-0500 [INFO]  plugin: configuring client automatic mTLS
2022-01-06T16:53:38.491-0500 [DEBUG] plugin: starting plugin: path=.terraform/providers/registry.terraform.io/mongodb/mongodbatlas/1.1.1/darwin_amd64/terraform-provider-mongodbatlas_v1.1.1 args=[".terraform/providers/registry.terraform.io/mongodb/mongodbatlas/1.1.1/darwin_amd64/terraform-provider-mongodbatlas_v1.1.1"]
2022-01-06T16:53:38.495-0500 [DEBUG] plugin: plugin started: path=.terraform/providers/registry.terraform.io/mongodb/mongodbatlas/1.1.1/darwin_amd64/terraform-provider-mongodbatlas_v1.1.1 pid=56084
2022-01-06T16:53:38.495-0500 [DEBUG] plugin: waiting for RPC address: path=.terraform/providers/registry.terraform.io/mongodb/mongodbatlas/1.1.1/darwin_amd64/terraform-provider-mongodbatlas_v1.1.1
2022-01-06T16:53:38.512-0500 [INFO]  plugin.terraform-provider-mongodbatlas_v1.1.1: configuring server automatic mTLS: timestamp=2022-01-06T16:53:38.511-0500
2022-01-06T16:53:38.547-0500 [DEBUG] plugin: using plugin: version=5
2022-01-06T16:53:38.547-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: plugin address: address=/var/folders/cq/lz76_n1n4wgg_xzzd3c9szb1kygwws/T/plugin625889451 network=unix timestamp=2022-01-06T16:53:38.547-0500
2022-01-06T16:53:38.577-0500 [TRACE] plugin.stdio: waiting for stdio data
2022/01/06 16:53:38 mongodbatlas importing... cluster
2022/01/06 16:53:39 mongodbatlas done importing cluster
2022/01/06 16:53:39 Number of resources for service cluster: 9
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_Dev
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_Staging
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_ecommerce-dev
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_customerlayer-production
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_ecommerce-staging
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_app-1
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_Cluster0
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_customerlayer-staging
2022/01/06 16:53:39 Refreshing state... mongodbatlas_cluster.tfer--XXXXXXX_ecommerce-production
2022-01-06T16:53:39.470-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: panic: runtime error: index out of range [1] with length 1
2022-01-06T16:53:39.470-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1:
2022-01-06T16:53:39.470-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: goroutine 84 [running]:
2022-01-06T16:53:39.470-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/mongodb/terraform-provider-mongodbatlas/mongodbatlas.decodeStateID(0xc000848030, 0x2a, 0x0)
2022-01-06T16:53:39.470-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/mongodb/terraform-provider-mongodbatlas/mongodbatlas/provider.go:226 +0x23f
2022-01-06T16:53:39.470-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/mongodb/terraform-provider-mongodbatlas/mongodbatlas.resourceMongoDBAtlasClusterRead(0x1fbd248, 0xc000822000, 0xc00084e100, 0x1c45700, 0xc00074cda0, 0xc00064a480, 0xc0006c9908, 0x100df38)
2022-01-06T16:53:39.470-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/mongodb/terraform-provider-mongodbatlas/mongodbatlas/resource_mongodbatlas_cluster.go:572 +0xb7
2022-01-06T16:53:39.471-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*Resource).read(0xc0001780e0, 0x1fbd248, 0xc000822000, 0xc00084e100, 0x1c45700, 0xc00074cda0, 0x0, 0x0, 0x0)
2022-01-06T16:53:39.471-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-sdk/v2@v2.8.0/helper/schema/resource.go:342 +0xa7
2022-01-06T16:53:39.471-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*Resource).RefreshWithoutUpgrade(0xc0001780e0, 0x1fbd248, 0xc000822000, 0xc00082ad00, 0x1c45700, 0xc00074cda0, 0x0, 0x0, 0xc00081fa70, 0x0)
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-sdk/v2@v2.8.0/helper/schema/resource.go:624 +0x1cb
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*GRPCProviderServer).ReadResource(0xc000204870, 0x1fbd248, 0xc000822000, 0xc000822040, 0xc000822000, 0x100b665, 0x1d15c40)
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-sdk/v2@v2.8.0/helper/schema/grpc_provider.go:576 +0x47d
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-go/tfprotov5/tf5server.(*server).ReadResource(0xc000614bc0, 0x1fbd2f0, 0xc000822000, 0xc00081c060, 0xc000614bc0, 0xc0006b8ba0, 0x106cb67)
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-go@v0.4.0/tfprotov5/tf5server/server.go:298 +0x105
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-go/tfprotov5/internal/tfplugin5._Provider_ReadResource_Handler(0x1d56880, 0xc000614bc0, 0x1fbd2f0, 0xc00081e000, 0xc00081c000, 0x0, 0x1fbd2f0, 0xc00081e000, 0xc00081a000, 0x3c0)
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-go@v0.4.0/tfprotov5/internal/tfplugin5/tfplugin5_grpc.pb.go:344 +0x214
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: google.golang.org/grpc.(*Server).processUnaryRPC(0xc000229880, 0x1fc8538, 0xc000579b00, 0xc000646360, 0xc00068c510, 0x259f810, 0x0, 0x0, 0x0)
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	google.golang.org/grpc@v1.38.0/server.go:1286 +0x52b
2022-01-06T16:53:39.473-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: google.golang.org/grpc.(*Server).handleStream(0xc000229880, 0x1fc8538, 0xc000579b00, 0xc000646360, 0x0)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	google.golang.org/grpc@v1.38.0/server.go:1609 +0xd0c
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: google.golang.org/grpc.(*Server).serveStreams.func1.2(0xc00020a2c0, 0xc000229880, 0x1fc8538, 0xc000579b00, 0xc000646360)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	google.golang.org/grpc@v1.38.0/server.go:934 +0xab
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: created by google.golang.org/grpc.(*Server).serveStreams.func1
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	google.golang.org/grpc@v1.38.0/server.go:932 +0x1fd
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: panic: runtime error: index out of range [1] with length 1
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1:
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: goroutine 85 [running]:
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/mongodb/terraform-provider-mongodbatlas/mongodbatlas.decodeStateID(0xc0007bc040, 0x31, 0x0)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/mongodb/terraform-provider-mongodbatlas/mongodbatlas/provider.go:226 +0x23f
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/mongodb/terraform-provider-mongodbatlas/mongodbatlas.resourceMongoDBAtlasClusterRead(0x1fbd248, 0xc0007d4080, 0xc0007cc100, 0x1c45700, 0xc00074cda0, 0xc00064a600, 0xc0001d3908, 0x100df38)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/mongodb/terraform-provider-mongodbatlas/mongodbatlas/resource_mongodbatlas_cluster.go:572 +0xb7
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*Resource).read(0xc0001780e0, 0x1fbd248, 0xc0007d4080, 0xc0007cc100, 0x1c45700, 0xc00074cda0, 0x0, 0x0, 0x0)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-sdk/v2@v2.8.0/helper/schema/resource.go:342 +0xa7
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*Resource).RefreshWithoutUpgrade(0xc0001780e0, 0x1fbd248, 0xc0007d4080, 0xc000740d00, 0x1c45700, 0xc00074cda0, 0x0, 0x0, 0xc000725a40, 0x0)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-sdk/v2@v2.8.0/helper/schema/resource.go:624 +0x1cb
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*GRPCProviderServer).ReadResource(0xc000204870, 0x1fbd248, 0xc0007d4080, 0xc0007d40c0, 0xc0007d4080, 0x100b665, 0x1d15c40)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-sdk/v2@v2.8.0/helper/schema/grpc_provider.go:576 +0x47d
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-go/tfprotov5/tf5server.(*server).ReadResource(0xc000614bc0, 0x1fbd2f0, 0xc0007d4080, 0xc00063a3c0, 0xc000614bc0, 0xc00063c7b0, 0xc0004dbba0)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-go@v0.4.0/tfprotov5/tf5server/server.go:298 +0x105
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: github.com/hashicorp/terraform-plugin-go/tfprotov5/internal/tfplugin5._Provider_ReadResource_Handler(0x1d56880, 0xc000614bc0, 0x1fbd2f0, 0xc00063c7b0, 0xc00063a360, 0x0, 0x1fbd2f0, 0xc00063c7b0, 0xc00064f400, 0x3c7)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	github.com/hashicorp/terraform-plugin-go@v0.4.0/tfprotov5/internal/tfplugin5/tfplugin5_grpc.pb.go:344 +0x214
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: google.golang.org/grpc.(*Server).processUnaryRPC(0xc000229880, 0x1fc8538, 0xc000579b00, 0xc000646480, 0xc00068c510, 0x259f810, 0x0, 0x0, 0x0)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	google.golang.org/grpc@v1.38.0/server.go:1286 +0x52b
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: google.golang.org/grpc.(*Server).handleStream(0xc000229880, 0x1fc8538, 0xc000579b00, 0xc000646480, 0x0)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	google.golang.org/grpc@v1.38.0/server.go:1609 +0xd0c
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: google.golang.org/grpc.(*Server).serveStreams.func1.2(0xc00020a2c0, 0xc000229880, 0x1fc8538, 0xc000579b00, 0xc000646480)
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	google.golang.org/grpc@v1.38.0/server.go:934 +0xab
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: created by google.golang.org/grpc.(*Server).serveStreams.func1
2022-01-06T16:53:39.474-0500 [DEBUG] plugin.terraform-provider-mongodbatlas_v1.1.1: 	google.golang.org/grpc@v1.38.0/server.go:932 +0x1fd
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022-01-06T16:53:39.476-0500 [DEBUG] plugin.stdio: received EOF, stopping recv loop: err="rpc error: code = Unavailable desc = transport is closing"
2022-01-06T16:53:39.476-0500 [DEBUG] plugin: plugin process exited: path=.terraform/providers/registry.terraform.io/mongodb/mongodbatlas/1.1.1/darwin_amd64/terraform-provider-mongodbatlas_v1.1.1 pid=56084 error="exit status 2"
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Unavailable desc = transport is closing
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:39 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:39 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 WARN: Fail read resource from provider, wait 300ms before retry
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 Fail read resource from provider, trying import command
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 rpc error: code = Canceled desc = context canceled
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_Dev
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_Staging
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_ecommerce-dev
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_customerlayer-production
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_ecommerce-production
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_app-staging
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_Cluster0
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_customerlayer-app-1
2022/01/06 16:53:40 ERROR: Unable to refresh resource mongodbatlas_cluster.tfer--XXXXXXX_ecommerce-staging
2022/01/06 16:53:40 Filtered number of resources for service cluster: 0
2022/01/06 16:53:40 mongodbatlas Connecting....
2022/01/06 16:53:40 mongodbatlas save cluster
2022/01/06 16:53:40 mongodbatlas save tfstate for cluster
2022-01-06T16:53:40.988-0500 [DEBUG] plugin: plugin exited

@sergeylanzman any idea if this is an issue with my code or is it a bug on the mongodbatlas provider?


[Runtime] Class MoveTo in x6/geometry causes Line.isLine type guard to throw

Describe the bug
Type guards Line.isLine and Curve.isCurve (and possibly others) throw exceptions when checking against MoveTo.
Your Example Website or App
https://codesandbox.io/s/x6-moveto-illegal-access-u8cyp?file=/src/App.tsx
Steps to Reproduce the Bug or Issue

Create a new MoveTo() object and call Line.isLine on it.

Expected behavior
As a developer, I would not expect runtime type checking functions to throw exceptions. They should only ever return true or false; if an exception occurs during type checking (say missing attributes etc.) then most likely the object we are checking isn't the expected type, in which case it should return false.
Screenshots or Videos
No response
Platform

OS: macOS 11.4
Browser: Chrome 96.0.4664.110
Version: 1.29.0

Additional context
This happens because the MoveTo class has a getter MoveTo.start that unconditionally throws:
https://github.com/antvis/X6/blob/2ec187c00f74b3d0c70538c288ae329fcb86bab1/packages/x6/src/geometry/path/moveto.ts#L28-L31
And then type guards like Line.isLine will try to access this .start property when checking:
https://github.com/antvis/X6/blob/2ec187c00f74b3d0c70538c288ae329fcb86bab1/packages/x6/src/geometry/line.ts#L536
I don't know in what other situation will this happen yet but it is crashing examples/x6-example-features when I visit /edge/tools.

/cib


An unauthenticated user should not be able to delete an image.

If the user is not logged in and viewing a popular image, there should be no action menu to delete the image.

Also, the "back" button should not say Repositories but should say "Popular Images"

This might be a general problem because of the upgrading of Clarity. We'll fix it.
@wknet123
Please take a loot at this issue.

@wknet123
Add same permission control like other components such as 'projects','repositories' etc.
(listMode)

Fixed

Does copy ID and copy parent ID make sense for the unauthenticated user @akshayl @steven-zou

@lweitzman
The two ID are just read-only information. Checked with @wknet123, in the old version, these two IDs are exposed to unauthenticated users.


set showToDamagerOnly to false, all the armor stands will become server-side?

I thought this plugin was using packets, so it would be client-side only. But if I set showToDamagerOnly to false, it becomes server-side, and there’s a high chance the armor stands won’t despawn. Now my server has a ton of armor stands that won’t despawn, and I have to use the /kill command to clear them.

Hello,
Thanks for the comment !, to better understand your problem I need to know which version of the plugin you are currently using, you can find out with the /spectraldamage command.
Sincerely

And the minecraft version of the server
Yes, when damage indicators are visible to all other players on the server, the hologram becomes server side for performance issues. There are plans to add a new configuration for this in the next update and change the way holograms are spawned.

And the minecraft version of the server

Plugin is 2.6.6, server is 1.20.2 and 1.21, both server have same issue.

Yes, when damage indicators are visible to all other players on the server, the hologram becomes server side for performance issues. There are plans to add a new configuration for this in the next update and change the way holograms are spawned.

You just claim it’s only packets and client-side on your plugin page without mentioning this anywhere.

Hello,
I carried out several tests on versions 1.21.1 of paper and spigot, I noticed no problem with the latest version 2.6.6 of the plugin, the holograms worked well. To resolve your problem, however, I need more information, what version of Minecraft you are on, spigot, paper, snapshot, ... You specified version 1.21 which is currently entirely replaced by version 1.21. 1 I therefore advise you to update it. The despawn of holograms may be due to your Minecraft instance or other external plugins. I therefore advise you to remove the plugins one by one to test.
Furthermore, I did not specify that the hologram visible to all players was not client-side, because the primary goal of sending packets to a single client is that only one player can see the modification in game (what the plugin does by default), so if we have to make a hologram appear to all the players in a certain radius and therefore send a packet to each player we are doing exactly the work of Minecraft and consequently we are reinventing the wheel since that is exactly what the game does by default . But as I specified before, i planned to add a configuration to make the holograms completely client side in order to use the falling animation with them.
Sincerely

Would it be possible to have video/image extracts to be able to see if it's a hologram that disappears / if the text disappears too, etc, please ?

When the armor stand is still there and the chunk gets unloaded or the server shuts down (or maybe more reason idk), the armor stand gets stuck forever. But that’s not the main point, I just want it to stay client-side even if showToDamagerOnly is set to false.


ArchLinux cant push models ! atleast on keras

Describe the bug
push_to_hub_keras(model,"stufuf333")
and the error I get
Traceback (most recent call last):
File "/run/aistuff/ai_thing2.py", line 215, in
push_to_hub_keras(model,"sneedger")
File "/home/ori/.local/lib/python3.10/site-packages/huggingface_hub/keras_mixin.py", line 373, in push_to_hub_keras
repo = Repository(
File "/home/ori/.local/lib/python3.10/site-packages/huggingface_hub/repository.py", line 504, in init
raise ValueError(
ValueError: If not specifying clone_from, you need to pass Repository a valid git clone.
git lfs has issues??
Reproduction
No response
Logs
No response
System Info
Archlinux
python 3.10

Hi there! Thanks for reporting!
Do you have a reproducible example? I just tried this in a Colab and it worked well https://colab.research.google.com/drive/1D46OEKDmvMwAieCVcShO1kKdqZsF4JeE?usp=sharing

(cc @merveenoyan )

Hey @sneedgers, thanks for opening an issue! As @osanseviero was mentioning, we'll need a reproducible code example in order to help you out. Please provide the version of your tools, especially the version of huggingface_hub as this is what's important. Thanks.

Hi there! Thanks for reporting!
Do you have a reproducible example? I just tried this in a Colab and it worked well https://colab.research.google.com/drive/1D46OEKDmvMwAieCVcShO1kKdqZsF4JeE?usp=sharing

dev version from github.

hey @sneedgers, can you please post the code snippet you used to push your model so we can test and see what doesn't work?

@sneedgers Hello there! Can you please put a code snippet here for us to reproduce your problem?

Push a model. Read again my issue

@sneedgers sorry if we didn't solve your issue here but we are really missing a part. Did you try the colab from @osanseviero's comment https://github.com/huggingface/huggingface_hub/issues/968#issuecomment-1207747180 ? If the colab is also working for you then we would need more context (e.g. a real code snippet) to see what could cause the error.
In general it's good to isolate the problem in a short example if you don't want to share your full code.
Otherwise, I will just close this issue as unresolved.


transferring data from stm32 nucleo to nodemcu

I am trying to send data using rx tx pins from stm32 board to nodemcu, but no data is received on nodemcu. But if try the same for arduino and nodemcu the data is being easily transferred. So there any library to support connection between the two boards (stm32 and nodemcu esp8266). Please help. I tried opening stm32duino forum but it is unaccessible.

Hi @gauri8427,
currently the forum is down, we do our best to get one up and running but this could take some time.
This repository is for BoardManager issue.
Please open a new one in the STM32 core repo and provide all relevant info without those info, we will not be able to help you as only safid:

rx tx pins from stm32 board to nodemcu

would not help.


Working with upgrade adapter

Hello, I'm trying to work with the upgrade adapter and the package and I'm getting the following error:
 Invalid provider - only instances of Provider and Type are allowed, got: [object Object]

Right after adding this line:
upgradeAdapter.addProvider(ANGULAR2_GOOGLE_MAPS_PROVIDERS);

Any ideas ?

I Debuged the angular 2 code and I found this:

Hi @gotenxds,
I need to see your code to be able to give you a useful answer. can you share it on plunker?

Closing this due to inactivity. Feel free to reopen if you can provide reproducable steps


doesnt work today (21.05.2023) v.13.10

doesnt work

Not related to the project. Make sure you have all the dependencies, frameworks, etc.


add a demo page

hi, I am interested in checking out this project, but the readme didn't have any links to any demo pages. This discouraged me from checking it out.
Just thought I'd mention it, incase the maintainers would like to add a demo app to the readme so people can check it out without running it locally.

@kamikaz1k There is a link to the django-classified-demo project:
https://github.com/slyapustin/django-classified-demo
Hope this helps.


Balance level goals based on playtesting

Some level goals such as "No Smoking Section 2" are extremely challenging. If no players can get an SSS rank, we should lower the target scores. If veteran players are struggling to even clear the level, we should make it shorter or easier.
Reach out to the community to find sore points in the levels; levels which are universally disliked or seen as too difficult.

SSS grading criteria have been decreased across the board, with a few levels such as "No Smoking Section 2" having their difficulties decreased or sharp decreases in grading criteria.


ROW_INDEX_V1 encoder should consider the secondary index size with the encoded data size tracking

Added code for resetting size values in encoding context.

Approved by Ram and Anoop


Resources SDK version 2020-10

Regenerated from the updated swagger to support TemplateLink.queryString property
Merged swagger PR - https://github.com/Azure/azure-rest-api-specs/pull/11637

Please ensure this checklist is complete: https://github.com/Azure/adx-documentation-pr/blob/master/engineering/adx_netsdk_process.md#appendix-a-pr-review-checklist

Please ensure this checklist is complete: https://github.com/Azure/adx-documentation-pr/blob/master/engineering/adx_netsdk_process.md#appendix-a-pr-review-checklist

Will push a commit in a bit

Can this PR be reviewed please.

/azp run

@Xynoclafe can you please pull master in your fork?

@Xynoclafe can you please pull master in your fork?

Done.


Merge Sort

Merge sort is a divide-and-conquer algorithm that sorts an array (or list) by recursively breaking the array down into smaller sub-arrays, sorting those sub-arrays, and then merging the sorted sub-arrays back together to form the final, sorted array.
Here is the basic approach of merge sort algorithm:
1-Divide the array into two equal-sized subarrays.
2-Recursively sort each subarray.
3-Merge the two sorted subarrays back into the original array in sorted order.
I will do it in C++ Please assign it to me.

Merge sort is a divide-and-conquer algorithm that sorts an array (or list) by recursively breaking it down into smaller sub-arrays, sorting them, and then merging the sorted sub-arrays back together to form the final, sorted array.
The basic approach of the merge sort algorithm is as follows:

Separate the array into two equal-sized subarrays.
2-Sort each subarray recursively.
3-In sorted order, merge the two sorted subarrays back into the original array.

I'll write it in Python. Please delegate it to me.

Sorry this algorithm has been implemented


Shanmugapriya N-Rajasekhar Talasila (Guest)rpa challenge code review and update

Hi Priya,
I have created RPA challenge process and pushed to remote repository. You can able to check that once Vajrang approved pull  request


Moderation: Don't require hash for edits that don't change the download

Currently you need to manually copy-paste the previous hash for edits like adding a screenshot, changing the description, etc., even if the download itself and thus the hash of the zipball do not change.

I think I can make a -5+7 fix for this, hehe


chore(contributing.md): update contributing.md instructions

Removed deprecated instructions on documentation section:

Currently npm run build does not generate a /site in project directory.
http://localhost:3000/ does not run.

Added the following:

Instructions for Windows users. For those that had issues with esLint giving all errors, this might help.
Provided a link to jsDoc for future doc contributors.

Thank you!


on jobs screen, refresh incomplete jobs every X seconds

do ajax call on anything in NEW or RUN status - select where id in (1, 2, 3...) - so page can auto-refresh these rows as they finish
also, look for newly created records - select where id > [max id on page] - don't just dump these to the page, since this will move things and maybe mess up clicks - instead, make the refresh button blink or show a message next to it or something like that

incomplete jobs updating. still need to check for new jobs


Fix markup links

A lot of the links weren't working properly (old repository name and other stuff). It's better to just use relative linking inside the same page. Any changes in branch names / repository names will not break the mark down links.

Seems to be a duplicate of PR https://github.com/Magisk-Modules-Repo/MagiskHidePropsConf/pull/133
:upside_down_face:

@Didgeridoohan :)


Update column and row selection tests

Update all tests covering the column and row selection features.

Looks good!  Thanks for the PR!


OpenGarage - correctly handle offline status (#12612)

Description:
Fixes problem described in the issue
Related issue (if applicable): fixes #12612
Pull request in home-assistant.github.io with documentation (if applicable): home-assistant/home-assistant.github.io#<home-assistant.github.io PR number goes here>
Example entry for configuration.yaml (if applicable):

Checklist:

[ ] The code change is tested and works locally.

If user exposed functionality or configuration variables are added/changed:

[ ] Documentation added/updated in home-assistant.github.io

If the code communicates with devices, web services, or third-party tools:

[ ] Local tests with tox run successfully. Your PR cannot be merged unless tests pass
[ ] New dependencies have been added to the REQUIREMENTS variable (example).
[ ] New dependencies are only imported inside functions that use them (example).
[ ] New dependencies have been added to requirements_all.txt by running script/gen_requirements_all.py.
[ ] New files were added to .coveragerc.

If the code does not interact with devices:

[ ] Local tests with tox run successfully. Your PR cannot be merged unless tests pass
[ ] Tests have been added to verify that the new code works.

Thanks! 🎉


Addition to CVE Exploits (CVE-2019-5029)

Addition of exploit for the config editor of the Exhibitor Web UI versions 1.0.9 to 1.7.1 (CVE-2019-5029).

Please add Hacktoberfest label if accepted 🚀

Was there a problem with this pull request? Looking at your CONTRIBUTING.md file, this was in-line with all contribution guidelines apart from the example IP address not being <IP_ADDRESS>. Please let me know I can improve for future contributions.
"PayloadsAllTheThings' Team ❤ pull requests :) Feel free to improve with your payloads and techniques !"

The CVE scripts will be removed in the near future.
Metasploit and Nuclei are best suited to handle these exploits.


[1.21] Small QoL and improvements

Mostly a few things that I noticed when playing the mod that make it a bit frustrating due to that.

Otherwood lacks the logs_that_burn tag, which allows it to be used on the charcoal crafting recipe.
OtherStone lacks the c:stones tag
Rename Otherworld Wood to Otherworld Log
(I feel that renaming it to Log would fall in line with the naming consistency. So if you are searching for logs, you would be able to see all logs.)
Allow for Shift-clicking on the Crusher menu to transfer items to and from the inventory.
(I have a habit of shift-clicking to pull and add items to inventories, like the furnace, so when I try to shift-click the ores to the crusher, is frustrating that it fails)
Change the Crusher inventory access method.
(The "Shift-Click with empty hand" method is kind of frustrating, Villagers let you access their UI with a simple click, and some interactions that require to Shift click to access the UI let you do it so with items in hand. The empty hand is the main problem since I keep my hot bar full, so needing to open my menu to free a slot adds up with time. Also, this interferes with mods that use the same interaction mechanic, like Carry On.)
Make the Binding book crafting consistent with the item texture
Add a "Wondering Demonic Trader"
(This is more something that came to mind that could expand the use of the 3rd Eye effect. Whenever a wondering trader spawns, there is a small chance it's actually a Demonic trader.
Stack Cooking on the demonic partner.

(Currently, the Divination Rod only purpose is to search for Iesenium ore. Mostly because the other 3 functions are for searching for the Groves in the overworld, but that feels pointless since you can get the wood and stone material way faster by using the spirit fire. So I think it would expand the usefulness of the rod by letting you Attune to ores and ancient debris and allow you to use it as a compass. and having it require you to find the block before you can attune to it makes it balance in my opinion)

Item 3 done in #1201


DSERV-155 Ontology adaptor improvements

The old ontology schemas need to be dropped? Other than that it looks good

Just talked to Ben, we can remove the old ontology collections and schemas. We are dropping the type field, so we are ready to merge.


nco: Patch hardcoded paths cp and mv

Motivation for this change
Commit b83ed3efe81525302469a3052982f41393a616e0 in the nco source
repo, hard-coded the paths to cp and mv, so as to point to their FHS
locations, which resulted in ncrename throwing a "file not found"
error when invoked outside of an FHS sandbox.
Things done
This nixpkgs commit patches the src/nco_fl_utl.c to instead point the
associated nixpkgs.coreutils locations. The hard-coded paths actually
occur in a number of other locations, but this is enough to quash the
error w/ ncrename (and presumably the other CLI nco tooling, although
this isn't tested).

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

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

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

Result of nixpkgs-review pr 87038 1

1 package built:
- nco


test: behaviors-message_on_lock_failure (2024-02-19 00:08:42.292435+00:00)

automatic test cleanup