O7s Timeline desynced after 4.3 update

See title, happened to the other 4 people in my raid group using cactbot as well. Seems like it didn't sync up at the divergent points, and just played the default timeline with no syncs in it.

I just cleared O7S and experienced the same issue. Dadaluma first program but timeline continued with Biblios. When Airforce program was happening timeline was at Ultros.

I think specifically the Timeline couldn't complete the "guess" for the first airforce/squid and just bork completely afterwards.

Earlier today in the FFLogs Discord Ravahn was made aware of this.

Interesting.  Yes - 00:2aae is combat log text.  the lack of 1A: line for this is a problem.
The missing Actor name on 1A lines (where "from  " doesnt have the name)  is a complex issue, but is technically by design.  This will happen if the plugin cannot find the combatant name of the source of the buff/debuff.  There probably isnt anything I can do about this without introducing an additional explicit delay into the buff tracking code in the network parser, which I would prefer not to do, since it would delay triggers.(edited)
regarding the missing 1A line, the only way I'm going to be able to track this down is if someone can reproduce it with the 'dump full network data' option turned on.  I'll see if I can get someone to run O7S with it on and get me a nice big logfile out of it.

Just wanted to say that I had the same issue as well. Is it something that could potentially be fixed ? Ravahn statement doesn't appear to be sure if it's fixable.

Also confirming, the timeline listed the correct order, however the call was incorrect - e.g. Airforce in timeline, but Ultros in the text popup. Very confusing.

08s is desynched as well

What do you mean by o8s being desynced? (Do you have video?) I think o7s here is weird because it's using 1A "gains the effect" lines to sync up.  o8s only uses ability usage ids, so I'm not sure I understand what's going wrong there.

Didn't see any issue in o8s tonight. Only had the o7s desync from buffs being missed due to the 00:2aae issue linked above.

Had no problems with 08s either.

I'm experiencing the same issue in O7S, sometimes it syncs right, but the other mechs are
inverted.

I wonder if it's something that can be fixed or should we try and learn 07s by heart seeing the reason why it happens a bit higher in the thread.

It could be fixed by changing the triggers to match 00 lines and not the 1A lines, but in general the 1A lines show up before the 00:2aee lines and I've seen the 00 lines get dropped and not parsed.  So, I'm not keen on using them if I don't have to.
So, the answer is yes, this could be fixed, but I'm going to give ravahn a chance to fix this in the ffxiv plugin first before changing a ton of triggers.  Sorry for this being broken in the meantime.

Ah nice to know it could be fixed. I REALLY appreciate the work you'Ve put in this, I know nothing of coding and this tool has me immensely useful. Hopefully I did not come as being entitled too much or anything. Thanks for the answer :)

If you want a temp fix try adding this to your user/raidboss.js
Options.Triggers = [ { 	zoneRegex: /Sigmascape V3\.0 \(Savage\)/, 	timeline:
50 "--sync--" sync /00:2aae:The Guardian gains the effect of Dadaluma Simulation/ jump 1050
510 "--sync--" sync /00:2aae:The Guardian gains the effect of Bibliotaph/ jump 2510       # Bibliotaph buff, jump to A1
510 "--sync--" sync /00:2aae:The Guardian gains the effect of Dadaluma/ jump 3510         # Dadaluma buff, jump to A2
1482 "--sync--" sync /00:2aae:The Guardian gains the effect of Bibliotaph/ jump 4482       # Bibliotaph buff, jump to B1
1482 "--sync--" sync /00:2aae:The Guardian gains the effect of Dadaluma/ jump 5482         # Dadaluma buff, jump to B2
`,
triggers: [
      {
  regex: / 00:2aae:The Guardian gains the effect of Dadaluma Simulation/,
  condition: function(data, matches) { return !data.first || data.seenVirus && !data.second },
  run: function(data) {
    if (data.seenVirus)
      data.second = 'dada';
    else
      data.first = 'dada';
  },
},
{
  regex: / 00:2aae:The Guardian gains the effect of Bibliotaph Simulation/,
  condition: function(data, matches) { return !data.first || data.seenVirus && !data.second },
  run: function(data) {
    if (data.seenVirus)
      data.second = 'biblio';
    else
      data.first = 'biblio';
  },
},
{
  regex: / 00:2aae:The Guardian gains the effect of Virus/,
  run: function(data) {
    data.seenVirus = true;
  },
},
],

},
]`

Seems like it was fixed with the ravahn's plugin's <IP_ADDRESS> update. I just did o7s last night and everything worked as it did before.

#126 Is now broken in a different way, since while the 1A: line is back, the Doom duration itself is inaccurate (9999 second)

This seems like it is fixed now.  I'll close this issue and leave the doom one open until that is fixed.
@Jolkien You didn't come off that way at all.  Just wanted to apologize for wanting to wait on ravahn and leaving things broken.  ravahn is awesome and came through super quickly, so I think that was the correct decision.  :)


Migrations not generated for hs_tracking and hs_access_control in RC 1.10.0

When deploying release-candidate-1.10.0 there are 2 missing migrations as denoted below:
Migrations for 'hs_tracking':
  0005_auto_20170502_1706.py:
    - Alter field value on variable
Migrations for 'hs_access_control':
  0021_auto_20170502_1706.py:
    - Alter field auto_approve on groupaccess

hs_tracking/migrations/0005_auto_20170502_1706.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals

from django.db import migrations, models

class Migration(migrations.Migration):

    dependencies = [
        ('hs_tracking', '0004_auto_20161010_1402'),
    ]

    operations = [
        migrations.AlterField(
            model_name='variable',
            name='value',
            field=models.TextField(),
        ),
    ]

hs_access_control/migrations/0021_auto_20170502_1706.py
# -*- coding: utf-8 -*-
from __future__ import unicode_literals

from django.db import migrations, models

class Migration(migrations.Migration):

    dependencies = [
        ('hs_access_control', '0020_merge'),
    ]

    operations = [
        migrations.AlterField(
            model_name='groupaccess',
            name='auto_approve',
            field=models.BooleanField(default=False, help_text=b'whether group membership can be auto approved', editable=False),
        ),
    ]

These have been applied to beta.
Operations to perform:
  Synchronize unmigrated apps: test_without_migrations, inplaceeditform, accounts, rest_framework, grappelli_safe, corsheaders, boot, jquery_ui, haystack, crispy_forms, postgres, hs_metrics, staticfiles, filebrowser_safe, sitemaps, gis, hs_sitemap, mobile, autocomplete_light, debug_toolbar, widget_tweaks, irods_browser_app, django_nose, heartbeat
  Apply all migrations: redirects, theme, galleries, hs_geo_raster_resource, ref_ts, hs_geographic_feature_resource, conf, hs_labels, forms, generic, hs_model_program, sites, blog, contenttypes, hs_tools_resource, hs_access_control, hs_app_netCDF, hs_app_timeseries, hs_modelinstance, core, hs_composite_resource, django_comments, sessions, hs_swat_modelinstance, robots, auth, hs_script_resource, pages, hs_collection_resource, oauth2_provider, hs_modflow_modelinstance, hs_tracking, admin, hs_core, security, django_irods, hs_file_types
Synchronizing apps without migrations:
  Creating tables...
    Running deferred SQL...
  Installing custom SQL...
Running migrations:
  Rendering model states... DONE
  Applying hs_access_control.0021_auto_20170502_1706... OK
  Applying hs_tracking.0005_auto_20170502_1706... OK

@mjstealey
This is the original migration file I generated which is in master:
https://github.com/hydroshare/hydroshare/blob/master/hs_access_control/migrations/0017_groupaccess_auto_approve.py
The same in develop:
https://github.com/hydroshare/hydroshare/blob/develop/hs_access_control/migrations/0017_groupaccess_auto_approve.py

@pkdash - it's possible that another migration 0018, 0019 or 0020 undid that work... The new migration depends on a migration file named  0020_merge.

@mjstealey @alvacouch What should we do for this? Should we regenerate these migration files because Django wants to regenerate and commit the migrations files as a hotfix to release candidate?

I regenerated them and committed them just now. They've been working fine in testing in that configuration.


Update yaml files to add key parameter

Files are missing newlines at the end but otherwise this looks good. Were you able to test with cloudformation?

Do they need newlines at the end? Don't see that previously.
And how did you test using cloudformation in the past?

Tested both YAML templates in demo aws account and both successfully created correct stack


ccmlib/common: support scylla dev mode

Signed-off-by: Benny Halevy<EMAIL_ADDRESS>

It looks like the code could use a loop over ['debug', 'dev', 'release'], but the logic looks good to me.

@bhalevy please reopen for next branch

Sorry, opened #133


Docs say to use stream.controller.abort() but controller is a private property

Confirm this is a Node library issue and not an underlying OpenAI API issue

[X] This is an issue with the Node library

Describe the bug
Docs say to use stream.controller.abort() but controller is a private property of Stream.
Docs:
If you need to cancel a stream, you can break from the loop or call stream.controller.abort().

Library code:

To Reproduce

Install the node library.
Create a stream with the library. (import { Stream } from 'openai/streaming';)
Call stream.controller.abort()

You will see an IDE error telling you that controller is a private property. This is also reflected in both the interface and the implementation shown in the screenshots.
Code snippets
No response
OS
macOS
Node version
v20.1.0
Library version
openai v4.2.0

Thanks for the bug report, the controller property will be made public in the next release!


Fine-tune code on 1b Model

hi @kazemnejad
What a wonderful idea and insight!
NOW I want to search more work after you, first I want to fine-tune your nope model. But I can only see the inference code in the readme. Could you please tell me how to fine-tune on your model?

Thanks for reaching out.
These are standard Huggingface models, which can be plugged into finetuning pipeline right away.
https://huggingface.co/docs/trl/sft_trainer

Thanks for your kind reply. That helps a lot.
Also I want to ask one more question, could you show me your pertaining dataset? Because I don't want to make distribution shift, so maybe the same source data for fine-tune is the best way.
Thank you again for your help.


Include method get checked items

This pull request includes a new method that return all checked items
This method was created to perform the search of the items that are checked, neglecting the main item.
Senary:
I am mounting a treeview to select the menus that will be displayed for each registered profile, if a "submenu" item is selected the main menu will automatically be displayed.
For this reason I have identified the need to create this feature to fetch the selected items.

We already have a getCheckedNodes method that is doing the same thing. Could you use our method. Thanks for the contribution.


.indexOn: .value

Hey @pkaminski
I dont think its possible right now when using fireplan
https://www.firebase.com/docs/security/guide/indexing-data.html#section-indexing-order-by-value

My bad just had to add the indexed key word
wondering if the other index type are supported as well
https://www.firebase.com/docs/security/guide/indexing-data.html

Yes, the indexed keyword should automatically resolve to the correct type
of index.  Please let me know if you find that it doesn't...
On Wed, Jul 15, 2015 at 2:08 PM, PG Herveou<EMAIL_ADDRESS>wrote:

My bad just had to add the indexed key word
wondering if the other index type are supported as well
https://www.firebase.com/docs/security/guide/indexing-data.html
—
Reply to this email directly or view it on GitHub
https://github.com/pkaminski/fireplan/issues/4#issuecomment-121748015.

--
Piotr Kaminski<EMAIL_ADDRESS>"That bun is dirty.  Don't eat that bun."


How use the project without ORM?

If I don't need the ORM how I can use the project without all the DB setup, seeds and migrations?

Excluding typeorm loader in app.ts should be enough. After that you can delete all files you don‘t need.


[FLINK-32660][table] Introduce external FS compatible FileCatalogStore implementation

What is the purpose of the change
Introduces a file catalog store implementation that supports external file systems.
Brief change log

Use org.apache.flink.core.fs.Path instead of standard Java local FS file utils.
Use FSDataOutputStream and FSDataInputStream to read/write the catalog store file.
Validate the given catalog store file exists in FileCatalogStore#open(), as automatic directory creation may fail on external file systems. (Permission problems or unsupported API)

Verifying this change
This change is already covered by existing tests, such as:

FileCatalogStoreTest
FileCatalogStoreFactoryTest

Will add a test case with an external FS.
Does this pull request potentially affect one of the following parts:

Dependencies (does it add or upgrade a dependency): no
The public API, i.e., is any changed class annotated with @Public(Evolving): no
The serializers: no
The runtime per-record code paths (performance sensitive): no
Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn, ZooKeeper: no
The S3 file system connector: no

Documentation

Does this pull request introduce a new feature? no

Thanks @ferenc-csaky , left some comments

@FangYongs thanks for the review, replied to your comments and updated the code as well.

Thanks @ferenc-csaky for updating this PR, it LGTM overall, please fix the failed ci


fix: Move platform scripts

Description
Move platform scripts out of the pipeline folder.
This is the easiest solution to avoid triggering all module pipelines in case changes are made to scripts only used by platform pipelines.
The alternative would be to explicitly exclude platform folder from triggers in all module workflows

@eriqua - can we add this to the loop for the next discussion?

Coverting this to draft until a decision/conflict is made... @eriqua @AlexanderSehr

@eriqua - Will we be picking this up again soon?

Closing in favor of #1294


Quick fix to scroll issue

some refactoring was merged last week that adds more lazy loading. as a result, links that scroll to a particular element using refs (rather than hashLinks) aren't scrolling to the right places. this is a quick fix for the alerts signup link. adding a trello ticket to address the bug as a whole
using git bisect--this looks like the PR where the scroll bug originated

 Lots of links don't scroll to right location.


The New Footer

Expected Behavior

https://www.figma.com/file/EvyDheixD72iX8qNfnuPl6/Website-4.0?node-id=0%3A1
Current Behavior
The Current Footer

Updated with Vanessa's asks


fix: Ensure the permission request is only asked once

Hi everyone,
It looked like my fix was not enough.
When the popup shows to ask for the permission, we leave the Flutter app.
In that case, the PermissionListener (ValueNotifier) was disposed.
That's why this listener is now on top of the app.
Furthermore, to prevent an initial test for nothing, we only check if the permission was requested when a listener is added = when the scan page is visible

@g123k For the record, there's a new breaking change for permission_handler: ^10.0.0 (was ^9.2.0)

We can easily migrate, as the change is related to the notifications (= we don't use them)
BREAKING CHANGE: Updated Android compileSdkVersion to 33 to handle the new POST_NOTIFICATIONS permission.
When updating to version 10.0.0 make sure to update the android/app/build.gradle file and set the compileSdkVersion to 33.

@g123k Then feel free to migrate if relevant.


Use of nonlocal scope keyword breaks Python2.7 compatibility.

Python3 introduced the nonlocal scope to allow for accessing variables outside of the default scope. This has proved very helpful in writing closures which the decorator can be thought as one big closure.
Unfortunately as the nonlocal keyword is not understood by Python2.7 this will result in import errors, requiring us to refactor the code to account for the limitations of Python2.7 scoping.
For now, this library will be only supported using Python3.6. If Python2.7 is required please write your use case here and I will put effort into updating the library to fix the scoping issues.

Python 2.7 will be deprecated soon. Closing this issue out.


allow two docs one about addons one about Kodi itself

Related to doxygen changes and the now available:

https://xbmc.github.io/docs.kodi.tv/master/kodi-base
https://xbmc.github.io/docs.kodi.tv/master/kodi-dev-kit

Please target the staging branch

Have changed to staging branch.


Atb defaults update script

Python script used to update the defaults using the file at https://github.com/NREL/SAM-documentation/tree/master/Defaults References and Tools/Fall 2022
Given our decision making on defaults (PV benchmark for PV, ATB on others) there will be some further modifications to the scripts throughout the process.
Defaults work in progress.

2. I'm having trouble matching up values I see in SAM with the script output and ATB spreadsheet. The utility costs seem to match, but the residential don't. Not sure if I'm looking in the right places:

The issue there is that the version of the CSV in this PR includes "incl. supply chain premium" which causes the script to skip the value. I fixed that in the csv in https://github.com/NREL/SAM/pull/1248
I'll get the other changes pushed here.


feat: optimize process registry updates

Motivation
Optimise process registry updates by replacing List.replace_at() with a combination of Stream + Enum.
Closes #466

This doesn't solve the problem. See this change for an example.
Currently, we are getting the validator indices, and then updating some other collection individually for each index. What we should do, is zip the collections we use (in this case only validators, so no zip), and then use Stream.map to transform them. That way we go through the list only once, instead of length(validators) times.

This doesn't solve the problem. See this change for an example.
Currently, we are getting the validator indices, and then updating some other collection individually for each index. What we should do, is zip the collections we use (in this case only validators, so no zip), and then use Stream.map to transform them. That way we go through the list only once, instead of length(validators) times.

Even now, we are traversing the validator_list only once, isn't it? The Stream operations (Stream.with_index() and Stream.map()) are lazy and only get applied when you actually enumerate over the list with Enum.to_list()? please correct me if I'm wrong.

That stream is later turned into a list. The Stream vs Enum difference isn't too important in this case. Here's another example.
The thing is, in process_registry_updates we have an Enum.reduce with a List.replace inside. Both need to iterate the validator set (or a subset), so the complexity ends up being $O(n^2)$. What we want, is to transform the Enum.reduce(List.replace()) into a single Enum.map (or something similar). With that, we are reducing the complexity to $O(n)$.
I suggest you check where's the bottleneck (maybe it's not directly in process_registry_updates but in activation_eligibility_and_ejections), and if your optimizations work, by adding prints like IO.inspect("[#{DateTime.utc_now()}] process_registry_updates") and running the test on #475.

hey @h3lio5 , what's the status of this task?


missing output result and duplicate result

Hi
i've found two bugs on v1.0 app.
1 - there are some duplicate result on output with same port and different pings, for example :
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,109,Ping : 192, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,109,Ping : 245, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,143,Ping : 192, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,143,Ping : 245, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,22,Ping : 192, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,22,Ping : 245, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,443,Ping : 192, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,443,Ping : 245, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,80,Ping : 192, Response :<PHONE_NUMBER>ms
SSHAccess 14 us.sshaccess.com United States,<IP_ADDRESS>,80,Ping : 245, Response :<PHONE_NUMBER>ms
2 - when i see live result, i saw this server on success output section but when i click on output it hasn't written on output file.
DynamicSSH 30 ca1.ssh.ipdyna.com Canada,<IP_ADDRESS>,guest,pswrd,22:80:109:143:442:443,444
Thanks

Hi @titancomputer, that's true, I will be fixing bugs and release new file. Thank you for bug reporting

Hey @titancomputer, I published new release.
Check this on :
https://github.com/omidmohajers/ssh-tester/releases/tag/v1.0.1


fix: disable Xdebug for composer command, fixes #4219

The Issue

#4219

How This PR Solves The Issue
Adds XDEBUG_MODE=off for ddev composer.
os.Setenv("XDEBUG_MODE", "off") is not working here, because ddev composer runs inside docker-compose exec.
Manual Testing Instructions

ddev start
ddev xdebug
ddev composer -V - should not show Xdebug output.

Automated Testing Overview

Related Issue Link(s)
Release/Deployment Notes

Rebased

Related: https://github.com/composer/xdebug-handler


Lightweight Redis client

#982

@atkawa7,
Thanks for having already signed the Contribution License Agreement. Your agreement was validated by Microsoft. We will now review your pull request.
Thanks,
Microsoft Pull Request Bot

Looks great, thanks for the PR!


Acceleration structure example

Template
If you dont understand something just leave it.
If you can provide more detailed information than the template allows for, please ignore the template and present all of your findings.

Version of vulkano: a1dca4261d421fc6008498b6fbc6f27f5de6a2a0
OS: TODO
GPU (the selected PhysicalDevice): TODO
GPU Driver: TODO
Upload of a reasonably minimal complete main.rs file that demonstrates the issue: TODO

Issue
Is there any acceleration structure example? I cannot find the way to build AS.
To build AS, commonly vkGetAccelerationStructureBuildSizesKHR() is called first with VkAccelerationStructureBuildGeometryInfoKHR.dstAccelerationStructure=scratchData=empty to acquire the size requirements for AS.
	// Get the size requirements for buffers involved in the acceleration structure build process
	VkAccelerationStructureBuildGeometryInfoKHR acceleration_structure_build_geometry_info{};
	acceleration_structure_build_geometry_info.sType         = VK_STRUCTURE_TYPE_ACCELERATION_STRUCTURE_BUILD_GEOMETRY_INFO_KHR;
	acceleration_structure_build_geometry_info.type          = VK_ACCELERATION_STRUCTURE_TYPE_BOTTOM_LEVEL_KHR;
	acceleration_structure_build_geometry_info.flags         = VK_BUILD_ACCELERATION_STRUCTURE_PREFER_FAST_TRACE_BIT_KHR;
	acceleration_structure_build_geometry_info.geometryCount = 1;
	acceleration_structure_build_geometry_info.pGeometries   = &acceleration_structure_geometry;

	const uint32_t primitive_count = 1;

	VkAccelerationStructureBuildSizesInfoKHR acceleration_structure_build_sizes_info{};
	acceleration_structure_build_sizes_info.sType = VK_STRUCTURE_TYPE_ACCELERATION_STRUCTURE_BUILD_SIZES_INFO_KHR;
	vkGetAccelerationStructureBuildSizesKHR(
	    device->get_handle(),
	    VK_ACCELERATION_STRUCTURE_BUILD_TYPE_DEVICE_KHR,
	    &acceleration_structure_build_geometry_info,
	    &primitive_count,
	    &acceleration_structure_build_sizes_info);

But current vulkano implementation requires AccelerationStructureBuildGeometryInfo.dst_acceleration_structure and .scratch_data not to be empty. So I think it's almost impossible to create AS without creating AS.
    let build_info = AccelerationStructureBuildGeometryInfo {
        flags: BuildAccelerationStructureFlags::PREFER_FAST_TRACE,
        mode: BuildAccelerationStructureMode::Build,
        ..AccelerationStructureBuildGeometryInfo::new(
            dst_acceleration_structure,
            geometries,
            scratch_data,
        )
    };

    let size = device.acceleration_structure_build_sizes(
        AccelerationStructureBuildType::HostOrDevice,
        &build_info,
        &[1],
    ).unwrap();

#2213

I've made a PR to fix the issue, but I think it demonstrates that I really don't know much about how acceleration structures are used in practice. Would you be willing to write an example for Vulkano?


FileListing should check if host cluster is running

Disable the download buttons if it is not running

Also disable the view button

closed in #400


Feat/137/general feedback fixed

Issue
https://github.com/SAP/guided-answers-extension/issues/137
Description
Allows users to enter general feedback about a Guided Answer.

Checklist for Pull Requests

[ ] Supplied as many details as possible on this change
[ ] Included the link to the associated issue in the Issue section above
[ ] The code conforms to the general development guidelines.
[ ] The code has unit tests where applicable and is easily unit-testable
[ ] This branch is appropriately named for the associated issue

@unseen1980, can you please check the 2 code smells: https://sonarcloud.io/project/issues?id=SAP_guided-answers-extension&pullRequest=302&resolved=false&types=CODE_SMELL

Done!

Thank you all !


Test DeepTTC

Status: Failed
Command: singularity exec --bind ${TEST_DIR}:/candle_data_dir build/DeepTTC.sif train.sh 4 /candle_data_dir
Depends on:

https://github.com/JDACS4C-IMPROVE/DeepTTC/issues/6
https://github.com/JDACS4C-IMPROVE/DeepTTC/issues/7

Output:
PRAD              818
MB                546
CLL               272
ACC               137
Name: count, dtype: int64
Traceback (most recent call last):
  File "/usr/local/DeepTTC/deepttc_baseline_pytorch.py", line 279, in <module>
    main()
  File "/usr/local/DeepTTC/deepttc_baseline_pytorch.py", line 271, in main
    run(args)
  File "/usr/local/DeepTTC/deepttc_baseline_pytorch.py", line 247, in run
    train_drug, test_drug, train_rna, test_rna = loader.load_data()
  File "/usr/local/DeepTTC/deepttc_baseline_pytorch.py", line 133, in load_data
    train_drug, test_drug, train_rna, test_rna = self._process_data(self.args)
  File "/usr/local/DeepTTC/deepttc_baseline_pytorch.py", line 188, in _process_data
    train_drug, test_drug = obj.Getdata.ByCancer(random_seed=args.rng_seed)
  File "/usr/local/DeepTTC/Step1_getData.py", line 213, in ByCancer
    train_data, test_data = self._split(df=drug_cell_df, col=self.cancer_id,
  File "/usr/local/DeepTTC/Step1_getData.py", line 175, in _split
    train_data = train_data.append(sub_train)
  File "/opt/conda/lib/python3.10/site-packages/pandas/core/generic.py", line 5989, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'DataFrame' object has no attribute 'append'. Did you mean: '_append'?

Command: IMPROVE_RESULT val_loss:        1.7727327054408248
Output:
Validation at Epoch 2 with loss:1.60653, MSE: 1.86214 , Pearson Correlation: 0.87763 with p-value: 0.0 Spearman Correlation: 0.83264 with p_value: 0.0 , Concordance Index: 0.82473
{'val_loss': 1.8621445139104555, 'rmse': 1.3646041601543122, 'pcc': 0.8776368581577472, 'scc': 0.8326412524002879, 'r2': 0.7668459324633321, 'best_epoch': 1}
Training at Epoch 3 iteration 0 with loss 1.86644. Total time 0.02583 hours
Currenf MSE: 1.7727327054408248
Validation at Epoch 3 with loss:1.71383, MSE: 1.77273 , Pearson Correlation: 0.88492 with p-value: 0.0 Spearman Correlation: 0.84164 with p_value: 0.0 , Concordance Index: 0.82975
{'val_loss': 1.7727327054408248, 'rmse': 1.3314400870639373, 'pcc': 0.8849223686446626, 'scc': 0.8416452175582434, 'r2': 0.7780409426651591, 'best_epoch': 2}

IMPROVE_RESULT val_loss:        1.7727327054408248

Status: OK

Missing commits - develop is failing

Modified definition file, new version in switch-to-improve-branch
Created improve branch in DeepTTC
Switched build branch in definition file
Build and tested image:

singularity run --nv --bind `pwd`/tmp:/candle_data_dir build/DeepTTC.sif train.sh 3 /candle_data_dir --epochs 1
....
Checkpoint save interval == 0 -> checkpoints are disabled.
Training at Epoch 1 iteration 0 with loss 14.3121. Total time 0.00055 hours
Currenf MSE: 2.1630810230494517
Validation at Epoch 1 with loss:1.75420, MSE: 2.16308 , Pearson Correlation: 0.85460 with p-value: 0.0 Spearman Correlation: 0.80406 with p_value: 0.0 , Concordance Index: 0.80849
{'val_loss': 2.1630810230494517, 'rmse': 1.4707416574808274, 'pcc': 0.8546015608904385, 'scc': 0.8040606021397423, 'r2': 0.7291664877951529, 'best_epoch': 0}

IMPROVE_RESULT val_loss:        2.1630810230494517


Github Copilot likes this

This popped up in my github copilot 🤣

What part of the code popped up, out of curiosity?

What part of the code popped up, out of curiosity?

Python - request.get


Apostrophe converting to '

How can we reproduce this bug?
My index.html partial contains this code:
      <columns small="12">
Don't miss out!

What did you expect to happen?
The text renders fine in browser tests, and using Litmus it looks fine in all clients except Outlook.
What happened instead?
However, the apostrophe in "Don't" is converted to '.
See this snippet from the dist folder:

Don't miss out!

That leads to this result in Outlook:

What email clients does this happen in?
Outlook 2007, 2013

Thanks for the report Looks like a duplicate issue. We'll close this in favor of https://github.com/zurb/foundation-emails/issues/281


Wrong height of window in FancyZones - reintroduced error!

Microsoft PowerToys version
0.64.1
Installation method
Chocolatey
Running as admin
Yes
Area(s) with issue?
FancyZones
Steps to reproduce
I have a zone which is defined as the full height from the top of the taskbar to the top of the screen.
When I drop a window in the zone, the window gets the full height of the screen, so part of the window is behind the taskbar.
This has been a problem before...
✔ Expected Behavior
When I drop a window in a zone, then window should have the height of the zone not the height of the screen!
❌ Actual Behavior
No response
Other Software
No response

Thank you for reporting. This problem is known, you can track it in the mentioned issue.
/dup of https://github.com/microsoft/PowerToys/issues/10903


Game freezing post launch

First of all — thanks for making this. It’s great to be able to play non-steam games with my family from my couch.
I’m trying to load the Outer Worlds using Epic Launcher and it freezes post launch on the Link. The game continues to run on my PC, but the link freezes. This happens about 15-20 seconds after the game opens (and it seems to be running fine for those 15 seconds).
Do you have any idea what could fix this? Happy to provide more information if needed.

When you say "Link" do you mean the Steam overlay or are you talking about input from the controller in-game? If it's the latter problem, you should be able to power off/on the controller and enter/exit the overlay to get input redirected back into the game. If it's the former problem the only workarounds I'm aware of involve using GloSC because it doesn't attach the overlay to the game just the input or a customized Desktop Mode config via BPM.
I don't own The Outer Worlds on EGL (Epic Games Launcher). I'm using GloSC to launch The Outer Worlds via Xbox Game Pass (as a UWP application), but as I understand it the Epic Launcher version has minimal DRM so a simple non-Steam game shortcut should work fine.


AudioPlayerState undefined after upgrading to release 19.0

Upgraded from 0.18.3 to 0.19.0 now: undefined name 'AudioPlayerState.'
Full Description
I hate to ask this, as I know it's me--the only reason I'm asking as I'm guessing other people may need the answer, also.
I see that audioplayers.dart now contains three exports, including audioplayers_api.dart, and THAT has this line:
export 'src/api/player_state.dart';

But yet my project can't find the enum.  As soon as I switch back to 18.3 all is well with the world again.
Code to Reproduce
audioplayers: ^0.19.0               <--- set to this
I did a flutter clean, flutter clean, and even exited Android Studio and re-entered.
Log Errors
error: Undefined name 'AudioPlayerState'. (undefined_identifier at [run_sergeant] lib\main.dart:1498)
error: Undefined class 'AudioPlayerState'. (undefined_class at [run_sergeant] lib\main.dart:1498)
error: Undefined class 'AudioPlayerState'. (undefined_class at [run_sergeant] lib\main.dart:2277)
Files/URLs/Sources
I know you re-organized the project.  I read the notes.
Screenshots
N/A
Platforms
[√] Flutter (Channel stable, 2.0.5, on Microsoft Windows [Version 6.1.7601], locale en-US)
• Flutter version 2.0.5 at E:\src\flutter
• Framework revision adc687823a (5 weeks ago), 2021-04-16 09:40:20 -0700
• Engine revision b09f014e96
• Dart version 2.12.3
[√] Android toolchain - develop for Android devices (Android SDK version 30.0.1)
• Android SDK at C:\Users\pete\AppData\Local\Android\sdk
• Platform android-30, build-tools 30.0.1
• Java binary at: C:\Program Files\Android\Android Studio\jre\bin\java
• Java version OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b01)
• All Android licenses accepted.
[√] Chrome - develop for the web
• Chrome at C:\Program Files (x86)\Google\Chrome\Application\chrome.exe
[√] Android Studio (version 4.1.0)
• Android Studio at C:\Program Files\Android\Android Studio
• Flutter plugin can be installed from:
https://plugins.jetbrains.com/plugin/9212-flutter
• Dart plugin can be installed from:
https://plugins.jetbrains.com/plugin/6351-dart
• Java version OpenJDK Runtime Environment (build 1.8.0_242-release-1644-b01)
[√] Connected device (3 available)
• Mi 9T (mobile) • 844fb80a • android-arm64  • Android 10 (API 29)
• Chrome (web)   • chrome   • web-javascript • Google Chrome 90.0.4430.212
• Edge (web)     • edge     • web-javascript • Microsoft Edge 90.0.818.46
• No issues found!

It's called PlayerState now: https://github.com/luanpotter/audioplayers/blob/master/packages/audioplayers/lib/src/api/player_state.dart

You see!  I thought it was me!  Even though I saw the new file with the new name my mind didn't connect the dots.

It's called PlayerState now: https://github.com/luanpotter/audioplayers/blob/master/packages/audioplayers/lib/src/api/player_state.dart

thanks


Error at prediction time with SpacyTokenizer token_pattern landing on word boundary

Rasa Open Source version
2.8.17
Python version
3.8
What happened?
Given:

A config with  SpacyTokenizer with a token_pattern, SpacyFeaturizer, and at least one non-spacy token based featurizer (CountVectorsFeaturizer, LexicalSyntacticFeaturizer):

language: en
pipeline:
   - name: SpacyNLP
     case_sensitive: false
     model: en_core_web_md
   - name: SpacyTokenizer
     token_pattern: "(\\d+|\\D+)"
   - name: SpacyFeaturizer
   - name: CountVectorsFeaturizer
   - name: DIETClassifier
     epochs: 10
     constrain_similarities: true

Input with multiple digits adjoined to a word e.g.

it's 12euro

At inference time, inputting the example sentence above causes DIETClassifier to complain of mismatched input dimensions (stacktrace below). In the absence of a second featurizer i.e. given only SpacyFeaturizer, this does not happen, implying that the final tokens iterated over by SpacyFeaturizer differs from those iterated over by the non-Spacy featurizer. It could be because SpacyFeaturizer uses the spacy tokens here not necessarily the ones Rasa uses.
The goal is that if the amount and the currency are stuck together without white space like this:
it's 12euro

This would be split into tokens it's, 12, euro.
At inference time, inputting the example sentence above causes DIETClassifier to complain of mismatched input dimensions (stacktrace below). In the absence of a second featurizer i.e. given only SpacyFeaturizer, this does not happen, implying that the final tokens iterated over by SpacyFeaturizer differs from those iterated over by the non-Spacy featurizer. It could be because SpacyFeaturizer uses the spacy tokens here not necessarily the ones Rasa uses.
Command / Request
rasa train nlu
rasa shell nlu
> it's 12euro

Relevant log output
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/nlu/model.py", line 470, in parse
    component.process(message, **self.context)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py", line 988, in process
    out = self._predict(message)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py", line 904, in _predict
    return self.model.run_inference(model_data)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py", line 318, in run_inference
    ] = self._rasa_predict(batch_in)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py", line 280, in _rasa_predict
    outputs = tf_utils.sync_to_numpy_or_python_type(self.predict_step(batch_in))
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/tensorflow/models.py", line 228, in predict_step
    return self.batch_predict(batch_in)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py", line 1707, in batch_predict
    text_transformed, _, _, _, _, attention_weights = self._tf_layers[
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/keras/engine/base_layer.py", line 1037, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/tensorflow/rasa_layers.py", line 992, in call
    seq_sent_features, mask_combined_sequence_sentence = self._tf_layers[
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/keras/engine/base_layer.py", line 1037, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/tensorflow/rasa_layers.py", line 645, in call
    sequence_features_combined = self._combine_sequence_level_features(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/tensorflow/rasa_layers.py", line 570, in _combine_sequence_level_features
    sequence_features_combined = self._tf_layers[f"sparse_dense.{SEQUENCE}"](
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/keras/engine/base_layer.py", line 1037, in __call__
    outputs = call_fn(inputs, *args, **kwargs)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/tensorflow/rasa_layers.py", line 338, in call
    return tf.concat(dense_features, axis=-1)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/util/dispatch.py", line 206, in wrapper
    return target(*args, **kwargs)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/ops/array_ops.py", line 1769, in concat
    return gen_array_ops.concat_v2(values=values, axis=axis, name=name)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1213, in concat_v2
    _ops.raise_from_not_ok_status(e, name)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/framework/ops.py", line 6941, in raise_from_not_ok_status
    six.raise_from(core._status_to_exception(e.code, message), None)
  File "<string>", line 3, in raise_from
tensorflow.python.framework.errors_impl.InvalidArgumentError: ConcatOp : Dimensions of inputs should match: shape[0] = [1,3,128] vs. shape[1] = [1,2,300] [Op:ConcatV2] name: concat

The same symptoms will be seen at training time if the token pattern causes the same situation at that time i.e. more Rasa tokens than spacy tokens.
Given token_pattern: "\\d" and training data including the sentence it's 12 euro, running rasa train shows the following traceback:
Epochs:   0%|                                                                                | 0/10 [00:00<?, ?it/s]Traceback (most recent call last):
  File "/Users/melinda/.pyenv/versions/rasa2/bin/rasa", line 8, in <module>
    sys.exit(main())
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/__main__.py", line 118, in main
    cmdline_arguments.func(cmdline_arguments)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/cli/train.py", line 59, in <lambda>
    train_parser.set_defaults(func=lambda args: run_training(args, can_exit=True))
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/cli/train.py", line 91, in run_training
    training_result = train_all(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/api.py", line 109, in train
    return rasa.utils.common.run_in_loop(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/common.py", line 296, in run_in_loop
    result = loop.run_until_complete(f)
  File "uvloop/loop.pyx", line 1456, in uvloop.loop.Loop.run_until_complete
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/model_training.py", line 103, in train_async
    nlu_model = await handle_domain_if_not_exists(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/model_training.py", line 129, in handle_domain_if_not_exists
    nlu_model_only = await _train_nlu_with_validated_data(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/model_training.py", line 758, in _train_nlu_with_validated_data
    await rasa.nlu.train.train(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/nlu/train.py", line 111, in train
    interpreter = trainer.train(training_data, **kwargs)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/nlu/model.py", line 221, in train
    component.train(working_data, self.config, **context)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/nlu/classifiers/diet_classifier.py", line 880, in train
    self.model.fit(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/rasa/utils/tensorflow/temp_keras_modules.py", line 190, in fit
    tmp_logs = train_function(iterator)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 885, in __call__
    result = self._call(*args, **kwds)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 950, in _call
    return self._stateless_fn(*args, **kwds)
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 3039, in __call__
    return graph_function._call_flat(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 1963, in _call_flat
    return self._build_call_outputs(self._inference_function.call(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 591, in call
    outputs = execute.execute(
  File "/Users/melinda/.pyenv/versions/rasa2/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 59, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InvalidArgumentError:  ConcatOp : Dimensions of inputs should match: shape[0] = [5,9,128] vs. shape[1] = [5,4,300]
         [[node rasa_sequence_layer_text/rasa_feature_combining_layer_text/concatenate_sparse_dense_features_text_sequence/concat (defined at /lib/python3.8/site-packages/rasa/utils/tensorflow/rasa_layers.py:338) ]] [Op:__inference_train_function_8141]

Errors may have originated from an input operation.
Input Source operations connected to node rasa_sequence_layer_text/rasa_feature_combining_layer_text/concatenate_sparse_dense_features_text_sequence/concat:
 IteratorGetNext (defined at /lib/python3.8/site-packages/rasa/utils/tensorflow/temp_keras_modules.py:190)
 rasa_sequence_layer_text/rasa_feature_combining_layer_text/concatenate_sparse_dense_features_text_sequence/dropout/dropout/Mul_1 (defined at /lib/python3.8/site-packages/rasa/utils/tensorflow/rasa_layers.py:308)

Function call stack:
train_function

I have invented a workaround for this.
You have to create custom class which extends the SpacyNLP class, in which you set up the Spacy tokenizer to split the tokens according to your regex. You then use this custom class instead of the SpacyNLP in your config.yml.
Code:
config.yml
language: en
pipeline:
  - name: workaround_spacy_nlp.WorkaroundSpacyNLP
    case_sensitive: false
    model: en_core_web_md
    additional_prefix_regexes: "(\\d+|\\D+)"
  - name: SpacyTokenizer
  - name: SpacyFeaturizer
  - name: CountVectorsFeaturizer
  - name: DIETClassifier
    epochs: 10
    constrain_similarities: true

workaround_spacy_nlp.py (substitue the language for your own or customize according to your needs):
import typing
from typing import Any, Dict, Text

import spacy
from rasa.nlu.utils.spacy_utils import SpacyNLP
from spacy.lang.cs import Czech

if typing.TYPE_CHECKING:
    from spacy.language import Language

PREFIX_REGEXES_ATTRIBUTE = "additional_prefix_regexes"

class WorkaroundSpacyNLP(SpacyNLP):
    """Custom component to add additional prefix regexes for the Spacy tokenizer (to better split some words).
    """

    defaults = {
        **SpacyNLP.defaults,
        # Additional prefix regexes for the Spacy tokenizer. Can be `List[str]` or just one `str`.
        # They will be added to the `Czech.Defaults.prefixes` and passed to (spacy) tokenizer (`nlp.tokenizer`).
        PREFIX_REGEXES_ATTRIBUTE: None,
    }

    def __init__(self, component_config: Dict[Text, Any] = None, nlp: "Language" = None) -> None:
        self._process_prefix_regexes(component_config, nlp)
        super().__init__(component_config, nlp)

    @staticmethod
    def _process_prefix_regexes(component_config: Dict[Text, Any], nlp: "Language"):
        prefix_regexes = component_config.get(PREFIX_REGEXES_ATTRIBUTE)
        if isinstance(prefix_regexes, str):
            prefix_regexes = [prefix_regexes]

        if prefix_regexes:
            prefixes = Czech.Defaults.prefixes + prefix_regexes
            prefix_regex = spacy.util.compile_prefix_regex(prefixes)
            nlp.tokenizer.prefix_search = prefix_regex.search

Thanks for the workaround @ondrej-jelinek-kbc-be !
@joejuzl The root issue here seems to be that SpacyNLP must already know all tokenizer settings in order for its doc (which includes the feature vectors fetched by SpacyFeaturizer) to match the tokens from SpacyTokenizer, which is
what other featurizers will see.
Could we move tokenizer settings to SpacyNLP and have SpacyTokenizer refer to them via it (since its a required component)?


App crashes after clearing the whole values entered for  Check intervals, and Network Response Timeout.

Expected behavior
I expected it not to crash, after users clears their input
Actual behavior
The app crashes after a user clears all the inputted value(s).
How to reproduce

launch Nock Nock
Click on add site
Enter an input for Check Interval, or Network Response Timeout
clear the values entered (Everything)
see it crashing

Note: It doesn't crash if everything isn't cleared. For example; enter 12, clear only 2, the app won't crash. But, it will crash just after clearing the remaining input which is 1.
Screenshot/Gif

Devices
Device: Tecno Camon Xpro
OS: Android
Version 8.1

Are you running an old version of the app? This was fixed a long time ago - unable to reproduce on my end to.

I'm on V0.8.1

Omg!! Latest is 0.8.3


Logging setup on import

eg.
https://github.com/ambiata/atmospherex/blob/master/atmospherex_activity_base/atmospherex_activity_base/__init__.py
https://github.com/ambiata/atmospherex/blob/master/atmospherex_activity_base/atmospherex_activity_base/logger_setup.py
Why did we have it like this? What is the goal?
It was causing me some issues so I temporarily commented it out.

The goal is just to setup the logging. If it causes issue, let's find another way.

@gusmith I'm not sure if this is fixed in the new sdk, can you please verify it is logging as expected now?


[!][thread-0][400 Bad Request] Something went wrong. Exiting thread . .

[!][thread-0][400 Bad Request] Something went wrong. Exiting thread . .

[!][thread-0][400 Bad Request] Something went wrong. Exiting thread . . .


proposal: add Lookup method to reflect.StructTag

I would like to propose the addition of another method to reflect.StructTag. The proposed change is very simple, and I'm happy to produce a design document and a PR. I have filed this issue to see if there is any likelihood of this change being accepted.
The reflect.StructTag currently has one method, Get, which makes it easy to extract the value for the associated key from the tag. What it does not do, however, is indicate if the key exists with an empty value.
So in the following example, the Get method will return the same value for the db tag assocated with the Name field as for the db tag associated with the Address field, but there is a difference in the meaning.
struct {
    Name    string `db:"" json:"-"`
    Address string
}

It could be argued that this is a pretty simple function and should not be added to the Go standard library. I am suggesting that it should be added because any third-party implementation requires some duplication of the code for the Get method in the standard library. Duplicating the code from the Go standard library presents at least two challenges:

There is an ongoing maintenance overhead of tracking any future changes to the Go standard library.
The Go BSD license requires distributing the Go copyright notice and conditions with any redistribution of source code. Not a huge deal, but an inconvenience that can be omitted by adding Lookup to the standard libary.

Note also that there was a similar addition in Go 1.5 in the os package, where the LookupEnv function was introduced to complement the GetEnv function.
Proposed New Method
func (StructTag) Lookup
func (tag StructTag) Lookup(key string) (string, bool)

Lookup returns the value associated with key in the tag string. If the key is present in the tag the value (which may be empty) is returned and the boolean is true. Otherwise the returned value will be empty and the boolean is false. If the tag does not have the conventional format, the value returned by Lookup is unspecified.

Seems reasonable to me.
Assigning @adg to own rounding up the deciders.

Looks fine to me. @rsc?

Russ is busy with other things. I approve this.


Fix loading of styles in Angular Storybook

The angular part in storybook doesn't load the themes styles correctly

Partially added changes on branch: https://github.com/sl-design-system/components/tree/fix/434-fix-styles-in-angular-storybook
There is still a problem with applying styles in only one iframe (we have two iframes, one for storybook with web components and second one for Angular storybook).

This is an issue with storybook itself: https://github.com/storybookjs/storybook/issues/15805
The workaround for now is that you have to refresh the page if you're on an Angular story. After the refresh, the theme is correct.


Permission request: add your userscript to my list

Hi, I'm putting together a list of qutebrowser userscripts here https://github.com/lufte/awesome-qutebrowser-userscripts.git. I'm asking developers of userscripts here on Github to either send me a pull request with the addition of their repo or to simply give me permission to link it myself.
Let me know if you're interested. Thanks.

That's awesome. Also itseems a built-in list of userscripts is on the works for qutebrowser, so making another list doesn't really make sense anyway. Thanks for your time.


rackspace supported?

Hi,
Running terraform gives me 401, bad credentials.
I can login with nova client however.
Is there a specific configuration that I need to add / modify?
(I noticed rackspace uses a non standard authentication mechanism somewhat plugged into the standard openstack auth flow. Is this correct?)

I haven't tested rackspace, but for openstack, you need to copy the terraform/openstack.sample file to  the main directory and modify it for tenant_name, etc.

ok, i will check. I am afraid rackspace != openstack, because:

they have their custom authentication
they have non-cloudstack api too (e.g. docker-machine uses a rackspace driver, but it has an openstack one too)
a lady from their sales told me they only support openstack integrations at their higher pay subscription

So yes, Rackspace does not support standard Openstack.
For that reason Terraform is introducing a Rackspace provider.
That is in work for a month but suspended at the moment.
It might already work and maybe Tuesday I will give it a try.


Add in Middleware support.

Right now we have a custom hook to add additional logging. I think this is fine but I think a more eloquent solution could be to use some sort of Middleware like outlined in this article.
https://link.medium.com/tq6FoquGQdb

We can use the package referenced since we are already using make executable schema.
https://github.com/maticzav/graphql-middleware

@arunsivasankaran I think this would allow us to have automatic light step tracing since there is some middleware for that.

added!


Add server_mounted_mirror to the testsuite server

This parameter is useful to "skip" SCC and instead get the info and
packages from a mirror.
Signed-off-by: Jordi Massaguer Pla<EMAIL_ADDRESS>What does this PR change?
add description

@srbarrios I need this to use minima-mirror as a mirror for SCC. With this, we can mount with nfs minima-mirror.mgr.prv.suse.net/srv/mirror ... and it works very good! This way it is faster and, more importantly, it is stable. I am doing this because I was having timeouts with scc in the deploy phase.

Looks good to me, but better if @rjmateus approve too.


Unable to Connect to Beacon

When trying to run the Change Beacon's Minor Demo, the application is unable to connect to the beacon and fails with the error, "Read Timed Out." I did make sure to update the AppID and AppToken from those in my EstimoteCloud account.

@achusuresh2 Can you drop me an email at wiktor (at) estimote (dot) com so we can look directly with your credentials?

Fixed in 0.6.1.


Bones "Inherit Rotation" property is ignored.

I'm working with a 3d model in Blender wich has some bones with 'Inherit Rotation' disabled.
Exporting to GLTF seems to ignore that property, all bones seems to be exported with 'Inherit Rotation' enabled.
Exporting to FBX works as expected.
Please see attached demo.
bones_test.zip

Is there some option in the exporter that fix this?
Is there a recommendation about the use of this property? Is it better to enable 'Inherit Rotation' in all bones and readjust them to have my animation exported correctly?

GLTF (like Unity and most engines, I think...) does not allow inherited rotation to be disabled the way that Blender does. I suspect that the FBX exporter bakes animation frame by frame to accomplish this, and that if you were to move the joints manually in an engine, rotation would still be inherited.
I'm surprised the "sample animations" option doesn't fix this when exporting to glTF. Not sure why that is, but we can consider this an enhancement, or at least try to figure out what the FBX exporter does.

Closing for now, I think this is likely out of current scope.


Support PyTorch 1.13

offline discussion: latest release like 1.13 should be also tested with pytest in cpu test like pre-test

Moving to https://github.com/pfnet/pytorch-pfn-extras/issues/652


Autocomplete does not render any content (comment as inner content)

Angular version: 5.0.0 angular/material version: 5.2.4
Trying to use Autocomplete.
I've got this form:
<form #updateForm="ngForm">
<mat-form-field >
     <input type="text" matInput [formControl]="studentFormControl" [matAutocomplete]="auto">
          <mat-autocomplete #auto="matAutocomplete">
               <mat-option *ngFor="let student of filteredStudentOptions | async" [value]="student">
                    {{student.FirstName}}
               </mat-option>
           </mat-autocomplete>
      </mat-form-field>
</form>

And I've got this component:
import { FormGroup, FormControl, FormsModule, ReactiveFormsModule } from '@angular/forms';
import { MatInputModule, MatAutocompleteModule, MatFormFieldModule } from '@angular/material';
export class DashboardComponent implements OnInit {
  this.studentFormControl = new FormControl();
    this.filteredStudentOptions = this.studentFormControl.valueChanges.pipe(
      startWith(''),
      map(val => this.filterSelectedStudent(val))
    );
...
}

Although the form shows up, the autocomplete box remains dimensionless with only a comment as it's content. If I place the options outside the autocomplete, they do render and respond to changes in the input, so I know that part is working.
Any ideas what could be happening here? Thanks in advance.

Issue was with z-index of the cdk-overlay-container. Thanks all. Closing.


Embed Uniqueness Issues on 2.12

Issue Summary
Embed uniqueness was not enforced at a db level pre-2.12, so it is possible for https://github.com/wagtail/wagtail/blob/master/wagtail/embeds/migrations/0008_allow_long_urls.py to fail during upgrade. (Additionally, because the uniqueness is enforced on the hash, rather than the url, there seems to be an additional issue with certain url strings that are apparently unique in postgres (a url_count annotation is 1 for both) but equal in Python, but I haven't worked out exactly what the problem is here)
Steps to Reproduce

Start a new project with wagtail start myproject on Wagtail 2.11, making sure the embeds app is added
Enter the django shell
Create two Embeds objects with the same url using Embed.objects.create
Attempt the 2.12 upgrade

Technical details

Python version: 3.6.4
Django version: 2.2.13
Wagtail version: 2.11.3 -> 2.12
Browser version: N/A

A data migration to delete the duplicates would fix this, although it's hard to see how to roll that out without breaking anything, since it has to run before migration 0008, and adding a new migration to the sequence would cause an inconsistent migration history error for people who already applied 0008. Bundling the data migration into migration 0008 could work, but we'll have to make sure that combining a data and schema migration doesn't cause any issues on any databases (see https://stackoverflow.com/questions/60806250/mix-data-and-schema-migrations-in-one-migrations-file-django).

PR: #6815
I forgot that there was an existing data migration as part of this change, so it wasn't as complicated as I'd feared :-) The only proviso is that if someone tried upgrading to 2.12 and encountered the failure on migration 0008, then after upgrading to this fixed version they'll have to roll back migrations to before 0007 to get unstuck...
./manage.py migrate wagtailembeds 0005
./manage.py migrate

Fixed in #6815

I saw this issue yesterday so waited for the fix. I just tried it but it's not working for me.
psycopg2.errors.UndefinedObject: constraint "wagtailembeds_embed_url_max_width_8a2922d8_uniq" of relation "wagtailembeds_embed" does not exist

I was upgrading from 2.11 to 2.12 and saw the error then tried out the above
./manage.py migrate wagtailembeds 0005
./manage.py migrate

As a bit of background we have been moving a site from 2.2.1 in major version steps and all has been fine up to 2.11. When i tried the 2.12 upgrade yesterday I saw the error and found this issue report so stopped at 2.11
From a fresh 2.2.1 database I tried upgrading to 2.11 (in one go) and that all worked OK but when the going to 2.12.1 I see the error again.

@nickmoreton Can you share the full output of ./manage.py migrate, please? In particular, it would be useful to know which migration number is triggering this error.

Sure
Running migrations:
  Applying wagtailembeds.0006_add_embed_hash... OK
  Applying wagtailembeds.0007_populate_hash... OK
  Applying wagtailembeds.0008_allow_long_urls...Traceback (most recent call last):
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
psycopg2.errors.UndefinedObject: constraint "wagtailembeds_embed_url_max_width_8a2922d8_uniq" of relation "wagtailembeds_embed" does not exist

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "app/manage.py", line 10, in <module>
    execute_from_command_line(sys.argv)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/__init__.py", line 381, in execute_from_command_line
    utility.execute()
  File "/usr/local/lib/python3.7/site-packages/django/core/management/__init__.py", line 375, in execute
    self.fetch_command(subcommand).run_from_argv(self.argv)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/base.py", line 323, in run_from_argv
    self.execute(*args, **cmd_options)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/base.py", line 364, in execute
    output = self.handle(*args, **options)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/base.py", line 83, in wrapped
    res = handle_func(*args, **kwargs)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/commands/migrate.py", line 234, in handle
    fake_initial=fake_initial,
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/executor.py", line 117, in migrate
    state = self._migrate_all_forwards(state, plan, full_plan, fake=fake, fake_initial=fake_initial)
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/executor.py", line 147, in _migrate_all_forwards
    state = self.apply_migration(state, migration, fake=fake, fake_initial=fake_initial)
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/executor.py", line 245, in apply_migration
    state = migration.apply(state, schema_editor)
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/migration.py", line 124, in apply
    operation.database_forwards(self.app_label, schema_editor, old_state, project_state)
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/operations/models.py", line 530, in database_forwards
    getattr(new_model._meta, self.option_name, set()),
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/base/schema.py", line 363, in alter_unique_together
    self._delete_composed_index(model, fields, {'unique': True}, self.sql_delete_unique)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/base/schema.py", line 399, in _delete_composed_index
    self.execute(self._delete_constraint_sql(sql, model, constraint_names[0]))
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/base/schema.py", line 137, in execute
    cursor.execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 99, in execute
    return super().execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 67, in execute
    return self._execute_with_wrappers(sql, params, many=False, executor=self._execute)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 76, in _execute_with_wrappers
    return executor(sql, params, many, context)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/utils.py", line 89, in __exit__
    raise dj_exc_value.with_traceback(traceback) from exc_value
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
django.db.utils.ProgrammingError: constraint "wagtailembeds_embed_url_max_width_8a2922d8_uniq" of relation "wagtailembeds_embed" does not exist

Thanks @nickmoreton. That seems odd then... at this point it looks like it's not failing due to the presence of duplicates, but because the old uniqueness constraint - the one we're trying to drop here - doesn't exist.
To clarify - when you say:

From a fresh 2.2.1 database I tried upgrading to 2.11 (in one go) and that all worked OK but when the going to 2.12.1 I see the error again.

you were starting from a database dump where the upgrade to 2.12 had NOT previously been attempted (and rolled back), correct? I'd like to rule out the possibility that the missing database constraint is due to migration 0008 failing after the point where the constraint had been dropped. (That theory doesn't really add up though: migrations ought to happen in a transaction that prevents them from failing in a partially-complete state, and either way, that step happens after the one that we know to be failure-prone.)
If you still have the pre-upgrade 2.2.1 database available, please could you check whether the uniqueness constraint is present there? Run ./manage.py dbshell, and then \d wagtailembeds_embed - the output should end with:
Indexes:
    "wagtailembeds_embed_pkey" PRIMARY KEY, btree (id)
    "wagtailembeds_embed_url_max_width_8a2922d8_uniq" UNIQUE CONSTRAINT, btree (url, max_width)

Thanks @gasman I have setup the repo again at where we started with Wagtail 2.2.1 with the sql dump from postgres that was taken then.
Probably doesn't make any different but there was a migration needs to be run:
wagtail@f30e8dd7f11b:/app/app$ ./manage.py migrate
Operations to perform:
  Apply all migrations: admin, auth, base, blog, contenttypes, general, home, portfolio, sessions, taggit, wagtailadmin, wagtailcore, wagtaildocs, wagtailembeds, wagtailforms, wagtailimages, wagtailmenus, wagtailredirects, wagtailsearch, wagtailusers, work
Running migrations:
  Applying wagtailmenus.0023_remove_use_specific... OK
wagtail@f30e8dd7f11b:/app/app$

This is the result of \d wagtailembeds_embed
pipit=# \d wagtailembeds_embed
                                          Table "public.wagtailembeds_embed"
    Column     |            Type             | Collation | Nullable |                     Default
---------------+-----------------------------+-----------+----------+-------------------------------------------------
 id            | integer                     |           | not null | nextval('wagtailembeds_embed_id_seq'::regclass)
 url           | character varying(200)      |           | not null |
 max_width     | integer                     |           |          |
 type          | character varying(10)       |           | not null |
 html          | text                        |           | not null |
 title         | text                        |           | not null |
 author_name   | text                        |           | not null |
 provider_name | text                        |           | not null |
 thumbnail_url | character varying(200)      |           |          |
 width         | integer                     |           |          |
 height        | integer                     |           |          |
 last_updated  | timestamp without time zone |           | not null |
Indexes:
    "wagtailembeds_embed_pkey" PRIMARY KEY, btree (id)
    "wagtailembeds_embed_url_max_width_8a2922d8_uniq" UNIQUE, btree (url, max_width)

pipit=#

The CONSTRAINT is missing
I'll keep the setup at this point, let me know if you need me to do anything else please.

I expect the UNIQUE vs UNIQUE CONSTRAINT is just a difference between postgresql versions...
Could you try installing Wagtail 2.12.1, then applying the migrations from wagtailembeds one at a time (./manage.py migrate wagtailembeds 0004, ./manage.py migrate wagtailembeds 0005 up to 0008), checking the output of \d wagtailembeds_embed after each one to see if the UNIQUE line is still there?

0004
Indexes:
    "wagtailembeds_embed_pkey" PRIMARY KEY, btree (id)
    "wagtailembeds_embed_url_max_width_8a2922d8_uniq" UNIQUE, btree (url, max_width)

0005
Indexes:
    "wagtailembeds_embed_pkey" PRIMARY KEY, btree (id)
    "wagtailembeds_embed_url_max_width_8a2922d8_uniq" UNIQUE, btree (url, max_width)

0006
Indexes:
    "wagtailembeds_embed_pkey" PRIMARY KEY, btree (id)
    "wagtailembeds_embed_url_max_width_8a2922d8_uniq" UNIQUE, btree (url, max_width)

0007
Indexes:
    "wagtailembeds_embed_pkey" PRIMARY KEY, btree (id)
    "wagtailembeds_embed_url_max_width_8a2922d8_uniq" UNIQUE, btree (url, max_width)

0008 Crashes
Running migrations:
  Applying wagtailembeds.0008_allow_long_urls...Traceback (most recent call last):
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
psycopg2.errors.UndefinedObject: constraint "wagtailembeds_embed_url_max_width_8a2922d8_uniq" of relation "wagtailembeds_embed" does not exist

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "./manage.py", line 10, in <module>
    execute_from_command_line(sys.argv)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/__init__.py", line 381, in execute_from_command_line
    utility.execute()
  File "/usr/local/lib/python3.7/site-packages/django/core/management/__init__.py", line 375, in execute
    self.fetch_command(subcommand).run_from_argv(self.argv)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/base.py", line 323, in run_from_argv
    self.execute(*args, **cmd_options)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/base.py", line 364, in execute
    output = self.handle(*args, **options)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/base.py", line 83, in wrapped
    res = handle_func(*args, **kwargs)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/commands/migrate.py", line 234, in handle
    fake_initial=fake_initial,
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/executor.py", line 117, in migrate
    state = self._migrate_all_forwards(state, plan, full_plan, fake=fake, fake_initial=fake_initial)
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/executor.py", line 147, in _migrate_all_forwards
    state = self.apply_migration(state, migration, fake=fake, fake_initial=fake_initial)
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/executor.py", line 245, in apply_migration
    state = migration.apply(state, schema_editor)
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/migration.py", line 124, in apply
    operation.database_forwards(self.app_label, schema_editor, old_state, project_state)
  File "/usr/local/lib/python3.7/site-packages/django/db/migrations/operations/models.py", line 530, in database_forwards
    getattr(new_model._meta, self.option_name, set()),
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/base/schema.py", line 363, in alter_unique_together
    self._delete_composed_index(model, fields, {'unique': True}, self.sql_delete_unique)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/base/schema.py", line 399, in _delete_composed_index
    self.execute(self._delete_constraint_sql(sql, model, constraint_names[0]))
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/base/schema.py", line 137, in execute
    cursor.execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 99, in execute
    return super().execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 67, in execute
    return self._execute_with_wrappers(sql, params, many=False, executor=self._execute)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 76, in _execute_with_wrappers
    return executor(sql, params, many, context)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/utils.py", line 89, in __exit__
    raise dj_exc_value.with_traceback(traceback) from exc_value
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
django.db.utils.ProgrammingError: constraint "wagtailembeds_embed_url_max_width_8a2922d8_uniq" of relation "wagtailembeds_embed" does not exist

I'm beginning to think the database dump given to me is not correct in some way.
It turns out the data base in use at the moment is Postgres 9.5
Im not suggesting this is the way to fix this but lets see if I can shed some light so to speak.
If I create an empty database and run the 2.11 migrations on it I see the same output as you do @gasman
Indexes:
    "wagtailembeds_embed_pkey" PRIMARY KEY, btree (id)
    "wagtailembeds_embed_url_max_width_8a2922d8_uniq" UNIQUE CONSTRAINT, btree (url, max_width)

I'm going to try a dumpdata from working database at 2.11 and loaddata...
It failed with
wagtail@ea65b08269cd:/app/app$ ./manage.py loaddata data.json
/usr/local/lib/python3.7/site-packages/django/db/models/fields/__init__.py:1421: RuntimeWarning: DateTimeField Embed.last_updated received a naive datetime (2018-09-02 15:37:06.843000) while time zone support is active.
  RuntimeWarning)
/usr/local/lib/python3.7/site-packages/django/db/models/fields/__init__.py:1421: RuntimeWarning: DateTimeField Embed.last_updated received a naive datetime (2018-09-03 10:04:56.957000) while time zone support is active.
  RuntimeWarning)
Traceback (most recent call last):
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
psycopg2.errors.UniqueViolation: duplicate key value violates unique constraint "wagtailembeds_embed_hash_c9bd8c9a_uniq"
DETAIL:  Key (hash)=() already exists.

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "./manage.py", line 10, in <module>
    execute_from_command_line(sys.argv)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/__init__.py", line 381, in execute_from_command_line
    utility.execute()
  File "/usr/local/lib/python3.7/site-packages/django/core/management/__init__.py", line 375, in execute
    self.fetch_command(subcommand).run_from_argv(self.argv)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/base.py", line 323, in run_from_argv
    self.execute(*args, **cmd_options)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/base.py", line 364, in execute
    output = self.handle(*args, **options)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/commands/loaddata.py", line 72, in handle
    self.loaddata(fixture_labels)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/commands/loaddata.py", line 114, in loaddata
    self.load_label(fixture_label)
  File "/usr/local/lib/python3.7/site-packages/django/core/management/commands/loaddata.py", line 181, in load_label
    obj.save(using=self.using)
  File "/usr/local/lib/python3.7/site-packages/django/core/serializers/base.py", line 223, in save
    models.Model.save_base(self.object, using=using, raw=True, **kwargs)
  File "/usr/local/lib/python3.7/site-packages/django/db/models/base.py", line 779, in save_base
    force_update, using, update_fields,
  File "/usr/local/lib/python3.7/site-packages/django/db/models/base.py", line 870, in _save_table
    result = self._do_insert(cls._base_manager, using, fields, update_pk, raw)
  File "/usr/local/lib/python3.7/site-packages/django/db/models/base.py", line 908, in _do_insert
    using=using, raw=raw)
  File "/usr/local/lib/python3.7/site-packages/django/db/models/manager.py", line 82, in manager_method
    return getattr(self.get_queryset(), name)(*args, **kwargs)
  File "/usr/local/lib/python3.7/site-packages/django/db/models/query.py", line 1186, in _insert
    return query.get_compiler(using=using).execute_sql(return_id)
  File "/usr/local/lib/python3.7/site-packages/django/db/models/sql/compiler.py", line 1332, in execute_sql
    cursor.execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 99, in execute
    return super().execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 67, in execute
    return self._execute_with_wrappers(sql, params, many=False, executor=self._execute)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 76, in _execute_with_wrappers
    return executor(sql, params, many, context)
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
  File "/usr/local/lib/python3.7/site-packages/django/db/utils.py", line 89, in __exit__
    raise dj_exc_value.with_traceback(traceback) from exc_value
  File "/usr/local/lib/python3.7/site-packages/django/db/backends/utils.py", line 84, in _execute
    return self.cursor.execute(sql, params)
django.db.utils.IntegrityError: Problem installing fixture '/app/app/data.json': Could not load wagtailembeds.Embed(pk=2): duplicate key value violates unique constraint "wagtailembeds_embed_hash_c9bd8c9a_uniq"
DETAIL:  Key (hash)=() already exists.

There are just a couple of embed records so I'll remove them from the dump
{
  "model": "wagtailembeds.embed",
  "pk": 1,
  "fields": {
    "url": "https://youtu.be/HtuaL9OOIkc",
    "max_width": null,
    "type": "video",
    "html": "<iframe width=\"480\" height=\"270\" src=\"https://www.youtube.com/embed/HtuaL9OOIkc?feature=oembed\" frameborder=\"0\" allow=\"autoplay; encrypted-media\" allowfullscreen></iframe>",
    "title": "PrimarySite promotional video",
    "author_name": "ThePrimarySite",
    "provider_name": "YouTube",
    "thumbnail_url": "https://i.ytimg.com/vi/HtuaL9OOIkc/hqdefault.jpg",
    "width": 480,
    "height": 270,
    "last_updated": "2018-09-02T15:37:06.843"
  }
},
{
  "model": "wagtailembeds.embed",
  "pk": 2,
  "fields": {
    "url": "https://vimeo.com/287978345",
    "max_width": null,
    "type": "video",
    "html": "<iframe src=\"https://player.vimeo.com/video/287978345?app_id=122963\" width=\"640\" height=\"360\" frameborder=\"0\" title=\"PrimarySite Demo Video\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>",
    "title": "PrimarySite Demo Video",
    "author_name": "Nick Rawson",
    "provider_name": "Vimeo",
    "thumbnail_url": "https://i.vimeocdn.com/video/723258267_640.jpg",
    "width": 640,
    "height": 360,
    "last_updated": "2018-09-03T10:04:56.957"
  }
},

Now ill try updating to 2.12.2
The migrations worked OK
So now the sites working, somewhere there's a couple of videos missing but we can add them back in I hope.

@nickmoreton Glad you got it working. I don't think you need to take any further action to add those records back: the records you had to delete were duplicate records that shouldn't have been there, and in any case, the embeds table only serves as a cache to store the data returned by the embed provider - so even if you did delete something important from there, the only ill effect would be that it has to re-download that data next time someone visits a page using that embed.

I'm having the same issue, when upgrading from wagtail 2.11.
I use MySQL DB and at first the error is exactely the same
Then when I run
./manage.py migrate wagtailembeds 0005
./manage.py migrate

I face the issue
line 133, in _delete_composed_index
    return super()._delete_composed_index(model, fields, *args)
  File "/Users/AlexandreR/Library/Python/3.9/lib/python/site-packages/django/db/backends/base/schema.py", line 437, in _delete_composed_index
    raise ValueError("Found wrong number (%s) of constraints for %s(%s)" % (
ValueError: Found wrong number (0) of constraints for wagtailembeds_embed(url, max_width)

In the same wagtailembeds.0008_allow_long_urls migration.
Any tip?

I just resolved this same issue and the solution is pretty simple, especially if you have a GUI to interact with the database (I'm using HeidiSQL). For reference, I'm on Wagtail 2.13.1 and Django 3.2.4.

Drop the wagtailembeds_embed table.
Remove all 'wagtailembeds' migrations from the django_migrations table.
Run 'python manage.py migrate'.

It'll just rebuild the whole table cleanly.


Accessibility -  Page Summary - Screen Reader

A wireframe design and justification that showcases the  summary of what a given page is about. Which can be read by a screen reader.

Made issue #369 to create an accessibility checklist that can be used for the MVP and going forward. Closing this along with other accessibility checklist items for now.


Allow output in any programming language

I've been looking into generating some custom TypeScript code based on some 3rd party TypeScript interfaces. I was hoping that this project could work for that, as it seems it is mostly a tool that parses a TypeScript interface then calls renders a Mustache template with the AST/metadata. It seems though that this tool explicitly requires your output to be either Swift or Kotlin. Could it be possible to allow custom language outputs (where the user would have to provide any language-specific transform logic)?

Sorry for missing this issue. Yes, I think it's feasible, ts-gyb's workflow is kind of simple. A Parser to read the type information from TS and a render to convert ts type to the target language's type and render the template.
The parsing part can be shared for all target language, and to support a new target language, we just need a new value type transformer to handle the type conversion.
Unluckily, our team doesn't have bandwidth to extend it but welcome to raise the PR


Append OAuth redirect URI to Slack OAuth URL

Summary
This PR appends a redirect_uri query param value based on the redirect URI specified in a given AppConfig, if such a value is set. This change enables Bolt application developers who need to configure their Slack applications with multiple OAuth redirect URIs to be explicit about where the OAuth callback should return to their Bolt application.
Requirements

[x] I've read and understood the Contributing Guidelines and have done my best effort to follow them.
[x] I've read and agree to the Code of Conduct.

 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.

@seratch this PR should address https://github.com/slackapi/java-slack-sdk/issues/491. Let me know if I can help annotate this PR to keep things organized on your end.


Update Python-lsp-server to Version 1.4.1

python-lsp-server version 1.4.1

[x] Check the upstream
https://github.com/python-lsp/python-lsp-server/tree/v1.4.1

[x] Check the pinnings

pluggy>=1.0.0
https://github.com/python-lsp/python-lsp-server/blob/v1.4.1/setup.cfg#L17
setuptools>=39.0.0
https://github.com/python-lsp/python-lsp-server/blob/v1.4.1/setup.cfg#L19

[x] Check the changelogs
https://github.com/python-lsp/python-lsp-server/blob/v1.4.1/CHANGELOG.md

The changes mentioned were bug fixes and new features.

[x] Additional research
https://github.com/conda-forge/python-lsp-server-feedstock/issues

There is only one open issue at the time of the review. It is a request to simplify the optional dependencies needed. This should not affect our ability to build the package.

[x] Verify the dev_url
https://github.com/python-lsp/python-lsp-server

[x] Verify the doc_url
https://github.com/python-lsp/python-lsp-server/blob/develop/README.md

[x] License is spdx compliant

[x] License family is present

[x] Verify that the build_number is correct

[x] Verify if the package needs setuptools

[x] Verify if the package needs wheel

[x] pip in the test section

[x] Veriy the test section

[x] Verify if the package is architecture specific or Noarch

[x] Private variables are not mentioned on the recipe For example: (_private_variable)

Results:
Based on the research findings and the results we can conclude
that it is safe to update python-lsp-server to version 1.4.1

We are only going to build the latest version of Python-lsp-server


add SystemErrno to Error

fixes #678

@mattn @GJRTimmer sqlite3_system_errno was added in SQLite 3.12.0. I guess whatever version you are using in the libsqlite3 tests is older than that. I don't see anywhere in your README that mentions a minimum required version of libsqlite3. How would you like me to proceed?

Coverage increased (+0.2%) to 50.622% when pulling 57bd9d12d147a8672f30ffb36d19bd6b944e07d5 on rittneje:feature/678-add-system-errno-to-error-struct into d3c690956bde8789300d0dd7e868189cb88cf6ad on mattn:master.

@mattn @GJRTimmer I was able to leverage the C pre-processor to work around the version issue.

@mattn @GJRTimmer sqlite3_system_errno was added in SQLite 3.12.0. I guess whatever version you are using in the libsqlite3 tests is older than that. I don't see anywhere in your README that mentions a minimum required version of libsqlite3. How would you like me to proceed?

The libsqlite3 test is using the library on the Travis CI system. Don't know if we can update to force a specific version.

@rittneje On first glance, this PR look great.

Sounds good to me.

@mattn What is the default we are using for merging "Create a Merge Request" of "Squash and merge"

I don't have strong opinion. Feel free to create rule if you want. :)

@GJRTimmer @mattn Can this be merged?

ping @mattn

Thanks


CUDA out of memory when run "python visualize_flow.py --eval_type seq"

Thanks for your excellent work! I use the command "python visualize_flow.py --eval_type seq" to test the code, and got an error "RuntimeError: CUDA out of memory. Tried to allocate 1.48 GiB (GPU 0; 5.78 GiB total capacity; 2.33 GiB already allocated; 1008.06 MiB free; 2.99 GiB reserved in total by PyTorch)"
My gpu is 3060 with 6GB memory, I dont understand why "out of memory" during inference?

Same problem even with few low res frames

You can reduce the TRAIN_SIZE parameter in visualize_flow.py

Yes. You can reduce the TRAIN_SIZE. You can also try the FlowFormer-small. :hugs:


Some updates and connection usage improvement

(Rakefile) update the gem packaging
(README) update the port parameter in the yaml
(example-stable.sql) adds a example table to be used with the module
(mysql_backend) updates the module to use only one connection on jruby and
close the statement after using
adds port as parameter for both jruby and ruby

Looks good to me @ncode - thanks, will get this rolled in.


enhancements

Everything worked expect whosthatpokemon, the timeout became 30sec delayed to timeout.
I see, is that because of the self.message: discord.Message = None ? I have seen you around playing with the buttons of this cog, trying to fix it, did you intentionally didn't have self.message in the __init__ ?

Everything worked expect whosthatpokemon, the timeout became 30sec delayed to timeout.

I see, is that because of the self.message: discord.Message = None ? I have seen you around playing with the buttons of this cog, trying to fix it, did you intentionally didn't keep self.message in the __init__ ?

Yeah, i dropped that self.message since it wasn't used / needed. kreu didn't made me use it either from his qa review so, and it's made from flame! :P

Thanks! That should be it.


Add disabled_on field to all metadata admin.

As in the title - except for OMIS

Codecov Report

Merging #632 into develop will increase coverage by <.01%.
The diff coverage is 100%.

@@             Coverage Diff             @@
##           develop     #632      +/-   ##
===========================================
+ Coverage    96.45%   96.45%   +<.01%
===========================================
  Files          130      130
  Lines         3892     3898       +6
  Branches       335      335
===========================================
+ Hits          3754     3760       +6
  Misses          97       97
  Partials        41       41

Impacted Files
Coverage Δ

datahub/interaction/admin.py
100% <100%> (ø)
:arrow_up:

datahub/metadata/admin.py
100% <100%> (ø)
:arrow_up:

datahub/investment/admin.py
100% <100%> (ø)
:arrow_up:

datahub/event/admin.py
100% <100%> (ø)
:arrow_up:

Continue to review full report at Codecov.

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Load seconds into intitial time value

This patch lets developers set the seconds value, which wasn't possible before without also specifying a date.
It also fixes a couple of issues surrounding this bug, both of which were caused by JavaScript treating 0 as a falsy value.

Looks good :+1:
I'll merge and refine over the weekend


Spacedock compatibility flag overrides the .version file

I just found that two of my  most important mods, ClickThroughBlocker and ToolBarController, have not been available for 1.7, even though the .version files embedded in each allowed the compatibility.
Upon investigation, I saw that Spacedock was saying that they weren't compatible, I had to go and manually update each mod to allow the compatibility.
This is unexpected and wrong.  The .version file is supposed to specify the compatibility.  I have a significant number of bug reports because of this

No, that's not how it works. AVC overrides SD. Need actual examples of what you're saying.

OK, "overrides" is not quite the right word. The values from SD and AVC are combined. The logic is in the AVC netkan code; both SD and AVC are checked for min and max values, and the smallest value is used for min and the largest for max:
https://github.com/KSP-CKAN/CKAN/blob/44d44ea5cd38e2f568d95f2af6d24674e01f7a45/Netkan/Transformers/AvcTransformer.cs#L131-L184
I don't think any of that could be changed without breaking things.
Recommendation: revert #7032 and #6659. If you want an open-ended version range defined completely by the AVC file, then a host that requires selection of the compatible game version is not for you. GitHub is a better fit.

I'll do that for the KURS to get the correct versions, and will move it back to spacedock when I push out the 1.7.0 version of KURS.
For the others, I'll just have to keep it in mind


Category Class (part of the Book Part)

The Category Class should differ from the Tag Class in that the Category class should have the option of having a parent Category class whereas the Tag Class is a pool of tags associated with a data object.
I should probably revise my ER diagram to reflect this difference.
Think of how tags are simply keywords that you can associate with something where as a category is structured classification.


GS series related updates to be published after 8/31

Added limits and verbiage related to GS-series VM support on Premium Storage. Since the official GS series Marketing content will be updated on 9/2, we want to publish this content in that week as well.

Pradnya

Hi @ms-prkhad, I'm your friendly neighborhood Azure Pull Request Bot (You can call me AZPRBOT). Thanks for your contribution!

In order for us to evaluate and accept your PR, we ask that you sign a contribution license agreement. It's all electronic and will take just minutes. I promise there's no faxing. https://cla.azure.com.

TTYL, AZPRBOT;

@ms-prkhad Thank you for these edits.  It appears you may be MSFT internal.  Would you please update your profile to meet the guidelines so pull request reviewers can recognize you?

@tamram Would you please review these edits and let me know if I have your approval to merge this request?  Thank you.

At MSFT as prkhad - CLA not required


malloc.c: No such file or directory

x_train Examples Loaded = (55000, 784)
y_train Examples Loaded = (55000, 10)
[ 0.  0.  1.  0.  0.  0.  0.  0.  0.  0.]
[New Thread 0x7ffff2211700 (LWP 6011)]
[New Thread 0x7ffff2a12700 (LWP 6012)]
[New Thread 0x7fffd33a4700 (LWP 6013)]
[Thread 0x7fffd33a4700 (LWP 6013) exited]
[Thread 0x7ffff2a12700 (LWP 6012) exited]
[Thread 0x7ffff2211700 (LWP 6011) exited]
Program received signal SIGSEGV, Segmentation fault.
0x00007ffff716602f in _int_free (av=0x7ffff74a8760 <main_arena>,
p=, have_lock=0) at malloc.c:3996
3996	malloc.c: No such file or directory.
gdb backtrace report
(gdb) bt
#0  0x00007ffff716602f in _int_free (av=0x7ffff74a8760 <main_arena>,
p=, have_lock=0) at malloc.c:3996
#1  0x00007ffff2ad9ef0 in ?? ()
from /home/shreeranga/PP/Exp/venvs/lib/python2.7/site-packages/numpy/core/..0
#2  0x00007ffff2ad4770 in ?? ()
from /home/shreeranga/PP/Exp/venvs/lib/python2.7/site-packages/numpy/core/..0
#3  0x00007ffff2ad486a in ?? ()
from /home/shreeranga/PP/Exp/venvs/lib/python2.7/site-packages/numpy/core/..0
#4  0x00007ffff2a28e09 in ?? ()
from /home/shreeranga/PP/Exp/venvs/lib/python2.7/site-packages/numpy/core/..0
#5  0x00007ffff2a26e7f in ?? ()
from /home/shreeranga/PP/Exp/venvs/lib/python2.7/site-packages/numpy/core/..0
#6  0x00000000009649e0 in ?? ()
#7  0x00007ffff521f1c8 in __frame_dummy_init_array_entry ()
from /home/shreeranga/PP/Exp/venvs/lib/python2.7/site-packages/numpy/core/..o
#8  0x00007fffffffdc00 in ?? ()
#9  0x00007ffff2ae7cd1 in ?? ()

It's a SEGV, which looks like numpy. Could you answer the following:

What tensorflow version are you using? Which OS?
Can you build from source with debug symbols and try again?
Were you loading ops or using something in tf.contrib?
Any small repro?

I'm using tensorflow 1.1.0 and my OS is Ubuntu 14.04
I couldn't build from the source. However, I uninstalled tensorflow and pip installed again. Everything seems to be working now.

OK, please reopen if it happens again and you have a way to repro.


Update sbt-header to 5.2.0

Updates de.heikoseeberger:sbt-header from 5.0.0 to 5.2.0.
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention @scala-steward in the comments below.
Have a nice day!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [{ groupId = "de.heikoseeberger", artifactId = "sbt-header" }]

superseded by #72


indexing/search for configuration

Try to evaluate whoosh for fields/data indexing

[x] added a generic find for config store.
[x] enable selecting whoosh from configuration (with correct needed parameters)
[x] implement find for factories
[x] create whoosh schema from base types (see if it can be created in runtime).
[x] implement add/list/delete with instance_name_ as a mandatory unique whoosh field.
[x] implement find using whoosh queries
[x] Explicit saving -not auto-save anymore, and it's much faster :laughing:-
[x] find_many should return the new cursor if any and a generator for results (also store.find).
[x] More documentation for stores and how to use them (including whoosh store).
[x] Document find_many and it's relation to current configured store.

For later
~- [ ] handle schema updates (maybe with migrations)~
~- [ ] caching for factories (as a layer on top-of data stores, need to discuss if we will require e.g. redis).~

After some investigation, there're two ways to implement this, either we support indexing for any base type used with stored factories, or we add whoosh as another storage type, in both cases, we need to consider the following:

Mapping from our configuration fields to whoosh fields.
Data consistency via migration/versioning (whoosh schema can be modified).

I'm still trying multi-process read/writes (using AsyncWriter).

It seems like AsyncWriter works well with gevent.
Will start implement whoosh as store backend.

Some tests still fail (stored factory tests).
They are mostly related to stored None values and Enums, can be checked later.

Used MultifieldParser for multi-field queries:
So, it can be used with multiple fields like:
factory.find_man(first_name="ab", rating=1)

Also, Float numeric fields are not working in whoosh, related issue:
https://bitbucket.org/mchaput/whoosh/issues/448/whoosh-numeric-float-fields

This code had an issue when saving:
from jumpscale.core.base import Base, fields, StoredFactory
class Model(Base):
    run_id = fields.String()
    status = fields.String(required=True)
    result = fields.List(field=fields.Typed(dict))
m = StoredFactory(Model)
o = m.new("test", status="error", run_id="12", result=[{"name": "test2", "type": "log", "content": "this is a test"}])

Handled Enum with different types dynamically, now we only have the float issue.
Another link from github:
https://github.com/whoosh-community/whoosh/issues/448.

Also, the problem mentioned here is fixed.

on commit: https://github.com/threefoldtech/js-ng/commit/e63cef73a0556e3c8915f07c499e74336b470421
objects returned from find_many are not exact matching for what is searched for.

The problem mentioned here should be fixed by this commit https://github.com/threefoldtech/js-ng/pull/322/commits/5240483ab27405f107f8a49a19e9fca517200fc7.

Now the store and generic search are ready, also added docs at https://github.com/threefoldtech/js-ng/blob/9c391338ed6c840ce2e941fa1cc6ea3ca3ab59be/docs/wiki/stores.md#always-reload.

I am verifying it

verifying


*: Remove AtomicU64 on unsupported platforms

As stated in #37 in regard to how this crate handles std::sync::atomic::AtomicU64, this PR removes any occurrences of this struct and instead defaults to its 32-bit version where appropriate.
[lychee  client_rust | drop-atomic64-for-unsupported-platforms  $] cross build --release --target=mipsel-unknown-linux-gnu
    Finished release [optimized] target(s) in 0.09s

Thanks for the help here.
I can do a patch release in the next couple of days, in case that is of some help @chitoku-k?!

Thanks! It would be appreciated if this is going to be released with a patch release in the near future as I am currently working with this using crate patch.