Plugin manager does not respect the visibility field in the manifest

The current version of npe2 supports setting the visibility field in the plugin manifest to hidden if the plugin developer wants to keep the Framework:: napari classifier but not be discoverable on the napari hub and in the plugin manager. The napari hub is being updated to respect this field as we speak, but we should also update the plugin manager to respect this field and not display plugins with visibility: hidden in search results.

Thanks for the heads up @DragaDoncila, will work on a fix :)

I think that we should update the server that gathers this information for us. So I think that this issue should be moved to https://github.com/napari/npe2api

That is a good suggestion indeed. You suggest that the info we query over at npe2api already only includes visible plugins? or that it contains that info over there and we still filter them directly on the plugin manager?

I suggest that npe2api should not serve information about hidden plugins.


Pass toolchainLibDir if using XCBuild

We pass this as an additional -L when building with SwiftPM's own build system, so we should also pass this when using XCBuild.
rdar://82313817

Going the same route as how we are passing SWIFT_EXEC here, another option would be setting it in the PIF itself.

Looks good to me, and is similar to the SWIFT_EXEC that had to be added recently (the line above the one you added).
Are there other settings that we need to pass as well, of a similar ilk?
Also, are there any meaningful unit tests that can be added here?  I added one for SWIFT_EXEC I think, maybe it can be extended.

It looks like there are a few more settings which could be interesting:

macosSwiftStdlib which gets passed passed to executables and tests on Darwin in the SwiftPM build system, so we should pass that via the PIF
getClangCompiler() which we should probably also pass here
extraCCFlags, extraSwiftCFlags and extraCPPFlags which I am not sure about whether we should pass them as overrides here or via the PIF

16:05:21 Test Case 'APIDiffTests.testCheckVendedModulesOnly' started at 2021-08-27 18:03:56.638
16:05:21
/home/buildnode/jenkins/workspace/swift-package-manager-self-hosted-Linux-smoke-test/branch-main/swiftpm/Tests/CommandsTests/APIDiffTests.swift:144: error: APIDiffTests.testCheckVendedModulesOnly : XCTAssertTrue failed -
16:05:21 Test Case 'APIDiffTests.testCheckVendedModulesOnly' failed (21.405 seconds)

This doesn't look related.

I rudely committed my changes to see if everything will build together

@swift-ci please test

@swift-ci please smoke test

Since this change unblocks work on back-deploying concurrency, I'm going to go ahead and merge.

Since this change unblocks work on back-deploying concurrency, I'm going to go ahead and merge.

@DougGregor
=> lets circle back to @neonichu above: https://github.com/apple/swift-package-manager/pull/3695#issuecomment-907519078
=> should adding this path also apply outside the context of XCBuild? ie when you using swift build on a mac we would want the same behavior, no
=> finally, buildParameters.toolchain.toolchainLibDir points to where SwiftPM places its dylibs used to provide the manifest and plugins "scripts" APIs. What would create these new swift/macosx subdirectories and place libraries there?

SwiftPM's build system already passes all these, it's just missing from builds with XCBuild as the build system.
I believe the libraries in swift/macosx get created by the compiler itself, e.g. this is where compatibility libraries end up (which initially spawned this PR).

I believe the libraries in swift/macosx get created by the compiler itself, e.g. this is where compatibility libraries end up (which initially spawned this PR).

got it

I believe the libraries in swift/macosx get created by the compiler itself, e.g. this is where compatibility libraries end up (which initially spawned this PR).

got it, is it new?

No, it is not new, but the set of compatibility libraries hasn't changed since Swift 5.1, which (I think) predates the introduction of this code path. The SwiftPM path gets it for free because the Swift driver is responsible for forming the link line, not XCBuild.


Reworked installation process. Solves Issue #4

Reworked installation Process to ease the installation on platform. For now only optimized for windows. Solves Issue #4

Found out that I made a mistake and you cannot install the VirtualBox SDK with pip. Reverted that change

Found out that I made a mistake and you cannot install the VirtualBox SDK with pip. Reverted that change


[FEATURE] Donate button linking to GitHub Sponsors

Description
We have social icons but it would be great to have a donate button, that linked to their GitHub Sponsor profile
Screenshots

https://linkfree.eddiehub.io/eddiejaoude
Additional information
No response

You can add a link with your link to a GitHub Sponsors or any other donations service profile. But having a button would be interesting too.

This would be a wonderful addition

@eddiejaoude can you please let me know which page are you referring to on the site?

@dheesimha people can add it as a link as mentioned by @Panquesito7 but I think if we have a special section in their json for donation and we can make it more prominent on the page - maybe bottom left for example

@eddiejaoude ,thanks for responding.I am new to Eddiehub, discovered you on Sunday via FreeCodeCamp's youtube channel and found your community very interesting and thought it was a perfect opportunity for me to get started with Open Source.
Hence I came across this issue, and I was unclear about which site was being referred over here. Could you please link the site you are talking about, so that I can understand the issue thoroughly and what needs to be done?
Thanks.

@dheesimha sorry for not being clearer, I have updated the description with a link and a screenshot - if you need more info let me know

Thanks a lot for updating the description @eddiejaoude . Now it's perfectly clear what the requirement is. So as per my understanding, we would require a button that says donate  in the bottom left corner and display that only if the person has enabled the sponsor option on GitHub, right?

yes that I correctly, I was initially thinking if they have adding the json property sponsored with a link, but you are correct, we could check if it is enabled on their GitHub via the GitHub API

Assigned 👍

I think this would work well using the same style as the help button on the home page, so on the profile page it would appear Sponsor if they have it setup

Cool.I'll keep that in mind !

anybody working on this issue??

@dheesimha are you working on this?

I have unassigned the issue as there has been no recent activity.

Can I work on this?

Can I work on this?

@sansarmaske I have assigned this to you

Q: Won't there be 2 button there, one for the testimonials and another for sponsors? wouldn't that be too much

Q: Won't there be 2 button there, one for the testimonials and another for sponsors? wouldn't that be too much

good spot, this issue was created before we had testimonials - but the button could go on the left side

On smaller screens that will still overflow :thinking:

Maybe we can put Sponsor button above testimonials button for mobile view?

I do not think we should put that many things down the bottom 🤔 Most people do not have more than 4-5 socials, it would be a good idea to put a button there IMO

We can also put it below social media icons. What do you think @eddiejaoude ?

I am thinking we should close this issue for now, as we have no clear solution and people are adding this to their list of links
Thank you all for working through this together, great collaboration 💪


Settings - Add option to clear Profile pic + Banner

**Task: ** From Stu's list, we want to add the ability for a user to clear they're PFP and PFB from the Settings/Profile page

This feature doesn't work on Linux as of yesterday when PR #436 was merged. It's a UI issue at this point.

Verified its fixed on my end after merging #448 tested this on Windows 11 Linux(Ubuntu) MacOS


It is possible use this library to stream a local camera?

It is possible use this library to stream a local camera ( like /dev/video ) in a web page ( using flask or another webserver ) ?

any help?
a simple example of how to stream /dev/video0 in h264 through a web page would be perfect

@blademckain I would not recommend trying this with ffmpeg - the part of the library that used to do this has been removed.
I think you'll have a lot easier time using something like https://github.com/mpromonet/v4l2rtspserver to provide an RTSP feed of a webcam.

That said, if you need to do some processing in the middle, you might use ffmpeg V4L support to read from the input and then output as a V4L device. I haven't played with this, as I don't have a Linux machine with a webcam at the moment.

An input parameter for ffmpeg to capture from local web camera is: -i video=My_web_cam_name. This parameter works at least in Windows. An attempt to use: ffmpeg.input('video=My_web_cam_name') raises error video="Unity Video Capture": Invalid argument.
How to read the local web camera with ffmpeg-python in Windows?


npm run build-dts fails with "Cannot find name 'Iterable'"

<EMAIL_ADDRESS>> npm run build-dts
> tsc --allowJs --declaration --emitDeclarationOnly --module amd --outFile ./dist/index.d.ts ./src/index.js ./src/types.d.ts && node ./utils/bundle-dts.js && tsc --noEmit ./dist/index.d.ts

src/types.d.ts:1:37 - error TS2304: Cannot find name 'Iterable'.

1 interface IndexedCollection extends Iterable<number> {
                                      ~~~~~~~~

Found 1 error.

Judging by this stackoverflow answer npm install @types/node --save-dev can save the day, but this dependency dont have mention in package.json
Also installing @types/node make project unhappy:
npm ERR! code ERESOLVE
npm ERR! ERESOLVE unable to resolve dependency tree
npm ERR!
npm ERR! While resolving<EMAIL_ADDRESS>npm ERR! Found<EMAIL_ADDRESS>npm ERR! node_modules/rollup
npm ERR!   dev<EMAIL_ADDRESS>from the root project
npm ERR!
npm ERR! Could not resolve dependency:
npm ERR! peer<EMAIL_ADDRESS>from<EMAIL_ADDRESS>npm ERR! node_modules/rollup-plugin-size-snapshot
npm ERR!   dev<EMAIL_ADDRESS>from the
root project
npm ERR!
npm ERR! Fix the upstream dependency conflict, or retry
npm ERR! this command with --force, or --legacy-peer-deps
npm ERR! to accept an incorrect (and potentially broken) dependency resolution.

npm install @types/node --save-dev -f do it's job. After that npm run build-dts works just fine

Ok that big log throws even with simple npm install

My bad, forgot to call npm install before run. @types/node already included as a dependency for del-cli
> npm ls @types/node
<EMAIL_ADDRESS>/mnt/c/Project/fork/gl-matrix
└─┬<EMAIL_ADDRESS>  └─┬<EMAIL_ADDRESS>    └─┬<EMAIL_ADDRESS>      └─┬<EMAIL_ADDRESS>        └──<EMAIL_ADDRESS>


refactor(cli): cleanup platformUrl method

Proposed changes
Extracted the fuss out of the method to make it cleaner.
Testing

[X] Unit Tests: covered
[X] Functionnal Tests: covered
❌  Manual Tests: above is enough imo ('specially the UT)

CDX-404

(GitHub Action is ded, see y'all next week)


ClangFormat incorrectly splits Objective-C string literals

I cloned and pulled the latest release of ClangFormat, which still exhibits this bug.
An NSArray literal containing NSString literals before running ClangFormat:
  NSArray *testInputStrings = @[
    @"abcdefg",
    @"*^&I*BEI*BDI C# RG#RC#YJGR #",
    @"那隻敏捷的棕色狐狸跳線懶狗。",
    @"1",
    @"12",
    @"123",
    @"1234",
    @"12345",
    @"123456",
    @"1234567",
    @"12345678",
    @"123456789",
    @"1234567890",
 @"kljsadgflkuyaerkuqhfbdsalkfbalkshdeklahdskjbfaskljhraslkrhuwbdbhsCKJhbasjkhfawkjhgrkjaebfdjkahsbdfjkhawkjfegkqrwjygr3uy24764587321rgj32hvr4jkh2vrkj2vfqrfqwjkh*&^*^&*RIBIEBKHBDJHABJEHBjqdbwjy3egjwybdehjbdfjsdhbfjsehbfjhsbfsjhbfdjshbfsmdbfshfbejw3jbfdsmhbdmshbfs"
  ];

The same NSArray literal after running ClangFormat:
  NSArray *testInputStrings = @[
    @"abcdefg",
    @"*^&I*BEI*BDI C# RG#RC#YJGR #",
    @"那隻敏捷的棕色狐狸跳線懶狗。",
    @"1",
    @"12",
    @"123",
    @"1234",
    @"12345",
    @"123456",
    @"1234567",
    @"12345678",
    @"123456789",
    @"1234567890",
    @"kljsadgflkuyaerkuqhfbdsalkfbalkshdeklahdskjbfaskljhraslkrhuwbdbhsCKJhbasj"
    @"khfawkjhgrkjaebfdjkahsbdfjkhawkjfegkqrwjygr3uy24764587321rgj32hvr4jkh2vr"
    @"kj2vfqrfqwjkh*&^*^&*"
    @"RIBIEBKHBDJHABJEHBjqdbwjy3egjwybdehjbdfjsdhbfjsehbfjhsbfsjhbfdjshbfsmdbf"
    @"shfbejw3jbfdsmhbdmshbfs"
  ];

Have set PenaltyBreakString:<PHONE_NUMBER> and clang-format is still breaking Objective-C string literals.
In my eyes, this issue should be reopened

It also seems to be a bug for me. I thought that PenaltyBreakString  should always have a higher priority than the ColumnLimit . Otherwise, is there a way for us to keep these two settings effective at the same time?

In my eyes, this issue should be reopened

It's not an issue with ClangFormat-Xcode. You need to report these issues to the LLVM Bugzilla.


How can I use the Azure Sink Connector?

Is there any basic procedure to follow in order to set up this connector?

@marcos1990 Azure sink?

@marcos1990 Theres a documentDB sink http://lenses.stream/connectors/sink/azuredocdb.html

They renamed Document Db to Cosmos Db.  Is this the one I would use to push to Cosmos Db?

@DaveSlinn  yes they did  but they did not change the endpoints. It uses the Microsoft drivers for talking to CosmosDb.


Replace 'aarch64' labels in favor of 'arm64'

Please @JonatanAntoni after merging it, create a new tag or branch with 'v1.2'.
I will use that in an upcoming patch for devtools.

I think you already created the v1.2. We just to update it.


Add a new vectorstore - AwaDB

Added AwaDB vector store, which is a wrapper over the AwaDB, that can be used as a vector storage and has an efficient similarity search.
Added integration tests for the vector store
Added jupyter notebook with the example
Complete the notebook about AwaDB which had not notebook in the last pr(https://github.com/hwchase17/langchain/pull/5687)
Please check, Thanks!
@dev2049
@hwchase17

there seems to be an empty jupyter notebook? otherwise lgtm!

you are right, there exists a unneeded file - awadb.ipypb, should be deleted! thanks!

there seems to be an empty jupyter notebook? otherwise lgtm!

you are right, there exists a unneeded file - awadb.ipypb, should be deleted! thanks!

@hwchase17  Could you please check it again? Thanks!


CDS-311 Add --reuse-db to addopts to reduce upfront timecost of db tests

Description of change
So, after looking through the profiling output of the database-dependent tests in data-hub-api, it looks like there is an upfront cost to creating the schema of the database that the tests are to be run on of about ~40 seconds.
This marries up with the observations myself and others have made; that there is a large wait time when running even a single database-dependent test in datahub API, so reducing or removing this overhead would seem to be a valuable exercise.
So, django-pytest provides a flag to its testing command to keep the test database after the tests have executed, and if the database exists, reuse it in the current execution: --reuse-db
Setting this flag on two concurrent runs caused the test suite execution time of pytest datahub/dataset/interaction/test/ to drop from 42.85s to 6.12s
This flag has been known about for a while, but people often forget to set it. Fortunately pytest allows you to specify default command line flags in the pytest.ini file by appending them to the addopts configuration option. This will allow the database to be reused by default. This can be overwritten by appending --create-db to the command line invocation of pytest
If additional migrations have been added since the previous test execution, these seem to be applied even with --reuse-db set
In CircleCI, the behavior will remain unchanged as we're always creating a new database as part of each CI execution

Checklist

[ ] If this is a releasable change, has a news fragment been added?

Explanation
A news fragment is required for any releasable change (i.e. code that runs in or affects production) so that a corresponding changelog entry is added when releasing.
Check changelog/README.md for instructions.

[ ] Has this branch been rebased on top of the current develop branch?

Explanation
The branch should not be stale or have conflicts at the time reviews are requested.

[ ] Is the CircleCI build passing?

General points

Other things to check

Make sure fixtures/test_data.yaml is maintained when updating models
Consider the admin site when making changes to models
Use select-/prefetch-related field lists in views and search apps, and update them when fields are added
Make sure the README is updated e.g. when adding new environment variables

See docs/CONTRIBUTING.md for more guidelines.

To verify that no leftover dynamic data is present after the test execution (i.e. that every test that populates data is wrapped in at least one transaction the prevents it committing data to the database), I ran the test suite then looked at the number of rows present for every table in the test database after the test run had completed. I can't see anything that looks like data that would populated outside of the context of a data migration, but if anyone can see any please let me know.
test_datahub=# select table_schema,
       table_name,
       (xpath('/row/cnt/text()', xml_count))[1]::text::int as row_count
from (
  select table_name, table_schema,
 table_name), false, true, '') as xml_count*) as cnt from %I.%I', table_schema,
  from information_schema.tables
  where table_schema = 'public' --<< change here for the schema you want
) t
;
 table_schema |                           table_name                            | row_count
--------------+-----------------------------------------------------------------+-----------
 public       | django_migrations                                               |       238
 public       | django_content_type                                             |       132
 public       | auth_permission                                                 |       549
 public       | auth_group_permissions                                          |       174
 public       | metadata_businesstype                                           |        12
 public       | metadata_employeerange                                          |         5
 public       | omis-market_market                                              |       218
 public       | metadata_title                                                  |        47
 public       | metadata_fditype                                                |         7
 public       | metadata_headquartertype                                        |         3
 public       | metadata_turnoverrange                                          |         4
 public       | metadata_referralsourceactivity                                 |        51
 public       | metadata_referralsourcewebsite                                  |         5
 public       | metadata_overseasregion                                         |         9
 public       | metadata_sectorcluster                                          |         6
 public       | metadata_service                                                |       230
 public       | metadata_sector                                                 |       256
 public       | metadata_salaryrange                                            |         4
 public       | metadata_referralsourcemarketing                                |         7
 public       | metadata_fdivalue                                               |         3
 public       | metadata_teamrole_groups                                        |        27
 public       | omis-payment_payment                                            |         0
 public       | metadata_teamrole                                               |        25
 public       | omis-payment_refund                                             |         0
 public       | metadata_administrativearea                                     |       373
 public       | omis-payment_paymentgatewaysession                              |         0
 public       | auth_group                                                      |         5
 public       | company_advisor_groups                                          |         0
 public       | company_advisor_user_permissions                                |         0
 public       | metadata_team                                                   |      1126
 public       | metadata_ukregion                                               |        22
 public       | omis-quote_termsandconditions                                   |         1
 public       | company_exportexperiencecategory                                |         6
 public       | omis-region_ukregionalsettings                                  |         0
 public       | proposition_proposition                                         |         0
 public       | company_onelisttier                                             |         8
 public       | report_spireport                                                |         0
 public       | proposition_propositiondocument                                 |         0
 public       | company_company_export_to_countries                             |         0
 public       | search_support_simplemodel                                      |         0
 public       | search_support_relatedmodel                                     |         0
 public       | django_session                                                  |         0
 public       | company_company_future_interest_countries                       |         0
 public       | support_inheritedmodel                                          |         0
 public       | support_mydisableablemodel                                      |         0
 public       | support_permissionmodel                                         |         0
 public       | support_emptymodel                                              |         0
 public       | company_advisor                                                 |         0
 public       | company_contact                                                 |         0
 public       | support_metadatamodel                                           |         0
 public       | company_onelistcoreteammember                                   |         0
 public       | support_book                                                    |         0
 public       | django_admin_log                                                |         0
 public       | axes_accessattempt                                              |         0
 public       | axes_accesslog                                                  |         0
 public       | company_company                                                 |         0
 public       | metadata_tradeagreement                                         |         9
 public       | support_book_authors                                            |         0
 public       | support_nullablewithdefaultmodel                                |         0
 public       | support_person                                                  |         0
 public       | support_foreignandm2mmodel                                      |         0
 public       | company_companyexportcountry                                    |         0
 public       | company_companyexportcountryhistory                             |         0
 public       | feature_flag_featureflag                                        |         0
 public       | support_foreignandm2mmodel_values                               |         0
 public       | user_event_log_userevent                                        |         0
 public       | support_multiaddressmodel                                       |         0
 public       | support_personlistitem                                          |         0
 public       | company_advisor_features                                        |         0
 public       | company_list_companylist                                        |         0
 public       | company_list_pipelineitem_contacts                              |         0
 public       | company_list_companylistitem                                    |         0
 public       | company_list_pipelineitem                                       |         0
 public       | reversion_version                                               |         0
 public       | investment_investmentsector                                     |        44
 public       | investment_fdisicgrouping                                       |        18
 public       | metadata_investmenttype                                         |         3
 public       | investment_investortype                                         |         2
 public       | investment_involvement                                          |        24
 public       | investment_specificprogramme                                    |        26
 public       | investment_likelihoodtoland                                     |         3
 public       | investment_projectmanagerrequeststatus                          |         5
 public       | investment_gvamultiplier                                        |        18
 public       | metadata_investmentbusinessactivity                             |        15
 public       | investment_investmentproject_business_activities                |         0
 public       | investment_investmentproject_client_contacts                    |         0
 public       | metadata_country                                                |       218
 public       | investment_investmentproject_competitor_countries               |         0
 public       | metadata_investmentstrategicdriver                              |        10
 public       | investment_investmentproject_strategic_drivers                  |         0
 public       | investment_investmentproject_uk_region_locations                |         0
 public       | investment_investmentproject                                    |         0
 public       | investment_investmentproject_actual_uk_regions                  |         0
 public       | investment_investmentdeliverypartner                            |        90
 public       | investment_investmentproject_delivery_partners                  |         0
 public       | investment_investmentprojectcode                                |         0
 public       | metadata_investmentprojectstage                                 |         5
 public       | investment_investmentprojectstagelog                            |         0
 public       | investment_investmentprojectteammember                          |         0
 public       | investment_investmentactivitytype                               |         5
 public       | reversion_revision                                              |         0
 public       | investment_investmentactivity                                   |         0
 public       | event_event_related_programmes                                  |         0
 public       | event_eventtype                                                 |        17
 public       | event_event_teams                                               |         0
 public       | event_locationtype                                              |         4
 public       | event_programme                                                 |        29
 public       | interaction_communicationchannel                                |        11
 public       | event_event                                                     |         0
 public       | interaction_servicedeliverystatus                               |         5
 public       | interaction_policyarea                                          |        64
 public       | interaction_interaction_policy_areas                            |         0
 public       | interaction_policyissuetype                                     |         6
 public       | interaction_interaction_policy_issue_types                      |         0
 public       | company_referral_companyreferral                                |         0
 public       | interaction_interaction_contacts                                |         0
 public       | interaction_interactionditparticipant                           |         0
 public       | interaction_servicequestion                                     |         7
 public       | interaction_serviceansweroption                                 |        47
 public       | interaction_serviceadditionalquestion                           |         0
 public       | interaction_interactionexportcountry                            |         0
 public       | interaction_interaction                                         |         0
 public       | documents_document                                              |         0
 public       | event_event_related_trade_agreements                            |         0
 public       | evidence_evidencedocument                                       |         0
 public       | evidence_evidencetag                                            |        25
 public       | evidence_evidencedocument_tags                                  |         0
 public       | feature_flag_userfeatureflag                                    |         1
 public       | investor_profile_assetclassinterestsector                       |         2
 public       | investor_profile_returnrate                                     |         4
 public       | investor_profile_requiredchecksconducted                        |         4
 public       | investor_profile_investortype                                   |        14
 public       | investor_profile_equitypercentage                               |         4
 public       | investor_profile_assetclassinterest                             |        32
 public       | investor_profile_largecapitalinvestorprofile_asset_classes_6eb3 |         0
 public       | investor_profile_constructionrisk                               |         3
 public       | investor_profile_largecapitalinvestorprofile_construction_risks |         0
 public       | investor_profile_dealticketsize                                 |         6
 public       | investor_profile_largecapitalinvestorprofile_deal_ticket_sizes  |         0
 public       | investor_profile_desireddealrole                                |         3
 public       | investor_profile_largecapitalinvestorprofile_desired_deal_roles |         0
 public       | investor_profile_largecapitalinvestmenttype                     |         8
 public       | investor_profile_largecapitalinvestorprofile_investment_types   |         0
 public       | investor_profile_timehorizon                                    |         4
 public       | investor_profile_largecapitalinvestorprofile                    |         0
 public       | investor_profile_largecapitalinvestorprofile_other_countrie8ce0 |         0
 public       | investor_profile_restriction                                    |         6
 public       | investor_profile_largecapitalinvestorprofile_restrictions       |         0
 public       | investor_profile_largecapitalinvestorprofile_time_horizons      |         0
 public       | investor_profile_largecapitalinvestorprofile_uk_region_loca4ce4 |         0
 public       | opportunity_opportunityvaluetype                                |         2
 public       | opportunity_opportunitystatus                                   |         5
 public       | opportunity_opportunitytype                                     |         2
 public       | opportunity_largecapitalopportunity_asset_classes               |         0
 public       | opportunity_largecapitalopportunity_construction_risks          |         0
 public       | opportunity_largecapitalopportunity_investment_projects         |         0
 public       | opportunity_largecapitalopportunity_investment_types            |         0
 public       | opportunity_largecapitalopportunity_other_dit_contacts          |         0
 public       | opportunity_largecapitalopportunity                             |         0
 public       | opportunity_largecapitalopportunity_promoters                   |         0
 public       | opportunity_abandonmentreason                                   |         3
 public       | opportunity_largecapitalopportunity_reasons_for_abandonment     |         0
 public       | opportunity_sourceoffunding                                     |         3
 public       | opportunity_largecapitalopportunity_sources_of_funding          |         0
 public       | opportunity_largecapitalopportunity_time_horizons               |         0
 public       | opportunity_largecapitalopportunity_uk_region_locations         |         0
 public       | interaction_interaction_related_trade_agreements                |         0
 public       | interaction_interaction_companies                               |         0
 public       | metadata_exchangerate                                           |         1
 public       | my_entity_document_myentitydocument                             |         0
 public       | omis-invoice_invoice                                            |         0
 public       | omis-quote_quote                                                |         0
 public       | omis-order_hourlyrate                                           |         1
 public       | order_cancellationreason                                        |        12
 public       | order_servicetype                                               |        15
 public       | order_order_service_types                                       |         0
 public       | order_ordersubscriber                                           |         0
 public       | order_order                                                     |         0
 public       | order_orderassignee                                             |         0
(179 rows)


[Transforms] merging "master" on 06/15/2016

@rbuckton could you take a look. there is a new batch coming in. but I won't merge till this one clear off


[Migration/Upgrade] Dedicated Server (in December) - Expected Downtime

There will likely be some downtime this month as I am migrating all applications over to a new Dedicated Server, which will be much faster and more stable due to better hardware & increased RAM.
Once ESXI 7 has been installed, I'll be freshly imaging a few virtual machines that will be dedicated to this project :).

Completed.


Module names shouldn't be translated

In the German translation, lots of module names are getting translated:

BrowserWindow -> Browserfenster
Menu -> Menü
Notification -> Mitteilung
Tray -> Fach

It's confusing to find a name in your code, search for it on the website and then not find it because it was translated.

Hey @nikwen, thanks for flagging this. I've fixed these instances by deleting the translations on Crowdin. The next deploy should pick those changes up. If you spot any more problems, feel free to submit amended (non-?)translations as well!

Thank you, @erickzhao!


Stuck at loading

Hi,
I've tried using this library to my flutter project somehow its stuck on "loading" placeholder without load chat window. Direct link fine cause i tried to open via browser is worked.
my Flutter SDK version
[✓] Flutter (Channel stable, 1.22.3, on Mac OS X 10.15.7 19H2, locale en-MY)
[✓] Android toolchain - develop for Android devices (Android SDK version 28.0.3)
[✓] Xcode - develop for iOS and macOS (Xcode 12.2)
[✓] Android Studio (version 3.5)
[✓] IntelliJ IDEA Community Edition (version 2020.2.3)
[✓] VS Code (version 1.51.1)
[✓] Connected device (2 available)

//          navigationDelegate: (NavigationRequest request) {
//            if (widget.onLinkTap != null) {
//              widget.onLinkTap(request.url);
//            }
//            return NavigationDecision.prevent;
//          },
For me, remove these lines helped.

Thanks for reporting the issue 😊, the package is completely tested on Android only, I will push a new version after tests complete.

I am facing the same issue, is there any estimate for when this will be resolved?

Done in v0.0.5


Improve testing of tileset generation

At the moment many of the tests are integration tests rather than unit tests. TestGenerateTilesets and TestMetaOutputCorrect are also rather slow, especially with a debug build. This is because they both run the tileset generation routines in full.
The tests should be chopped up into smaller pieces, Google Mock should be used where appropriate, and the tile generation routines should be refactored to be more amenable to mocking.

#64 makes a little progress on this issue, checking that the order and position of generated tiles is correct.


Safari Support

Description
This is a really nice plugin! Is there any plan to add Safari support? What would be needed to support it? I would also be happy to support in it.

Thank you!
I think the biggest hurdle is that this extension uses webextension-polyfill to abstract the differences between chrome & firefox browser API calls.
It looks like Apple provides some tools for running a non-Safari extension on Safari, but I anticipate I'd need to remap all of those browser API calls to something safari-compatible. I'm not sure that is realistic.
Let me do a little more research before I say no, but it's not something I'm super familiar with.

I was able to get most things working - although there's a lot of cosmetic bugs. I'll figure out how to get it published to the app store soon.
If you're feeling bold... you can run npm run port:safari to build the extension in xcode and open in safari. You'll need to 'Allow unsigned extensions' in Safari.

This was fast! I didn't even get the chance to contribute! Thank you so much! I got it to work right away from the branch! I will be out of the office until Monday and will check it more thoroughly then.

I had the chance today to test it thoroughly and so far I couldn't find any problems apart from the missing icons that you also already found.

I fixed up some of those small issues and submitted this to the app store.
It's not approved yet, but expect to see it here soon:
https://apps.apple.com/us/app/aws-sso-extender/id6450935274

@jan-xyz app store listing is live now.

Thank you for the fast pace! I will give it a spin tomorrow! Any way to buy you a coffee? ❤ ☕ ?

I added a sponsor button to the repo, but no need - I appreciate the feedback and interest!


error while loading shared librarie

compile whit the "make problem #2" suggestions, the compilation was successful but when running test or camera I get:
"error while loading shared libraries: libmtcnn.so: cannot open shared object file: No such file or directory"
how can I fix this?

Try adding the shared library path to $LD_LIBRARY_PATH variable


Timeseries problems on TPU throw exception "unexpected keyword argument 'drop_remainder'"

Hello,
When training on both timeseries problems, timeseries_toy_problem and timeseries_synthetic_data_series10_samples100k, I get an exception, unexpected keyword argument 'drop_remainder'.  Any tips?
Thanks!
update: the following change in problem.py seems to solve the problem in this case:
dataset.batch(batch_size, drop_remainder=True) -> dataset = dataset.batch(batch_size).  However, I am not sure what's the functionality of drop_remainder and whether omitting it is ok here.
...
Environment information
OS: Debian GNU/Linux 9.4 (stretch) on Google Cloud

$ pip freeze | grep tensor
-e git+https://github.com/tensorflow/tensor2tensor.git@814c4a13e1b03e3db444b31be2e6337c02c11bc7#egg=tensor2tensor
tensorboard==1.8.0
tensorflow==1.8.0

$ python -V
Python 2.7.13

Steps to reproduce:
t2t-datagen --problem=timeseries_synthetic_data_series10_samples100k --data_dir=$DATA_DIR --tmp_dir=$TMP_DIR
t2t-trainer
--model=transformer
--hparams_set=transformer_tpu
--data_dir=$DATA_DIR
--problem=timeseries_synthetic_data_series10_samples100k
--train_steps=1
--eval_steps=1
--output_dir=$OUT_DIR
--use_tpu=True
--master=$TPU_MASTER

Error logs:
INFO:tensorflow:Found TPU system:
INFO:tensorflow:*** Num TPU Cores: 8
INFO:tensorflow:*** Num TPU Workers: 1
INFO:tensorflow:*** Num TPU Cores Per Worker: 8
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:CPU:0, CPU, -1)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:XLA_CPU:0, XLA_CPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:XLA_GPU:0, XLA_GPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:0, TPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:1, TPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:2, TPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:3, TPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:4, TPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:5, TPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:6, TPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU:7, TPU,<PHONE_NUMBER>4)
INFO:tensorflow:*** Available Device: _DeviceAttributes(/job:tpu_worker/replica:0/task:0/device:TPU_SYSTEM:0, TPU_SYSTEM,<PHONE_NUMBER>4)
INFO:tensorflow:Calling model_fn.
INFO:tensorflow:num_partitions = 1 partition_id = 0
INFO:tensorflow:Reading data files from gs://elec_transformer_bucket/TS/data/timeseries_synthetic_data_series10_samples100k-train*
INFO:tensorflow:partition: 0 num_data_files: 9
Traceback (most recent call last):
File "/usr/local/bin/t2t-trainer", line 6, in
exec(compile(open(file).read(), file, 'exec'))
File "/home/meshx/tfrc_scripts/tensor2tensor/tensor2tensor/bin/t2t-trainer", line 32, in
tf.app.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/app.py", line 126, in run
_sys.exit(main(argv))
File "/home/meshx/tfrc_scripts/tensor2tensor/tensor2tensor/bin/t2t-trainer", line 28, in main
t2t_trainer.main(argv)
File "/home/meshx/tfrc_scripts/tensor2tensor/tensor2tensor/bin/t2t_trainer.py", line 368, in main
execute_schedule(exp)
File "/home/meshx/tfrc_scripts/tensor2tensor/tensor2tensor/bin/t2t_trainer.py", line 315, in execute_schedule
getattr(exp, FLAGS.schedule)()
File "/home/meshx/tfrc_scripts/tensor2tensor/tensor2tensor/utils/trainer_lib.py", line 305, in continuous_train_and_eval
self._eval_spec)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/training.py", line 439, in train_and_evaluate
executor.run()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/training.py", line 518, in run
self.run_local()
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/training.py", line 650, in run_local
hooks=train_hooks)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 363, in train
loss = self._train_model(input_fn, hooks, saving_listeners)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 843, in _train_model
return self._train_model_default(input_fn, hooks, saving_listeners)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 856, in _train_model_default
features, labels, model_fn_lib.ModeKeys.TRAIN, self.config)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/estimator/estimator.py", line 831, in _call_model_fn
model_fn_results = self._model_fn(features=features, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 2025, in _model_fn
input_holders.generate_infeed_enqueue_ops_and_dequeue_fn())
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 992, in generate_infeed_enqueue_ops_and_dequeue_fn
self._invoke_input_fn_and_record_structure())
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 1055, in _invoke_input_fn_and_record_structure
host_device, host_id))
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 687, in generate_per_host_enqueue_ops_fn_for_host
inputs = _Inputs.from_input_fn(input_fn())
File "/usr/local/lib/python2.7/dist-packages/tensorflow/contrib/tpu/python/tpu/tpu_estimator.py", line 1976, in _input_fn
return input_fn(**kwargs)
File "/home/meshx/tfrc_scripts/tensor2tensor/tensor2tensor/data_generators/problem.py", line 733, in estimator_input_fn
dataset_kwargs=dataset_kwargs)
File "/home/meshx/tfrc_scripts/tensor2tensor/tensor2tensor/data_generators/problem.py", line 865, in input_fn
dataset = dataset.batch(batch_size, drop_remainder=True)
TypeError: batch() got an unexpected keyword argument 'drop_remainder'

Hi Meir Meshulam. I am using tensor2tensor to build a transformer network for time series prediction. But I encounter some problems while training and cannot fix it after searching a lot of tutorials. I wonder if you have successfully train your network and could you please help me with my problems.
There lists my training log:

I0722 16:13:18.533865<PHONE_NUMBER>94656 session_manager.py:502] Done running local_init_op.
I0722 16:13:21.954446<PHONE_NUMBER>94656 basic_session_run_hooks.py:606] Saving checkpoints for 0 into ./models/model.ckpt.
2019-07-22 16:13:25.741894: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0

The problem:
My program paused at this position, it was not processing anything but just paused here and didn't exit.
I will be appreciate if you can help me figure out the answer to this problem. Thank you!

Hi Meir Meshulam. I am using tensor2tensor to build a transformer network for time series prediction. But I encounter some problems while training and cannot fix it after searching a lot of tutorials. I wonder if you have successfully train your network and could you please help me with my problems.
There lists my training log:

I0722 16:13:18.533865<PHONE_NUMBER>94656 session_manager.py:502] Done running local_init_op.
I0722 16:13:21.954446<PHONE_NUMBER>94656 basic_session_run_hooks.py:606] Saving checkpoints for 0 into ./models/model.ckpt.
2019-07-22 16:13:25.741894: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0

The problem:
My program paused at this position, it was not processing anything but just paused here and didn't exit.
I will be appreciated if you can help me figure out the answer to this problem. Thank you!

fix merged


Add support for Windows thread-pool scheduler/io_context

The io_service class is currently a thin wrapper around Win32 IO completion-port and requires clients to manually manage their own threads to call process_events().
This can be fairly easily used to build a fixed-size thread-pool by spawning N threads and having each thread call io_service::process_events().
However, there are advantages to using the built-in Win32 thread-pool facilities to implement the thread-pool instead of manually spawning/managing your own pool of threads.
One benefit is that the OS is able to dynamically spin up more threads or shutdown idle threads as required.
Another benefit is that multiple libraries/frameworks can share the same underlying pool of threads without needing to go through the same API.
Otherwise, if your application uses, say 3 libraries, each of which create their own thread-pools, then you could end up with 3N threads being created across 3 separate thread-pools. If all of those libraries instead used the OS thread pool then a single pool of threads can be used to multiplex execution of tasks from each of those libraries.

Commit 91e9b039b25b1267e7adabd7bd8f5323e097e07a adds basic io_service that wraps IOCP.
Commit 8cf10ce184ec1602fc08bdb5abba609f84729fa5 adds some async file I/O.
Still need to add some documentation to README for this.


Fix SQLParseException when querying unknown object keys from aliased tables

Summary of the changes / Why this improves CrateDB
Fixes part of https://github.com/crate/crate/issues/14365, for SET error_on_unknown_object_key = FALSE
Noting that the failing query from the description of the bug:
WITH foo AS (SELECT 1 AS id)
SELECT *
FROM
  foo
  JOIN
  testdrive.bar AS T
ON
  foo.id = T.foo_id
WHERE
  T.tags['unknown'] IS NOT NULL;

can be reduced to:
SELECT T.tags['unknown'] FROM (SELECT 1) as foo, testdrive.bar AS T;

-- or even further to:

SELECT T.tags['unknown'] FROM (SELECT * FROM testdrive.bar) AS T;

After fix:
cr> SET error_on_unknown_object_key=FALSE;
SET OK, 0 rows affected  (0.000 sec)
cr> WITH foo AS (SELECT 1 AS id)
    SELECT *
    FROM
      foo
      JOIN
      testdrive.bar AS T
    ON
      foo.id = T.foo_id
    WHERE
      T.tags['unknown'] IS NOT NULL
    ;
+----+--------+------+
| id | foo_id | tags |
+----+--------+------+
+----+--------+------+
WITH 0 rows in set (0.004 sec) -- returns nothing instead of throwing SQLParseException

Checklist

[x] Added an entry in CHANGES.txt for user facing changes
[x] Updated documentation & sql_features table for user facing changes
[x] Touched code is covered by tests
[x] CLA is signed
[x] This does not contain breaking changes, or if it does:

It is released within a major release
It is recorded in CHANGES.txt
It was marked as deprecated in an earlier release if possible
You've thought about the consequences and other components are adapted
(E.g. AdminUI)

Would it be possible to normalize the expression containing the void reference to false/null somewhere earlier to reduce its spread across the code base?

Thanks, I will give it a try.

Could you also look into test_subscript_on_ignored_object_does_not_raise_missing_key_error - it currently uses @UseRandomizedOptimizerRules(0) because it starts raising an error if optimization rules are randomized. That seems to point to a bug as well, as the rule randomization shouldn't impact the behavior

I will handle

https://github.com/crate/crate/pull/14371#discussion_r1262735707
https://github.com/crate/crate/pull/14371#issuecomment-1649518805

as follow-ups.

Regarding: https://github.com/crate/crate/pull/14371#issuecomment-1649518805 I took a quick look, and set randomization to 1, then it fails when MergeFilterAndCollect filter is not applied with:
2023-07-26T03:46:36,498][ERROR][i.c.t.SQLTransportExecutor] [[Time-limited test]] Error executing stmt=select * from (select * from tbl) as t where obj['b'] = 10 args=null error=org.postgresql.util.PSQLException: ERROR: Couldn't create execution plan from logical plan because of: Couldn't find obj['b'] in SourceSymbols{inputs={obj=INPUT(0)}, nonDeterministicFunctions={}}:
Rename[obj] AS t (rows=0)
  └ Filter[(10 = _cast(obj['b'], 'integer'))] (rows=0)
    └ Collect[qbnatcxgkjizk.tbl | [obj] | true] (rows=unknown)

Because it tries to filter on a subcolumn that doesn't exist.

Regarding: #14371 (comment) I took a quick look, and set randomization to 1, then it fails when MergeFilterAndCollect filter is not applied with:
2023-07-26T03:46:36,498][ERROR][i.c.t.SQLTransportExecutor] [[Time-limited test]] Error executing stmt=select * from (select * from tbl) as t where obj['b'] = 10 args=null error=org.postgresql.util.PSQLException: ERROR: Couldn't create execution plan from logical plan because of: Couldn't find obj['b'] in SourceSymbols{inputs={obj=INPUT(0)}, nonDeterministicFunctions={}}:
Rename[obj] AS t (rows=0)
  └ Filter[(10 = _cast(obj['b'], 'integer'))] (rows=0)
    └ Collect[qbnatcxgkjizk.tbl | [obj] | true] (rows=unknown)

Because it tries to filter on a subcolumn that doesn't exist.

Thanks, I need to check again but my understanding is that with this PR merged, PSQLException will be resolved to ColumnUnknownException. It would be thrown when executing SubscriptObjectFunction because we can no longer know that an object is ignored.


Version management

Insights AWS demo not showing existing agent version in Update screen
Data Component Version optimization

remove version backup file


change webdir from being a constant

It should default to cwd, but allow for setting of an env variable

I think I fixed this a while ago.


Update publish.yml

This change provides ability to create a nuget package hosted at https://github.com/orgs/USACE/packages

The package successfully deployed to https://github.com/orgs/USACE/packages


5.0.3 doesn't compile

Tested on Unreal Version 5.0.3 and Texture->SetPlatformData doesn't exist for the UVolumeTexture class.
https://github.com/rdeioris/glTFRuntime/blob/b352c8c190696b7a7358d24923afc2e2b95ee06c/Source/glTFRuntime/Private/glTFRuntimeParserMaterials.cpp#L424

fixed in master. Thanks for reporting.


Add AVX512BW implementation::convert_utf8_to_utf16

I will be reviewing this PR from now on. The other PR has been reviewed. Thanks for your patience.

I'm going to resolve conflicts and push-force this branch.

Please be aware that my next goal is to port your UTF-8 validation that relies on pshufb.

Please be aware that my next goal is to port your UTF-8 validation that relies on pshufb.

My suspicion is that it would be much faster than what you have here if implemented properly. :-) And interesting in its own right!!!

Note that I have not actually proven that your approach is correct. It is possible that there might be a conceptual bug that I have not caught, but this can be handled with unit tests. (Easy enough to do.)

This is important work.

This is important work.

Thank you Daniel for so detailed review. I appreciate your hard work. I will push some fixes soon and then move to the next pieces that are waiting for integration.

I am merging it into a repository within simdutf, to be worked further.


Add boolean validation for tanzu config set feature flags

What this PR does / why we need it

Add validation for tanzu config set feature flag value to restrict to boolean true or false values.

Which issue(s) this PR fixes

Fixes #
Describe testing done for PR

Added unit tests
Manual testing

> tz config get | grep foo
> tz config set features.global.foo bar
[x] : invalid value provided only boolean true or false are accepted
> tz config set features.global.foo true
> tz config set features.global.foo false
> tz config set features.global.foo bar
[x] : invalid value provided only boolean true or false are accepted
> tz config set features.global.foo ""
[x] : invalid value provided only boolean true or false are accepted
> tz config set features.global.foo true
> tz config get | grep foo
            foo: "true"
>

Release note

Tanzu CLI will only allow boolean true or false feature flag values

Additional information
Special notes for your reviewer

For completeness let's mention that this PR is technically not a backwards-compatible change. A script could currently run tz config set features.cluster.myfeat TRUE and everything would work but now it will not be able to. Considering the scenarios, I think a small breaking change is ok but I'd like opinions. @mpanchajanya @vuil @anujc25
If we want to reduce the risk of breakage we could allow the widest, valid and consistent values. Those values must work for both APIs, so they would be true/false, TRUE/FALSE and True/False. That being said, I think true/false is enough but I'd also like opinions.

Thanks for the explanation. Yes, I think this should be fine to accept as the field was used to set a boolean so far.


Rename package to just web3

What was wrong?
The package was named web3.py which meant people would have to type pip install web3.py.  It's a nicer experience to say pip install web3
How was it fixed?
Changed the package name
Cute Animal Picture

Due to directory renaming, I recreated this commit on the master branch. Closing this.


[Masthead]: Default to the correct translation endpoint for application calling just lc/language code in the URL parameter

The problem

The cloud.ibm.com/docs application is currently loading just the language code within its ?locale= parameter (eg. https://cloud.ibm.com/docs?locale=es) where other content ecosystems like Drupal is using both lc and cc.
This is a feature that has not yet been accounted for in the Masthead component data fetching script.
Docs mentioned that altering their parameter to accept both lc and cc will requires some changes in their current translation files which they're not in the position to adjust.
Currently, the short-term solution (eg. https://github.ibm.com/webstandards/ibm-dotcom-translations/pull/427) for this issue is to define an lc JSON file for the 6 languages that the Docs app is supporting, however, we'll need to figure out a checking mechanism that pulls in the correct translation without country code/cc.

The solution

Figure out a checking mechanism that fetches the correct translation without having the country code/cc in the URL parameter.

Included in the Sept 13 Engineering Issues Review meeting agenda.

Convert to an epic.  2)  Circle back with Linda to get an estimate from the translation team regarding the availability of the needed files

@jeffchew @RobertaJHahn  Looks like this workaround (https://github.ibm.com/webstandards/ibm-dotcom-translations/pull/427) doesn't work for the Cloud Docs application (see slack thread). We might need to adjust the priority of this issue. Let me know what you both think.

@proeung We will talk about this topic in our Adopter Issues review meeting tomorrow morning, 9/16.  We have a dependency on translation files from another team, I'll update this issue when there is more information.

The Locale service change:  The locale API needs to add flixibility to only fetch the LC code  2)  The Translation service api needs to pull the corresponding translation file if only lc is provided.

Issues needed:  1 dev issue to update the services, Prod QA testing of both React & WC.

Once, the PR for this work is ready for review, please reach out to the Docs/KC team (Mark Kulube and Jenifer Schlotfeldt) to review and test the work within their application.

@RobertaJHahn @annawen1 Looks like the two issues that are associated with this EPIC have been closed. Is there anything else that we need to follow up on for this request? If not, I think we can close this issue out.

Yeah looks like we're good to go in closing this one. @RobertaJHahn?

@proeung @annawen1 I assigned to the release, updated the Roadmap dates and closed.  Thanks for the head-up.


Setup process

Why
As a users or developer onboarding to SuperDuperDB I need to have a clean and non-buggy way to install the software.
How
Go through the setup procedure through the eyes of a developer, making sure all steps run smoothly. Document this in a markdown document which we can include in the docs build.
What

[x] clean install from 0 using pip
[x] minimum working example as a notebook, which developers can execute
[x] running test suite
[ ] setting up a cluster deployment of SuperDuperDB (hard)

[ ] setting up our server (non-existent)
[ ] setting up CDC process
[ ] setting up LanceDB for vector-search use-cases
[ ] setting up Dask for scalable use-cases

Closing as most of these issues have been completed and I believe that the outstanding tasks are covered by our work on Colab and Binder (eg #557).
Please reopen if this is incorrect.


Understanding Quarkus

There is less content about Quarkus - what is Quarkus and why is it required on this project.

Quarkus and Springboot are two very popular Java frameworks today to do build Cloud Native Java applications.
The goal of this project is not to show details of those frameworks, if a Java developer lands here they will for sure know about these.


extract helper methods from lib/indent.js into its own module

it will be extremely useful for plugins to be able to increase/decrease the indent level in between tokens, so I think we should maintain these methods as a separate module to encourage code reuse.
we should not extract the whole file, only extract pure functions that are useful in different contexts (similar to what we did with rocambole-token) - we tried to maintain the indentation as a separate project before and it was a PITA to keep both projects in sync and to test everything.
see #270

Extracting functions for adding and removing indent sounds good, I could use that in my esformatter-jquery-chain plugin.

wow.. this was harder than expected.. spent the past 3h working on this: https://github.com/millermedeiros/rocambole-indent - I still plan to add the logic to align the comments before publishing v1.0.0 (maybe do it inside the sanitize method)
I ended up changing a lot in the esformatter indentation logic but I think it was for the better.. now we support negative indent levels!! - will create a pull request soon with my work in progress branch.


Example Usage Trouble

Mac OSX 10.11.3/Python 3.4.3
GoogleScraper 0.2.1
When running the function basic_usage() listed under Example Usage in README.md I encounter a problem:

No keywords to scrape for. Please provide either an keyword file (Option: --keyword-file) or specify and keyword with --keyword.
'NoneType' object has no attribute 'query'

I have tried altering the last line of core.py from:
if return_results: return scraper_search
to
if return_results: return session
as I believed this issue may be related to https://github.com/NikolaiT/GoogleScraper/issues/77, but it did not change anything as far as I can tell.

Seconded. I'm getting the exact same issue!

I also have this trouble.

I am experiencing the same issue
However, I used  keyword_file settings in my config dictionary, so I don't get "No keywords to scrape for" error. Just this one:

'NoneType' object has no attribute 'query'

Altering last line of core.py also didn't help me.

This pull request solves the issue: https://github.com/NikolaiT/GoogleScraper/pull/137
Diff makes it easy to spot how to make your code work: https://github.com/NikolaiT/GoogleScraper/pull/137/commits/da959f80c8b3fa8908b5a56cda31eac4a4225141

Actually your fix is not complete as also the other options need to be put in the first order of the dict in order to be parsed.
You can refer to the examples in the Examples folder which are up to date.


Override output size

If I have a shader like this:
float4 mainImage(VertData v_in) : TARGET {
	return float4(
		image.Sample(textureSampler, v_in.uv * float2(0.5,1)).rgb,
		image.Sample(textureSampler, v_in.uv * float2(0.5,1) + float2(0.5,0)).r
	);
}

the output should be half the size, but the shader is computing the full size, just to be resized by a transform afterwards.

Good suggestion, and probably not too hard to add. I'd just need to come up with a way to add this option without cluttering the options more than they already are.


Correction for raw affiliation CBGP, INRAE, IRD, CIRAD, Institut Agro, Univ. Montpellier, Montpellier, France.

Correction needed for raw affiliation CBGP, INRAE, IRD, CIRAD, Institut Agro, Univ. Montpellier, Montpellier, France.
raw_affiliation_name: CBGP, INRAE, IRD, CIRAD, Institut Agro, Univ. Montpellier, Montpellier, France.
new_rors: 05q3vnk25;03rnk6m14;003vg9w96;05kpkpg04;051escj72;05h7ddb14
previous_rors: 05q3vnk25;03rnk6m14;003vg9w96;05kpkpg04;051escj72
works_examples: W4393528898
contact: f747f87c82e8f271cd65b239148f3b0e:8e2d7d9b4216caafdb33123517afe925afb3 @ inrae.fr

This issue was accepted and ingested by the OpenAlex team on 2024-11-18. The new affiliations should be visible within the next 7 days.


tell more about flipped feature

can you tell me more about 'flipped feature' ?

First, flip the input image. Then extract its features and add up the two features (origined feaure+flipped feature) as the final feature representation.


Blocking behaviour of the tutorial code in Firefox

I am new to deeplearnjs and was trying out the tutorial code here: https://deeplearnjs.org/docs/tutorials/ml_beginners.html
To test it I added some extra lines to display the result to the screen, here is my full code:
document.body.innerHTML += "Welcome to JS"

import {Scalar, Graph, Tensor, SGDOptimizer, CostReduction, Session,
  ENV, NDArray,
  InCPUMemoryShuffledInputProviderBuilder} from 'deeplearn';

const graph = new Graph();
// Make a new input in the graph, called 'x', with shape [] (a Scalar).
const x: Tensor = graph.placeholder('x', []);
// Make new variables in the graph, 'a', 'b', 'c' with shape [] and random
// initial values.
const a: Tensor = graph.variable('a', Scalar.new(Math.random()));
const b: Tensor = graph.variable('b', Scalar.new(Math.random()));
const c: Tensor = graph.variable('c', Scalar.new(Math.random()));
// Make new tensors representing the output of the operations of the quadratic.
const order2: Tensor = graph.multiply(a, graph.square(x));
const order1: Tensor = graph.multiply(b, x);
const y: Tensor = graph.add(graph.add(order2, order1), c);

// When training, we need to provide a label and a cost function.
const yLabel: Tensor = graph.placeholder('y label', []);
// Provide a mean squared cost function for training. cost = (y - yLabel)^2
const cost: Tensor = graph.meanSquaredCost(y, yLabel);

// At this point the graph is set up, but has not yet been evaluated.
// **deeplearn.js** needs a Session object to evaluate a graph.
const math = ENV.math;
const session = new Session(graph, math);

// For more information on scope / track, check out the [tutorial on performance](/docs/tutorials/performance.html).
async function run() {
  await math.scope(async (keep, track) => {
  /**
   * Inference
   */
  // Now we ask the graph to evaluate (infer) and give us the result when
  // providing a value 4 for "x".
  // NOTE: "a", "b", and "c" are randomly initialized, so this will give us
  // something random.
  let result: NDArray =
  session.eval(y, [{tensor: x, data: track(Scalar.new(4))}]);
  document.body.innerHTML += "Welcome to JSHELL"
  console.log(result.shape);
  console.log('result', await result.data());
  document.body.innerHTML += await result.data()
  /**
   * Training
   */
  // Now let's learn the coefficients of this quadratic given some data.
  // To do this, we need to provide examples of x and y.
  // The values given here are for values a = 3, b = 2, c = 1, with random
  // noise added to the output so it's not a perfect fit.
  const xs: Scalar[] = [
  track(Scalar.new(0)),
  track(Scalar.new(1)),
  track(Scalar.new(2)),
  track(Scalar.new(3))
  ];
  const ys: Scalar[] = [
  track(Scalar.new(1.1)),
  track(Scalar.new(5.9)),
  track(Scalar.new(16.8)),
  track(Scalar.new(33.9))
  ];
  // When training, it's important to shuffle your data!
  const shuffledInputProviderBuilder =
  new InCPUMemoryShuffledInputProviderBuilder([xs, ys]);
  const [xProvider, yProvider] =
  shuffledInputProviderBuilder.getInputProviders();

  // Training is broken up into batches.
  const NUM_BATCHES = 100;
  const BATCH_SIZE = xs.length;
  // Before we start training, we need to provide an optimizer. This is the
  // object that is responsible for updating weights. The learning rate param
  // is a value that represents how large of a step to make when updating
  // weights. If this is too big, you may overstep and oscillate. If it is too
  // small, the model may take a long time to train.
  const LEARNING_RATE = .01;
  const optimizer = new SGDOptimizer(LEARNING_RATE);
  for (let i = 0; i < NUM_BATCHES; i++) {
    // Train takes a cost tensor to minimize; this call trains one batch and
    // returns the average cost of the batch as a Scalar.
    const costValue = session.train(
      cost,
        // Map input providers to Tensors on the graph.
        [{tensor: x, data: xProvider}, {tensor: yLabel, data: yProvider}],
        BATCH_SIZE, optimizer, CostReduction.MEAN);

   // pageReady
    // await wait(0)
    console.log('average cost: ' + await costValue.data());
  }

  // Now print the value from the trained model for x = 4, should be ~57.0.
  result = session.eval(y, [{tensor: x, data: track(Scalar.new(4))}]);
  console.log('result should be ~57.0:');
  console.log(result.shape);
  console.log(await result.data());
  document.body.innerHTML += await result.data()
});

}
run();

Note that I added several  document.body.innerHTML += SOMETHING in between the code.
The code runs as expected in Chrome. In Firefox, the console.log runs at approximately correct timing but the document content did not change until the end of the session.
Was I doing anything wrong? And what is the correct way to avoid the session blocking the UI?

I think the problem is you need to yield to the UI thread. Instead of looping over the batches with a for loop, try using a requestAnimationFrame loop, or using a setTimeout with a small interval between batches.

@cwhy did you manage to resolve the issue?
FYI, with the release of 0.5.0 we are deprecating the graph API in favor of the eager API, which is more suited to faster development and rapid prototyping, and easier debugging.

@dsmilkov
Sorry I was busy on other tasks and did not test it. Since the old API is deprecated, I will try the eager API instead.
Thanks!


Failed to init socket

Hi,
I am trying to compile and run the sample http server. However its unable to initialize the socket properly.
Could you please help as source code is not available for socket library?
ubuntu@dpdk$ sudo ./http_server
affinity to 0 core by default
EAL: Detected 2 lcore(s)
EAL: WARNING: cpu flags constant_tsc=yes nonstop_tsc=no -> using unreliable clock cycles !
USER8: LCORE[-1] anssock any lcore id 0xffffffff
USER8: LCORE[-1] Can't find ans memzone
init sock failed
USER8: LCORE[-1] socket: anssock isn't init, (nil)
socket error

you shall run ans(tcp/ip stack) process before run http_server.


Allow server-generated pushes as per SPDY spec.

SPDY spec allows server-generated pushes, in order to initiate one, we
need to first send a SYN_FRAME, followed by one or multiple data
frames.
Current decoding mechanism for server-generated SYN_FRAMES doesn't add
current Http Request with Entity to message map, therefore subsequent
data frames are being ignored.
This commit allows decoder to wait for incoming data frames and add them
to the server-originated Request.

AUTOMATED MESSAGE for ADMINS:Please verify and accept the pull request.To accept, say @netkins acceptTo build again, say @netkins buildTo whitelist the author, say @netkins whitelist

@jpinner can you check...

Just adding a bit more info: http://www.chromium.org/spdy/spdy-protocol/spdy-protocol-draft3#TOC-3.3-Server-Push-Transactions

the SYN_STREAM for the pushed resources MUST be sent prior to sending any content which could allow the client to discover the pushed resource and request it.
The server must send a HEADERS frame including the scheme/host/port headers before sending any data frames on the stream.

Spec does mention data frames, although somehow they do it in the very end of description of server-push transaction, and they mention it along the line with the headers.
BTW, this commit would / should fix subsequent Header frames too. I've only tested for data frames locally (I just don't have a need for an additional headers frame).

The Server Push part of the SPDY spec is "under-developed" but the "TL;DR" is that the pushed "request" should only contain headers -- in particular pushing of a request with a body is not defined or supported.
This implementation attempts to mirror the HTTP/2 specification for Server Push as closely as possible. In particular that means only pushes of the form:
SYN_STREAM (request headers) HEADERS (response headers) DATA* (response data)
are supported.

@jpinner but SYN_STREAM followed by HEADERS followed by DATA won't work in current implementation.
Exactly because of the current issue: the SYN_STREAM is considered to be a "final" message, the rest will be simply ignored.
If you're trying to push pretty much anything, whatever comes with SYN_STREAM is going to be given to the handler as "FullHttpRequest", and that's it. The rest of frames will because illegal state.
Could you please point me to at least some example of server push (or help out to prepare one)? I'll cook a pull request with proper comments so that others could save a bit of time on investigation.

@ifesdjeen The SYN_STREAM is considered to be the final HttpRequest. But if you look at line 265, you'll see that the HEADERS frame will become an HttpResponse and that will be added to the map if there are data frames that follow.
The result will be that upstream of this handler you should receive a FullHttpRequest followed by a FullHttpResponse, both with the same (even) Stream-ID header.

@jpinner that'd be an acceptable behaviour for me, but unfortunately it doesn't work like that right now: you only get a FullHttpRequest with an empty content() and nothing else.
Currently, DefaultFullHttpRequest consists only of two frames (SYN_STREAM followed by the DATA), there is no additional HEADERS frame inbetween.
DefaultSpdySynStreamFrame(last: false; unidirectional: false)
DefaultSpdyDataFrame(last: true)
```

Am I missing something?

@ifesdjeen What version of Netty are you running?

@ifesdjeen I think I see the issue -- the encoder is broken :(

@ifesdjeen See https://github.com/netty/netty/pull/3320

Perfect!
@jpinner Thank you so much!
I think I'll add an example for pushes and maybe a little guide on running SPDY on Netty, took me a little to start understanding where to look :)


Build next version (WIP)

Streamline, modernize code
In TypeScript 4.1, parse the selector to return the exact type
Return undefined instead of null
Use for-of internally, dropping IE11 support

This has been published as prerelease 7.0.0 on the next tag (it won't be installed by regular npm install select-dom)

Missing:

[ ] It needs to default to HTMLElement instead of Element; That likely means having to use extends/infer on the output of ParseSelector
[ ] Why are the type tests not failing?

However, the original definition of querySelector from TypeScript is returning Element, not HTMLElement.

However, the original definition of querySelector from TypeScript is returning Element, not HTMLElement.

Yeah, your module is correct, but select has always defaulted to HTMLElement because that's what the vast majority of elements are. It's just easier than having to specify <HTMLElement> every time, or in this case, div.class

I think now only missing:

[ ] https://github.com/g-plane/typed-query-selector/pull/10
[ ] https://github.com/g-plane/typed-query-selector/pull/9
[ ] Element generic support


Ability to add a lifecycle policy to an S3 bucket

Especially on versioned buckets, there is a need to be able to apply a default lifecycle policy so that items aren't kept forever.

Any thoughts on what syntax would look like, i was looking over the lifecycle parameters and its pretty open-ended
http://boto3.readthedocs.io/en/latest/reference/services/s3.html#S3.Client.put_bucket_lifecycle_configuration

@tim-elliott any thoughts on usage scenarios/example policies.

@kapilt For usage, we would like to be able to put a default lifecycle policy on any bucket that is created as or becomes versioned so that old versions won't live forever.  Another use case we would like to enforce is expiration on log buckets.  In either case i would see the policy being something like
{
  "Rules": [
    {
      "ID": "default-retention-policy",
      "Status": "Enabled",
      "Expiration": {
        "Days": 60
        "ExpiredObjectDeleteMarker": false
      },
      "NoncurrentVersionExpiration": {
          "NoncurrentDays": 60
      }
    }
  ]
}

As for syntax, for this policy it could be something like:
actions:
  - type: lifecycle
  - id: default-retention-policy
  - expire-days: 60
  - expire-obj-del-marker: false
  - noncur-expire-days: 60

And in general:
actions:
  - type: lifecycle
  # probably must-haves (though I only care about expire options):
  - id: <string>
  - prefix <string>
  - expire-days: <num-days>
  - expire-obj-del-marker: <true|false>
  - noncur-expire-days: <num-days>
  - abort-multipart-days: <num-days>
  - trans-days: <num-days>
  - trans-type: <GLACIER|STANDARD_IA>
  - non-curr-trans-days: <num-days>
  - noncurr-trans-type: <GLACIER|STANDARD_IA>
  # can live without:
  - expire-date: <yyyy-mm-dd>
  - trans-date: <yyyy-mm-dd>

Custodian shouldn't attempt to check the rationality of the policy parms, that is up to the user.  If if fails to apply it is on the user to catch it and fix it.

@tim-elliott - Should any of the fields you mentioned have defaults?
What about conditional defaults?  E.g. I am assuming that if any of the trans-* fields are supplied then we want to include the following stanza:
                'Transitions': [
                    {
                        'Date': datetime(2015, 1, 1),
                        'Days': 123,
                        'StorageClass': 'GLACIER'|'STANDARD_IA'
                    },
                ],

But what do we do it we get, say, trans-days but not either of the other two fields?  Leave those out?  Or should they have defaults in this case?

I am not the be-all for requirements, but my preference would be: if the policy does not provide sufficient information then it should fail.  Default values can be a tricky area, I think even more so with lifecycle rules, and I don't think the tool should make any assumptions in this case on behalf of users.

@tim-elliott - Ok, I will not provide any defaults, and I'll go with the approach of only including fields that are specified.  As you mentioned in your initial request, this pushes validation/rationality to the user.  We can make improvements based on feedback as people start using this feature, if necessary.  I'm traveling a bit, but I should have something for you to test this week.

@tim-elliott - the PR has a working version.  Would you like to test?  I'm still working on a unittest, but I have manually tested it successfully.
Also, should there be a corresponding delete-lifecycle action?  ( @kapilt )

merged


Key value differing for saves

I'm getting an error when I save the document without any modifications.
The only fact that I am saving it changes the snapshot and it returns as a "no match".
I am using enzyme-to-json with a enzyme.mount which is mounting:
<Provider store={store}>
    <MemoryRouter>
        <Component {...properties} />
     </MemoryRouter>
</Provider>

Component is a wrapped redux-form container:
reduxForm({
  form: 'myForm',
  validate
})(MyComponent)

The errors are:
  ● <ForgotPassword /> › render › should render correctly all

    expect(value).toMatchSnapshot()

    Received value does not match stored snapshot 1.

    - Snapshot
    + Received

    @@ -37,11 +37,11 @@
                 "canGo": [Function],
                 "createHref": [Function],
                 "entries": Array [
                   Object {
                     "hash": "",
    -                "key": "yhrazi",
    +                "key": "wegq0d",
                     "pathname": "/",
                     "search": "",
                     "state": undefined,
                   },
                 ],
    @@ -51,11 +51,11 @@
                 "index": 0,
                 "length": 1,
                 "listen": [Function],
                 "location": Object {
                   "hash": "",
    -              "key": "yhrazi",
    +              "key": "wegq0d",
                   "pathname": "/",
                   "search": "",
                   "state": undefined,
                 },
                 "push": [Function],

      at Object.<anonymous> (tests/renderers/authentication/forgotPassword.tests.js:71:52)
      at Promise.resolve.then.el (node_modules/p-map/index.js:42:16)
      at process._tickCallback (internal/process/next_tick.js:109:7)

Am I doing something wrong?

Hi @jpenna,
Thanks for raising the issue, I'll have a look as soon as I can! Sorry for the delay.

It might be due to a key randomly generated by redux or redux-form but it doesn't look like a bug with enzyme-to-json, I'll close this for now, if you need help, please create a small repo to reproduce the issue.


[feature-request] add keyword command

Create a command to easily add a new keyword.
If text is already selected use this selection as keyword.

Could we consider the delete keyword command? In certain scenarios, we may highlight multiple keywords for temporary reading, but later we don't need these keywords. Therefore, the abilities to quickly add and remove highlighted keywords  will be helpful.


Minimal changes to fix bugs in square_neighbourhooding.

Minimal changes required to get rid of < 0.0 and > 1.0 values
in square neighbourhooding.
Reference issue if exists
Testing:

[X] Ran tests and they passed OK

As a general comment, we only seem to have one test that takes in a separate masked cube and it is not in the Test_run class. It might be good to have at least one more as this is the primary way will be using this code.

The acceptance criteria say to remove clipping from the CLIs. Are these changes enough to remove the clipping? If so we should changes the CLIs.


Bad Chunk Error After Creating Pipeline on Beta 4

On a clean Beta 4 installation, I created one repo and one pipeline.  The pipeline pod immediately failed to start and went into a "crash backoff loop" of restarts.  User log shows a bad chunk error:
error getting pipelineInfo: could not retrieve pipeline spec file from PFS for pipeline 'benchmarking': bad chunk. HAVE:<PHONE_NUMBER>3163303236653534336232653861623265623036303939646161316431653564663437373738663737383766616162343563646631326665336138 WANT:<PHONE_NUMBER>6662386266653864316165366231623630303338326235643332633064383965343036366466333233646232636334663562316562646530656266

I tried deleting and recreating the pipeline without success.  This is the same pipeline that I have been using for my performance testing all along, so it should just work.
storage.log
user.log
AB#12

Here are the pachd logs as well:
pachd.log

This morning I tried deploying a completely different pipeline, and got the same result.

The pipeline I'm referring to in my previous comment was one of the customer pipelines I've been testing with called "cron_daily". After it failed in the same way as the pipeline I initially tried creating yesterday. I decided to try to uninstall and reinstall Pachyderm to see if that had any effect on the issue.  When I did, however, I forgot to delete the cron_daily pipeline first. So, after reinstall, that pipeline tried to start and failed in the same way again.  However, there was also a new problem that surfaced, specifically pachd started failing and restarting as well, with segmentation faults. I have opened #6641 to track that issue.

This is reproducible on Hub as well:
error getting pipelineInfo: could not retrieve pipeline spec file from PFS for pipeline 'benchmarking': bad chunk. HAVE:<PHONE_NUMBER>3163303236653534336232653861623265623036303939646161316431653564663437373738663737383766616162343563646631326665336138 WANT:<PHONE_NUMBER>3461323032313737343739366137643536343864646264326637366639346234353865656365306433366162353339613263343636326666316438

This should be addressed by: #6651. Feel free to reopen if it is not.

Confirmed this is working on Beta 5.


Use poetry for dependencies in ci

We are failing to run lint/tests here https://github.com/vulncheck-oss/sdk-python/actions/runs/11634137608/job/32400758857?pr=28
I think updating the workflow to use poetry install ought to get us in a better state

This is actually deviating from the original github actions workflow that was generated - which is causing more problems than it's fixing. Closing this as won't do


Oriscus goes up with each character entered

Copy and paste the following code in the exsurge test page and then continue the melody with anything.
(c2) Sal(f!gwh/io)ve,(h)

Result: oriscus goes up with each entered character:

This seems to be fixed on Benjamin Bloomfield's react native version


Use git directly instead of actions/checkout on Windows

The GitHub-provided actions/checkout action is for some reason
unusably slow on the large managed Windows runners. We assumed this was
because of some tricky IO issue or something, but I decide to just try
directly using git commands to see and lo the checkout time goes from
10 minutes to 1.5 :rocket:
With the caching improvements from
https://github.com/openxla/iree/pull/13183, this gets the Windows build
down under 10 minutes, which means we can run it on presubmit (left for
a future PR).
Part of https://github.com/openxla/iree/issues/11009
Tested:
Enabled this workflow on push to my branch:
https://github.com/openxla/iree/actions/runs/4750681034/jobs/8439091687
skip-ci: this only affects the Windows job, which isn't run on presubmit

Still seeing high variance, unfortunately. This might be a net improvement though.

checkout in 4m30s: https://github.com/openxla/iree/actions/runs/4756664881/jobs/8452525355
checkout in 6m30s: https://github.com/openxla/iree/actions/runs/4757392882/jobs/8454160397

It's getting monotonically slower (⊙ _◎)


Productionize IEmailSender interface

We need to refactor the interface that we had on the template (now on the UI package) into a shape that we like, and find the right place for it. (probably the M.A.I package).
My proposal
public interface IEmailSender
{
    Task SendAsync(Email email);
}

public class Email
{
    public IList<string> To { get; }
    public string Subject { get; set; }
    public string Body { get; set; }
}

The idea of using a class is to allow for adding new members if necessary in the future without causing breaking changes.
/cc: @HaoK

Following up on this. I'm ok with this living on the UI package, so the work here is to do the following:

Update the interface to look like the snippet below. (This interface as called out above is not a general purpose email sending interface but an adapter for the UI). The only point of having a class for email is in case we need to extend it in the future, hence the DTO.

public interface IEmailSender
{
    Task SendAsync(Email email);
}

public class Email
{
    public IList<string> To { get; set; }
    public string Subject { get; set; }
    public string Body { get; set; }
}

Change the usage of IEmailSender in the UI to make it optional (Injecting IEnumerable instead of IEmailSender).
Get rid of the dummy EmailSender implementation.

@HaoK Does this sound good to you?

If we change the interface we should probably change the name just to avoid conflicts with existing IEmailSender classes, maybe just add an UI IUIEmailSender and UIEmail?
Is it really better to make it optional instead of a default no-op?  What happens when there's no email sender, do we stop rendering ForgotPassword links, or just have it throw?  We'd have to probably throw if requireEmailConfirmation = true and there is no email sender.  I believe the idea behind making email sending part of the flows in templates for 2.0 was that we didn't think it was realistic for a site not to have an email sender...

I'm moving this out to 2.2

I think @javiercn was planning on doing something about this in rc1

@blowdart Id rather address this for 2.1 just to make sure we have something that doesn't corner us in the future.

Talk to @mkArtakMSFT - I feel this has been left too late now

One cheap thing you could do for future proofing in 2.1 is just to make it not an interface... so you can revisit things later
public class EmailSender {
   Send(whatever)
}

Lets you just always register a no-op one, and they can plug in a real one if they want, and you aren't rushed into defining the IEmailSender interface

I also suggest something really specific like DefaultUIEmailSender

@HaoK I would just change it to what we discussed above. Switch from parameters to object is cheap, swiching to a class is also cheap, but then you still have to live with the old methods.


What should I put in data parameter inside the response with already solved hCaptcha?

When I'm requesting page with requests library I receive this respoce from a server:
{'captcha_key': ['You need to update your app to join this server.'],  'captcha_sitekey': 'a9b5fb07-92ff-493f-86fe-352a2803b3df',  'captcha_service': 'hcaptcha',  'captcha_rqdata': 'OccZocPS0udA/9MOyn4qvfLuti5qTqBYoyNljA7F5cT8JBJrhBWRhw0TEDEFDTOOHMnE6jvE2WzhbGjvDN4hk9fxZkcvQ7Bgjjd/QEJEXReGJWyyxhB0HFSjFjRjn6H23PJjdTyRWpDrTjhV6l/qDb4O14C9XiiXfKF2hQgh',  'captcha_rqtoken': 'IlZFamJXMkdPZ1BiMTJsYlJhQ2NMYlFOaHJTWWdtUjl0NjBhQ0cyZTFCWmhtd01xc0pYeCtMMHhENXNKcmpWRHJPN0FrM2c9PWk5Zk5NUmRRdTNjdFRTTDQi.Yn7Hbw.CNj-_pg2pNmt47a-9OG8PyevmHA'}
then I'm using twocaptcha for solving this captcha in that manner:
recaptcha_answer = solver.hcaptcha(sitekey="a9b5fb07-92ff-493f-86fe-352a2803b3df",                                        url=f'https://discord.com/api/v9/invites/{my_invite}',                                        defaultTimeout=600)
and this function return captchaId and code.
The question is where and what should I put in data parameter if captcha is invisible? Cause If I requesting this page again with just a code as captcha_key server response for solving captcha again. I think I just give the wrong payload.

I'm not 100% sure but For the url you'll just have to use https://discord.com/channels/@me
And you'll have to pass the rq_data in the data parameter. I suppose you're also writing in discord.py-self. I'm also working with this module so if I have it figured out I'll get back to you.


Add a Dockerfile for easy builds

My Mac doesn't meet the dependencies for building this. I'm getting some complaint about my version of Python. I don't really want to mod my Mac for every project's own unique needs these days so I use Dockerfiles as build machines so the build can happen in a container. This is is nice for documenting the requirements for building, documenting the the process for building, and lastly for consistency of builds not to mention avoiding the "Oh shit we lost Bob's laptop, now we can't compile, we have to shut the project down" problem.
Now the only dependency is Docker so we can do a build like...
$ git clone https://github.com/zeit/hyperterm.git
$ cd hyperterm
$ docker build -t hyperterm .
$ docker run -v $(pwd)/dist:/hyperterm/dist hyperterm

The result is the same. You'll find a dist folder in your hyperterm directory on your host machine with the builds that happened inside the container.
... of course, the result of this still complains about missing Python so the build fails. Can someone solve this? I don't know what version of Python this project requires. Bob does.

I have Python 2.7.10 on my OS X machine, FYI

Why would you want to build it as a OS X user using Docker?
All you get is the Unix-binary you can only use in a VM or in a container using xhyve (Docker for Mac)

I don't understand the python problem. Where are we using python? Is it one of our deps?

@dj-hedgehog I think I see what you are saying. Is it "If you build hyperterm in a Linux environment, it will only result in a build of hyperterm that works for Linux ". Is that right? That's not the case when creating executables for platforms using tools like Cordova. Is it always the case that with Electron you can only build apps for the platform you are building from?

Our build process works on Linux, Windows and OSX.

@TooTallNate Looks like I'm on Python 3.5.1.
 ⚡ python --version
Python 3.5.1 :: Anaconda 2.4.1 (x86_64)

@rauchg Here's a log containing a bunch of errors around python when I try npm install.
log.txt

Our build process works on Linux, Windows and OSX.

The question is not "Can we perform a build on X platform?" but more like "Can we do a build on X platform that produces an executable on Y platform?" In this case it's "Can we do a build in Ubuntu that produces and executable for Mac?" If so, then we can reliably build Hyperterm for Mac from a Mac that has Docker for Mac installed.

@rjsteinert  Seem pretty much an issue with support of node-gyp.
Coming from node-gyp:
On Mac OS X: python (v2.7 recommended, v3.x.x is not supported)
What is your node version and npm version ?
Take a look at https://github.com/nodejs/node-gyp/issues/746

@rjsteinert Python 3 isn't supported by Node.js (through gyp). I wouldn't necessarily call this a hyperterm-related issue seeing how you will run into the same problem on any system using Python 3 and Node.js. There's "somewhat" progress here but I don't think one should expect py3 support in gyp anytime soon.

Woohoo! This works now as described in my change to the README. Only problem is, as @dj-hedgehog alluded to, all I have generated is an executable for Linux when I'm ultimately trying to generate an executable for Mac. So this is a reliable way for generating the Linux version of Hyperterm on either Mac or Linux without having to modify your python version but not yet a way to reliably generate the Mac version.
As I mentioned before, tools like Cordova allow you to compile for more than one "platform" as they call it. I wonder if we can do the same so that your Linux container can produce the Mac.app.

@rjsteinert, does this provide any insight for you?
https://github.com/electron-userland/electron-builder/wiki/Multi-Platform-Build

Possible to try this? https://github.com/electron-userland/electron-packager . I am not fully successfull with it however, the build works perfectly (I can build from linux docker container for macOS) however when I try to run it, I get this.

I'm guessing this has to do with hyperterm being dependent on the system npm instead of using its own internal npm.
If someone else gets this to work, however it may be, using Docker, please comment here :)

I think this is a lot of work for limited effect. Like it was mentioned, this only gets you a Linux build. The only way to get all the builds right is to rely on the travis matrix. I appreciate the work, but ultimately I'd like one less thing to maintain.


lumi.curtain.hmcn02 (Xiaomi BLE Curtain Driver E1) did not recognizing

I see that curtain driver is in supported devices list https://github.com/merdok/homebridge-miot/blob/main/supported_devices.md
But anyway it doesn't showing in devices list. Hub is connected.

How does your config look like?

@merdok https://drive.google.com/file/d/1HxnbvaWwNR_CYoMuek_-cm0MaUTCuCn1/view?usp=drivesdk

I do not see it in your config. You have to specify the token and ip of the gateway, but the model and deviceId needs to be that of the BLE device.

Thank you for your help @merdok, it's worked! I am so happy.


Can't load model

RT

Hi @Xiaohui9607, the latest version with PR #41 adds this. You can install the package from source:
git clone https://github.com/xuyxu/Ensemble-Pytorch.git
cd Ensemble-Pytorch
pip install .

no, it doesn't, you need to "fit" a model before you can load the checkpoint:
fail:
`
model = VotingClassifier(estimator=model_wrapper,  # your deep learning model
n_estimators=10)
{Ensemble_Method_Name}{Base_Estimator_Name}{n_estimators}
filename = "{}{}{}ckpt.pth".format(type(model).name,
model.base_estimator.name,
model.n_estimators)
io.load(model, "/home/golf/Downloads")
save_dir = os.path.join("/home/golf/Downloads", filename)`
success:
`model = VotingClassifier(estimator=model_wrapper,  # your deep learning model
n_estimators=10)
import os
{Ensemble_Method_Name}{Base_Estimator_Name}{n_estimators}
filename = "{}{}{}ckpt.pth".format(type(model).name,
model.base_estimator.name,
model.n_estimators)
model.set_optimizer("Adam",
lr=learning_rate,
weight_decay=weight_decay)
model.fit(train_loader,
epochs=1)
io.load(model, "/home/golf/Downloads")`

Thanks, I will fix this ;-)
If you want to use the model on the fly, could you check if methods like pickle.dump help?

@all-contributors please add @Xiaohui9607  for bug

The problem is that torchensemble does not register all base estimators into the ensemble during the instantiation. Instead, each of them will be inserted into the ensemble when calling the fit method. As a result, if we want to reload params into a newly-declared model, all keys in the state_dict are missing.
Thanks for your report, we will fix this.


User management in replicasets / sharding

Source: https://github.com/edelight/chef-mongodb/pull/344

would it be possible to at least pull this: https://github.com/chef-brigade/mongodb-cookbook/commit/a840e843d628c8ee9e751551360c8baed584bb08
Currently chef fails on this when run on a secondary node with authentication enabled

Squashed, rebased, and fixed rubocop


[Bug]: Mongo - Generate CRUD is failing with Empty Table Data

Is there an existing issue for this?

[X] I have searched the existing issues

Description

Steps To Reproduce

Connect to a Mongo Data source
Verify the collections has data
Generate page with this Data source
Observe that table has no data displayed
Expected: Table should be generated per collection

Public Sample App
No response
Version
Cloud/Release v1.6.17

Tried this on release build and here are the observations:

First time when I try to reproduce this issue, I get the following behavior -
https://www.loom.com/share/3702339d0621461fa7059245da9a5924
Though the table data is populated, an error still pops up - "The action findQuery has failed"

On retrials of the same steps, the table data gets populated without any error -
https://www.loom.com/share/f2a6b7d0187d47f98f48bf992b02c843

After discussion with @abhvsn, raised a separate bug to track the above observation - https://github.com/appsmithorg/appsmith/issues/12329
Closing this issue as the base issue of empty data has been fixed. Data is now getting populated.