So badly openaq  tutorail for use openaq python package,is rubbish and awful !

Description
oh my god ,first use so badly tutorial for  this ,and even I don't find how to get the air quality data  example like pandas dataframe.
why ？ is your team have no time to write ,and the v3 api is can not safe suit the v2 v1. baddly experience
Example Code
No response
Python, openaq & OS Version
s

Contributions to improve the package as well-formed bug reports or feature requests are welcome. Note the package is still in a pre 1.0.0 release and under active development.
We encourage you to be constructive in your feedback and follow our Code of Conduct, which you can find here: Code of Conduct
The Code of Conduct outlines our commitment to a welcoming and respectful environment for everyone in the OpenAQ community. It ensures we can all learn and collaborate effectively.

Contributions to improve the package as well-formed bug reports or feature requests are welcome. Note the package is still in a pre 1.0.0 release and under active development.
We encourage you to be constructive in your feedback and follow our Code of Conduct, which you can find here: Code of Conduct
The Code of Conduct outlines our commitment to a welcoming and respectful environment for everyone in the OpenAQ community. It ensures we can all learn and collaborate effectively.

I am feel sorry to report this.but  I eagerly  need the aqi data, so  use waqi


[Serialization] Handle XREFs to generic subscripts

Found while compiling another project.

@swift-ci Please test


EMG Filtering and Threads

Included thread based functions for EMG filtering data
Made the code event driven. Added makefile for EMG filtering

I have added build scripts as well for building the project from scratch


[type:feat]  add brpc and http Integration testing cases

Make sure that:

[ ] You have read the contribution guidelines.
[ ] You submit test cases (unit or integration tests) that back your changes.
[ ] Your local test passed ./mvnw clean install -Dmaven.javadoc.skip=true.

Codecov Report

Merging #4731 (5ce2864) into master (3cb2deb) will decrease coverage by 0.02%.
The diff coverage is 0.00%.

@@             Coverage Diff              @@
##             master    #4731      +/-   ##
============================================
- Coverage     66.18%   66.17%   -0.02%
+ Complexity     8004     8002       -2
============================================
  Files          1103     1103
  Lines         32157    32157
  Branches       2908     2908
============================================
- Hits          21284    21280       -4
- Misses         9179     9183       +4
  Partials       1694     1694

Impacted Files
Coverage Δ

...u/admin/listener/apollo/ApolloDataChangedInit.java
0.00% <0.00%> (ø)

... and 2 files with indirect coverage changes
:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


Update base images to ECR public

Issue #, if available: https://github.com/aws-controllers-k8s/community/issues/925
Description of changes:
Update the base and builder image for the continuous deployment Dockerfiles
By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.

/approve


convert unicode to str in JDL before submit to Condor

fixes #7367 @amaltaro, @hufnagel, Alan, Dirk please review

Looks good to me.


Error installing neuralcoref during docker build: Variables cannot be declared with 'cpdef'. Use 'cdef' instead.

Hello,
I am trying to build the docker container for Elevant. I have cloned the repo and run docker build -t elevant ..
This is on MacOS.
The output is below.
`docker build -t elevant .
[+] Building 83.3s (11/28)                                                                                docker:desktop-linux
=> [internal] load build definition from Dockerfile                                                                                0.0s
=> => transferring dockerfile: 1.54kB                                                                                0.0s
=> [internal] load .dockerignore                                                                                0.0s
=> => transferring context: 259B                                                                                0.0s
=> [internal] load metadata for docker.io/library/ubuntu:20.04                                                                                1.9s
=> [internal] load build context                                                                                0.1s
=> => transferring context: 1.95MB                                                                                0.0s
=> [ 1/24] FROM docker.io/library/ubuntu:20.04@sha256:ed4a42283d9943135ed87d4ee34e542f7f5ad9ecf2f244870e23122f703f91c2                                                               3.7s
=> => resolve docker.io/library/ubuntu:20.04@sha256:ed4a42283d9943135ed87d4ee34e542f7f5ad9ecf2f244870e23122f703f91c2                                                                 0.0s
=> => sha256:a80d11b67ef30474bcccab048020ee25aee659c4caaca70794867deba5d392b6 424B / 424B                                                                                0.0s
=> => sha256:0341906bdafc976cd73b05ea0e3df2e4884c6b6816197a2ffbd2367061c19acf 2.32kB / 2.32kB                                                                                0.0s
=> => sha256:915eebb74587f0e5d3919cb77720c143be9a85a8d2d5cd44675d84c8c3a2b74a 25.97MB / 25.97MB                                                                                2.8s
=> => sha256:ed4a42283d9943135ed87d4ee34e542f7f5ad9ecf2f244870e23122f703f91c2 1.13kB / 1.13kB                                                                                0.0s
=> => extracting sha256:915eebb74587f0e5d3919cb77720c143be9a85a8d2d5cd44675d84c8c3a2b74a                                                                                0.7s
=> [ 2/24] WORKDIR /home/                                                                                0.1s
=> [ 3/24] RUN apt-get update                                                                                7.6s
=> [ 4/24] RUN apt-get install -y python3 python3-pip git wget vim curl python3-gdbm                                                                                45.0s
=> [ 5/24] RUN git clone https://github.com/huggingface/neuralcoref.git                                                                                13.2s
=> [ 6/24] RUN python3 -m pip install -r neuralcoref/requirements.txt                                                                                10.7s
=> ERROR [ 7/24] RUN python3 -m pip install -e neuralcoref                                                                                1.1s

[ 7/24] RUN python3 -m pip install -e neuralcoref:
0.654 Obtaining file:///home/neuralcoref
1.082     ERROR: Command errored out with exit status 1:
1.082      command: /usr/bin/python3 -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/home/neuralcoref/setup.py'"'"'; file='"'"'/home/neuralcoref/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(file);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' egg_info
1.082          cwd: /home/neuralcoref/
1.082     Complete output (39 lines):
1.082     /usr/local/lib/python3.8/dist-packages/Cython/Compiler/Main.py:381: FutureWarning: Cython directive 'language_level' not set, using '3str' for now (Py3). This has changed from earlier releases! File: /home/neuralcoref/neuralcoref/neuralcoref.pxd
1.082       tree = Parsing.p_module(s, pxd, full_module_name)
1.082
1.082     Error compiling Cython file:
1.082     ------------------------------------------------------------
1.082     ...
1.082         int length
1.082
1.082
1.082     cdef class Vocab:
1.082         cdef Pool mem
1.082         cpdef readonly StringStore strings
1.082               ^
1.082     ------------------------------------------------------------
1.082
1.082     /usr/local/lib/python3.8/dist-packages/spacy/vocab.pxd:29:10: Variables cannot be declared with 'cpdef'. Use 'cdef' instead.
1.082     Processing neuralcoref.pyx
1.082     Traceback (most recent call last):
1.082       File "/home/neuralcoref/bin/cythonize.py", line 168, in
1.082         run(args.root)
1.082       File "/home/neuralcoref/bin/cythonize.py", line 157, in run
1.082         process(base, filename, db)
1.082       File "/home/neuralcoref/bin/cythonize.py", line 123, in process
1.082         preserve_cwd(base, process_pyx, root + ".pyx", root + ".cpp")
1.082       File "/home/neuralcoref/bin/cythonize.py", line 86, in preserve_cwd
1.082         func(*args)
1.082       File "/home/neuralcoref/bin/cythonize.py", line 62, in process_pyx
1.082         raise Exception("Cython failed")
1.082     Exception: Cython failed
1.082     Traceback (most recent call last):
1.082       File "", line 1, in
1.082       File "/home/neuralcoref/setup.py", line 239, in
1.082         setup_package()
1.082       File "/home/neuralcoref/setup.py", line 174, in setup_package
1.082         generate_cython(root, 'neuralcoref')
1.082       File "/home/neuralcoref/setup.py", line 163, in generate_cython
1.082         raise RuntimeError('Running cythonize failed')
1.082     RuntimeError: Running cythonize failed
1.082     Cythonizing sources
1.082     ----------------------------------------
1.083 ERROR: Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.

Dockerfile:8
6 |     RUN git clone https://github.com/huggingface/neuralcoref.git
7 |     RUN python3 -m pip install -r neuralcoref/requirements.txt
8 | >>> RUN python3 -m pip install -e neuralcoref
9 |     COPY requirements.txt requirements.txt
10 |     RUN python3 -m pip install -r requirements.txt
ERROR: failed to solve: process "/bin/sh -c python3 -m pip install -e neuralcoref" did not complete successfully: exit code: 1`

It looks like this is related to this issue: https://github.com/huggingface/neuralcoref/issues/357

It appears that neuralcoref is old (last release 2019) and won't work with more recent versions of Python. Is neuralcoref even necessary if you aren't using coref?

Sorry for the late reply! I will look into it, but in the meantime you can simply remove the instructions for installing neuralcoref from the Dockerfile (should be just lines 6, 7 and 8). As you wrote, neuralcoref is not necessary if you're not planning on using coreference resolution.


tsconfig.json parsing errors aren't helpful

create a tsconfig.json file with a typo in it (invalid json)
run tsc
error TS6050: Unable to open file 'tsconfig.json'.
If I can't spot the typo I have to paste it into a json validator to find it. Can it give a nice error, eg., Sublime gives "Unexpected character, expected a comma or closing bracket in Packages\User\Preferences.sublime-settings:56:2"

readConfigFile currently uses undefined return value to signal either an non-existent file or an malformed one. We will need to change that, and show the error message from the exception thrown by JSON.parse

What do you prefer here? Just propagate the error message with a throw statement? So the consumers should try/catch themselves or do you prefer an object with a error (if any) and a result?

The only parallel i could think of is CompilerHost.getSourceFile, it takes an optional onError property that would report the error. so may be that is a better way to go.

+1

One thing to note is that the intrinsic JSON object doesn't give the most useful information at this time.

JSON.parse("{ a : true }"

gives me

SyntaxError: Unexpected token a

Which is significantly better than silently skipping the file.

It's better, but not having the line/col is a pretty big limitation.

I think if we want to be fancy, we can parse it ourselves :D, in theory you can use the scanner/parser. not sure if the cost justifies the value though.

Well we would be able to give the line/col for the file references, this would help us give better errors for those at a later stage.

@mhegazy This can be closed, parsing it with ts's parser is what happens now afaik.
export function parseConfigFileTextToJson(fileName: string, jsonText: string): { config?: any; error?: Diagnostic } {
    const jsonSourceFile = parseJsonText(fileName, jsonText);


Leverage: (HAL-08) PANIC IS USED FOR ERROR HANDLING

Summary
Several instances of the panic function were identified in the codebase. They appear to be used to handle errors. This can cause potential issues, as invoking a panic can cause the program to halt execution and crash in some cases. This in turn can negatively impact the availability of the software for users
Problem Definition

https://github.com/umee-network/umee/blob/rafilx/umeed-cosmwasmd/x/leverage/abci.go#L11-21
https://github.com/umee-network/umee/blob/rafilx/umeed-cosmwasmd/x/leverage/keeper/keeper.go#L64-66

Proposal
Instead of using panics, custom errors should be defined and handled according to the Cosmos best practices.
For Admin Use

[ ] Not duplicate issue
[ ] Appropriate labels applied
[ ] Appropriate contributors tagged
[ ] Contributor assigned/self-assigned

All our instances of panic are

Store unmarshal fail on getter ("should never happen" - similar to SDK's approach to bank.GetBalance)
EndBlocker (which MUST halt the chain on error)


panic: interface conversion: interface {} is nil, not string

Describe the bug
Running terraform plan results in panic. This seems like a recent regression since the same TF resources we're previously built correctly on same version (0.3.16).
Error message
Stack trace from the terraform-provider-dbtcloud_v0.3.16 plugin:

panic: interface conversion: interface {} is nil, not string

goroutine 484 [running]:
github.com/dbt-labs/terraform-provider-dbtcloud/pkg/sdkv2/resources.resourceConnectionRead({0x104ccc498?, 0x1400091c510?}, 0x140005b0280, {0x104cb5420?, 0x140004b2800})
	github.com/dbt-labs/terraform-provider-dbtcloud/pkg/sdkv2/resources/connection.go:309 +0x126c
github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*Resource).read(0x140002da8c0, {0x104ccc498, 0x1400091c510}, 0xd?, {0x104cb5420, 0x140004b2800})
	github.com/hashicorp/terraform-plugin-sdk/v2@v2.34.0/helper/schema/resource.go:823 +0xe8
github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*Resource).RefreshWithoutUpgrade(0x140002da8c0, {0x104ccc498, 0x1400091c510}, 0x14000826340, {0x104cb5420, 0x140004b2800})
	github.com/hashicorp/terraform-plugin-sdk/v2@v2.34.0/helper/schema/resource.go:1117 +0x430
github.com/hashicorp/terraform-plugin-sdk/v2/helper/schema.(*GRPCProviderServer).ReadResource(0x1400000d890, {0x104ccc498?, 0x1400091c3c0?}, 0x1400068e880)
	github.com/hashicorp/terraform-plugin-sdk/v2@v2.34.0/helper/schema/grpc_provider.go:708 +0x5ac
github.com/hashicorp/terraform-plugin-mux/tf5to6server.v5tov6Server.ReadResource({{0x104cd8740?, 0x1400000d890?}}, {0x104ccc498?, 0x1400091c3c0?}, 0x1400068e4c0?)
	github.com/hashicorp/terraform-plugin-mux@v0.15.0/tf5to6server/tf5to6server.go:215 +0x228
github.com/hashicorp/terraform-plugin-mux/tf6muxserver.(*muxServer).ReadResource(0x104ccc4d0?, {0x104ccc498?, 0x1400058fec0?}, 0x1400068e4c0)
	github.com/hashicorp/terraform-plugin-mux@v0.15.0/tf6muxserver/mux_server_ReadResource.go:35 +0x184
github.com/hashicorp/terraform-plugin-go/tfprotov6/tf6server.(*server).ReadResource(0x140002595e0, {0x104ccc498?, 0x1400058e900?}, 0x140002522a0)
	github.com/hashicorp/terraform-plugin-go@v0.23.0/tfprotov6/tf6server/server.go:784 +0x224
github.com/hashicorp/terraform-plugin-go/tfprotov6/internal/tfplugin6._Provider_ReadResource_Handler({0x104c8e7e0?, 0x140002595e0}, {0x104ccc498, 0x1400058e900}, 0x140005b0000, 0x0)
	github.com/hashicorp/terraform-plugin-go@v0.23.0/tfprotov6/internal/tfplugin6/tfplugin6_grpc.pb.go:482 +0x164
google.golang.org/grpc.(*Server).processUnaryRPC(0x14000189000, {0x104ccc498, 0x1400058e2d0}, {0x104cd3950, 0x140004f4000}, 0x140005767e0, 0x1400037b380, 0x10531b868, 0x0)
	google.golang.org/grpc@v1.63.2/server.go:1369 +0xba0
google.golang.org/grpc.(*Server).handleStream(0x14000189000, {0x104cd3950, 0x140004f4000}, 0x140005767e0)
	google.golang.org/grpc@v1.63.2/server.go:1780 +0xc80
google.golang.org/grpc.(*Server).serveStreams.func2.1()
	google.golang.org/grpc@v1.63.2/server.go:1019 +0x8c
created by google.golang.org/grpc.(*Server).serveStreams.func2 in goroutine 23
	google.golang.org/grpc@v1.63.2/server.go:1030 +0x150

Error: The terraform-provider-dbtcloud_v0.3.16 plugin crashed!

This is always indicative of a bug within the plugin. It would be immensely
helpful if you could report the crash with the plugin's maintainers so that it
can be fixed. The output above should help diagnose the issue.

Resource configuration
terraform {
  required_providers {
    dbtcloud = {
      source  = "dbt-labs/dbtcloud"
      version = ">= 0.3.16"
    }
  }
}

resource "dbtcloud_project" "this" {
  dbt_project_subdirectory = "dbt/${var.project_name}"
  name                     = var.project_name
}

resource "dbtcloud_global_connection" "this" {
  databricks = {
    catalog   = var.databricks_catalog
    host      = var.databricks_host
    http_path = var.databricks_http_path
  }
  name = "Databricks - ${var.project_name}"
}

resource "dbtcloud_connection" "this" {
  catalog    = var.databricks_catalog
  database   = "" // currenyly need to be empty for databricks
  host_name  = var.databricks_host
  http_path  = var.databricks_http_path
  name       = "Databricks - ${var.project_name}"
  project_id = dbtcloud_project.this.id
  type       = "adapter"
}

resource "dbtcloud_databricks_credential" "this" {
  adapter_id   = dbtcloud_connection.this.adapter_id
  adapter_type = "databricks"
  project_id   = dbtcloud_project.this.id
  schema       = var.schema
  target_name  = "default"
  token        = var.databricks_token
}

resource "dbtcloud_environment" "dev_env" {
  connection_id     = dbtcloud_global_connection.this.id
  dbt_version       = "versionless"
  name              = "Development"
  project_id        = dbtcloud_project.this.id
  type              = "development"
  use_custom_branch = false
}

resource "dbtcloud_environment" "ci_env" {
  connection_id     = dbtcloud_global_connection.this.id
  credential_id     = dbtcloud_databricks_credential.this.credential_id
  dbt_version       = "versionless"
  name              = "CI"
  project_id        = dbtcloud_project.this.id
  type              = "deployment"
  use_custom_branch = false
}

resource "dbtcloud_environment" "prod_env" {
  connection_id     = dbtcloud_global_connection.this.id
  credential_id     = dbtcloud_databricks_credential.this.credential_id
  dbt_version       = "versionless"
  deployment_type   = "production"
  name              = "Production"
  project_id        = dbtcloud_project.this.id
  type              = "deployment"
  use_custom_branch = false
}

resource "dbtcloud_repository" "this" {
  git_clone_strategy        = "github_app"
  github_installation_id    = local.github_installation_id
  project_id                = dbtcloud_project.this.id
  remote_url                = var.git_repo_remote_url
}

resource "dbtcloud_project_repository" "this" {
  project_id    = dbtcloud_project.this.id
  repository_id = dbtcloud_repository.this.repository_id
}

resource "dbtcloud_job" "ci_job" {
  environment_id       = dbtcloud_environment.ci_env.environment_id
  execute_steps        = ["dbt build"]
  generate_docs        = false
  name                 = "CI"
  num_threads          = 4
  project_id           = dbtcloud_project.this.id
  run_generate_sources = false
  target_name          = "CI"
  timeout_seconds      = 0
  triggers = {
    git_provider_webhook = false
    github_webhook       = true
    on_merge             = false
    schedule             = false
  }
  triggers_on_draft_pr = true
}

resource "dbtcloud_job" "prod_merge_job" {
  environment_id       = dbtcloud_environment.prod_env.environment_id
  execute_steps        = ["dbt compile"]
  generate_docs        = false
  name                 = "Production"
  num_threads          = 4
  project_id           = dbtcloud_project.this.id
  run_generate_sources = false
  target_name          = "PROD"
  timeout_seconds      = 0
  triggers = {
    git_provider_webhook = false
    github_webhook       = false
    on_merge             = true
    schedule             = false
  }
  triggers_on_draft_pr = false
}

resource "dbtcloud_job" "prod_deploy_job" {
  environment_id       = dbtcloud_environment.prod_env.environment_id
  execute_steps        = ["dbt build"]
  generate_docs        = true
  name                 = "Production Deployment"
  num_threads          = 4
  project_id           = dbtcloud_project.this.id
  run_generate_sources = false
  target_name          = "PROD"
  timeout_seconds      = 0
  triggers = {
    git_provider_webhook = false
    github_webhook       = false
    on_merge             = false
    schedule             = false
  }
  triggers_on_draft_pr = false

  job_completion_trigger_condition {
    job_id     = dbtcloud_job.prod_merge_job.id
    project_id = dbtcloud_project.this.id
    statuses   = ["success"]
  }
}

Expected behavior
terraform plan runs without errors.
Config (please complete the following information):
( the version can be retrieved running the command terraform providers )

dbt Cloud provider version 0.3.16

Additional context
Add any other context about the problem here.

Thanks for the report!
Nothing really changed in this part of the provider code recently, so I am not too sure what is happening but seeing the error I can still think of ways to avoid this null pointer issue.
I will release a fix soon.

I could reproduce it and I am working on a quick fix.
I think that someone might have removed the catalog from the dbtcloud_connection (not the dbtcloud_global_connection) directly from the UI.

Will be fixed in 0.3.17 that should be out in the registry in 15-20 min


encryption - decryption tool

Create a  encryption - decryption tool in html,css and javascript.
the tool should  encrypt/decrypt the plain  text messages.
users can choose different methods of encryption. Add atleast 3 methods of encryption

Add navbar in your tool's html file. You can copy the navbar from index.html.
Add screenshot of your tool in, PR message and also in the folder of your tool
Before Making the PR Pull the latest changes that have been made to the repository

**Note: Please Don't Make Any Changes In index.html AND contributors.html **
**Note: Only make changes to the folder that you have created for your tool/utility **
Add the below mention section to your PR message
Title
Number of files/folder added
changes made
check the options that you have completed,
I have;

[ ] Read contibuting.md
[ ] Followed all the guidelines
[ ] Followed the directory Structure
[ ] updated readme.md
[ ] add your name in the footer of your tool.html file (if you created length conversion tool then add your name to length.html file you created)
[ ] provide below mentioned details if you want your name to be added in contributors.html
[ ] mail, twitter, github profile link.

hello @shubham2704 I can take this task please assign me

hey,is there anything i can work on,here?

@atom19-i Yes you can work on this one or you can choose from here


10 refactoring convertfrom gzipstring

resolves #10

Codecov Report

Merging #11 (305c214) into main (348167a) will increase coverage by 8.43%.
The diff coverage is 74.54%.

:exclamation: Your organization is not using the GitHub App Integration. As a result you may experience degraded service beginning May 15th. Please install the Github App Integration for your organization. Read more.
@@            Coverage Diff             @@
##             main      #11      +/-   ##
==========================================
+ Coverage   73.03%   81.46%   +8.43%
==========================================
  Files          20       21       +1
  Lines         879      885       +6
==========================================
+ Hits          642      721      +79
+ Misses        237      164      -73

Flag
Coverage Δ

PS_5.1
81.46% <74.54%> (+8.43%)
:arrow_up:

PS_7_Windows
81.46% <74.54%> (+8.43%)
:arrow_up:

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files
Coverage Δ

...Compression/Commands/ConvertToGzipStringCommand.cs
72.30% <ø> (ø)

src/PSCompression/ExcetionHelpers.cs
40.00% <ø> (+13.33%)
:arrow_up:

src/PSCompression/PSCompressionExtensions.cs
81.03% <58.33%> (-0.97%)
:arrow_down:

...mpression/Commands/ConvertFromGzipStringCommand.cs
72.41% <72.41%> (ø)

src/PSCompression/ZipEntryBase.cs
95.55% <75.00%> (+31.11%)
:arrow_up:

...rc/PSCompression/Commands/ExpandZipEntryCommand.cs
71.42% <100.00%> (+8.92%)
:arrow_up:

src/PSCompression/Commands/GetZipEntryCommand.cs
91.66% <100.00%> (+3.03%)
:arrow_up:

src/PSCompression/Commands/NewZipEntryCommand.cs
74.02% <100.00%> (+2.94%)
:arrow_up:

src/PSCompression/EncodingArgumentCompleter.cs
100.00% <100.00%> (ø)

... and 3 files with indirect coverage changes
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Does rasa core keras policy training change? It seems less good than rasa_core before

Rasa version: Rasa 1.0
Python version: 3.7
Operating system (windows, osx, ...): Linux
Issue: (question) Does rasa core keras policy training change? It seems less good than rasa_core before.
While using the same training data (i.e. stories) and policy config as rasa_core before (Keras + Memoization), the action taken by my chatbot changed dramatically. Saying that I only have 3 stories like "story1: intent_A -> utter_A; story2: intent_B -> utter_B; story3: intent_C -> utter_C".
When using rasa_core before, I obtained dialogue like "intent_A -> utter_A -> intent_B -> utter_B -> intent_A -> utter A".
However, now using rasa 1.0, I obtain "intent_A -> utter_A -> intent_B -> ??" and "intent_A -> utter_A -> intent_A -> ??".  (?? means no action or action with extremly low confidence) It seems rasa now consider with higher weight the beginning and the end of stories.
Edit:
Reason 1: Augmentation (def=20, in rasa 1.0.3) is a bit reduced for KerasPolicy. By increasing augmentation factor, Chatbot can answer correctly in the situations like "intent_A -> utter_A -> intent_A -> utter_A", etc. Because by augmentation, the initial stories are glued together as new training stories.
Reason 2: As I first tested with "rasa init" using all default options (random seed is not set), the model is underfit. Different runs result in different performances. By increasing epochs (ex: 500) and lowering batch_size (ex: 20), I obtained a much more converged model.

Nothing has changed between versions about how the KerasPolicy was implemented. The only thing that has changed is that the augmentation doesn't get applied to the MemoizationPolicy and also it's a bit reduced for KerasPolicy. So by default it will train on 50 stories that are created from your training data. You could probably increase the augmentation factor, but i'm not sure that's really necessary with so few stories.
Could you post the output of rasa train --debug for the core part?

@akelad Thanks for the info. I did many tries just now. Now I know why. This is not because of Keras Policy change.
It is because the "rasa init" example has KerasPolicy by default. These default options are not enough for the core model to converge. So runs can result in very differernt models, randomly.
With the same config (all by default as "rasa init"), I have Run 1:
Epoch 100/100
62/62 [==============================] - 0s 148us/sample - loss: 1.0351 - acc: 0.5806

Run 2:
Epoch 100/100
62/62 [==============================] - 0s 243us/sample - loss: 0.8892 - acc: 0.8548

When I set epochs: 500 and batch_size:20, we have a converged model and the performance is much better. So, for me, if you can make the "rasa init" example more stable, it should be better.

@akelad Hello again. You were right. I did more tests.
Two reasons make this happen. First reason is the default options (epochs, batches, etc.) are trying to underfit like I explained above in the example of "rasa init". Because I didn't set random seed, the results varied a lot. The other reason is that the augmentaion is reduced. That means "intent_A -> utter_A -> intent_B -> utter_B -> intent_A -> utter A" has lower chance of being created in the data augmentation step. Chatbot tends to answer correctly to the first query, but incorrect if the following query is not in a training story.

Awesome glad you managed to make this work

@Jinchao-Yu Hello I am curious about how did you do that? Can you please share your config.yml file?
Thank you.

@sushilr007 Do you mean this file?
policies:
  - name: "KerasPolicy"
    featurizer:
    - name: MaxHistoryTrackerFeaturizer
      max_history: 5
      state_featurizer:
        - name: BinarySingleStateFeaturizer
    epochs: 400
    batch_size: 50
    validation_split: 0.2
  - name: "MemoizationPolicy"
    max_history: 5
  - name: "FallbackPolicy"
    nlu_threshold: 0.2
    core_threshold: 0.2
    fallback_action_name: "utter_default"

Augmentation factor can be configured in a script for training rasa core. Maybe it can be set in command line too but I am not sure because I always use my scripts for training.
loop = asyncio.get_event_loop()
    training_data = loop.run_until_complete(
        agent.load_data(dir_core_training_data,
                        augmentation_factor=CORE_AUGMENTATION_FACTOR)
    )  # -> List[DialogueStateTracker]
    agent.train(training_data)

Thank you @Jinchao-Yu I exactly want this.  I read your issue and same I was thinking on that.
and also please share, which pipeline you are using?
Thank you so much.

@sushilr007 it's better for you to test your training sets with several pipelines based on your needs and select the best. For ex, I have my own class of preprocessing, which can change the choice of tokenization. Mine is:
language: "en"

pipeline:
- name: "SpacyNLP"
- name: "SpacyTokenizer"
- name: "CRFEntityExtractor"
  # "pos", "pos2" can be applied only when using SpacyNLP
  features: [
  ["low", "title", "upper"],
  ["bias", "low", "prefix5", "prefix2", "suffix5", "suffix3", "suffix2", "upper", "title", "digit", "pattern", "pos", "pos2"],
  ["low", "title", "upper"]]
- name: "CountVectorsFeaturizer"
- name: "EmbeddingIntentClassifier"
  intent_tokenization_flag: true
  intent_split_symbol: "+"


Include Drips.sol when calculating the circulating supply

https://etherscan.io/address/0xd0dd053392db676d57317cd4fe96fc2ccf42d0b4
Call the splittable function with accountId 0 (for the zero address).

ABI: https://github.com/drips-network/sdk/blob/main/src/abi/Drips.json


Fix broken section link in Identity troubleshooting guide

API change check
API changes are not detected in this pull request.


Unable to fetch parent entity with children that only match a certain criteria

This is in EF Core, I'll use the following schema for my examples:
BagOfSkittles
-----------------
id
type

Skittle
-----------------
id
bag_id
colour

In short, if I want to fetch a specific BagOfSkittles (whether by type or id), how do I ensure I always get the matched BagOfSkittles, while filtering the Skittles that belong to it by colour.  Even when there are no related Skittles that match.
I think what I'm after here is a left join, but the syntax to produce such a query isn't apparent to me and I haven't been able to find it in documentation (yet).
Perhaps something like this?
            var firstBagOfSkittles = await context.BagsOfSkittles
                .Include(b => b.Skittles)
                // This is where I'm a bit fuzzy.  Maybe something like...
                .Where(b => b.Skittles.Any(s => s.colour == "red" || s.colour == null))
                .FirstAsync()
            ;

@atrauzzi - Can you elaborate more what you are trying to fetch? If you know what your SQL should be then please post it. It will help in translating to LINQ.

@smitpatel -
...how do I ensure I always get the matched BagOfSkittles, while filtering the Skittles that belong to it by colour. Even when there are no related Skittles that match.
So I guess if I had the following data:
+---------------+----+------------+
| BagOfSkittles | id | type       |
+---------------+----+------------+
|               |    |            |
+---------------+----+------------+
| 1             | 45 | 'tropical' |
+---------------+----+------------+
| 2             | 77 | 'original' |
+---------------+----+------------+
| 3             | 18 | 'sour'     |
+---------------+----+------------+

+---------+----+--------+----------+
| Skittle | id | bag_id | colour   |
+---------+----+--------+----------+
|         |    |        |          |
+---------+----+--------+----------+
| 1       | 1  | 45     | 'red'    |
+---------+----+--------+----------+
| 2       | 2  | 45     | 'blue'   |
+---------+----+--------+----------+
| 3       | 3  | 77     | 'red'    |
+---------+----+--------+----------+
| 4       | 4  | 77     | 'green'  |
+---------+----+--------+----------+
| 5       | 5  | 45     | 'pink'   |
+---------+----+--------+----------+
| 6       | 6  | 18     | 'orange' |
+---------+----+--------+----------+
| 7       | 7  | 45     | 'red'    |
+---------+----+--------+----------+

Using the psuedo-linq in my original description, my hope would be to always get every BagOfSkittles regardless of whether related rows were found in the Skittles table.
A further refinement would be to specify a specific bag of skittles, and to always get the record, even if none of the colours matched.  For example: sour with blue doesn't appear as a combination in my data above.  I would still want to get the top of the graph which is an instance of BagOfSkittles.

...how do I ensure I always get the matched BagOfSkittles, while filtering the Skittles that belong to it by colour. Even when there are no related Skittles that match.

This statement is ambiguous, It does not clarify if you want BagOfSkittles which does not have any matching Skittles.
If you are trying to get all BagOfSkittles with Skittles navigation property populated without any condition then
context.BagOfSkittles.Include(b => b.Skittles)
If you want to have only those BagOfSkittles which have at least 1 Skittle which satisfy condition then
context.BagOfSkittles.Where(b => b.Skittles.Any(condition))
If you want all BagOfSkittles but want to load only Skittles in memory which satisfy the condition then it is filtered include which is being tracked by #1833

Yeah, definitely the third. The rest seems obvious otherwise. :)

@smitpatel, it seems that the second scenario is not working when using an array inside the .Any
var skittleNames = new string[] { "Lemon", "Orange", "Strawberry" };
context.BagOfSkittles.Where(b => b.Skittles.Any(s => skittleNames.Contains(s.Name)))

This will throw an exception since it cannot be translated to SQL
System.InvalidOperationException: The LINQ expression 'Any<Skittles>(
    source: Where<Skittle>(
        source: DbSet<Skittle>,
        predicate: (u0) => Property<string>(EntityShaperExpression:
            EntityType: Skittle
            ValueBufferExpression:
                ProjectionBindingExpression: EmptyProjectionMember
            IsNullable: False
...

Is there any alternative so this expression could be translated to SQL ?
Thanks in advance.
dotnet --info

.NET Core SDK (reflecting any global.json):
 Version:   3.0.100
 Commit:    04339c3a26

Runtime Environment:
 OS Name:     Mac OS X
 OS Version:  10.15
 OS Platform: Darwin
 RID:         osx.10.15-x64
 Base Path:   /usr/local/share/dotnet/sdk/3.0.100/

Host (useful for support):
  Version: 3.0.0
  Commit:  7d57652f33


Loosen asyncstorage-down version to allow 4.x.x

This is the current version as of July, 2017.
https://github.com/tradle/asyncstorage-down/commits/master

@Empact thanks! Released as 3.0.1


Levels

Hi,
How can we change Game levels?
Like easy, Medium, Hard.
Please tell us.
Thanks lot.

Hi @rasIOS
When creating an AIPlayer you can pass in an AIConfiguration struct. Pass in the difficulty when creating the AIConfiguration, you can use .easy, .medium or .hard.
For instance, you can create a hard difficulty AI player like this:
let configuration = AIConfiguration(difficulty: .hard)
let player = AIPlayer(color: .black, configuration: configuration)

It's work thanks :)


Update CI server image version (Node)

Use the lts and latest tag.

I'll check if we can apply similar changes to the rest of the matrix.


The module destroys the stable diffusion webui environment

Installed with the ComfyUI manager.
After a restart of the webui, it's no more working and I've got the following problem:
venv "G:\stable-diffusion-webui\venv\Scripts\Python.exe"
Python 3.10.11 (tags/v3.10.11:7d4cc5a, Apr  5 2023, 00:38:17) [MSC v.1929 64 bit (AMD64)]
Version: v1.10.1
Commit hash: 82a973c04367123ae98bd9abdf80d9eda9b910e2
Installing sd-webui-comfyui requirement: changing portalocker version from 2.10.1 to 2.7.0
Launching Web UI with arguments: --xformers --medvram-sdxl --opt-split-attention-v1 --theme dark --api
Traceback (most recent call last):
  File "G:\stable-diffusion-webui\launch.py", line 48, in <module>
    main()
  File "G:\stable-diffusion-webui\launch.py", line 44, in main
    start()
  File "G:\stable-diffusion-webui\modules\launch_utils.py", line 465, in start
    import webui
  File "G:\stable-diffusion-webui\webui.py", line 13, in <module>
    initialize.imports()
  File "G:\stable-diffusion-webui\modules\initialize.py", line 39, in imports
    from modules import processing, gradio_extensons, ui  # noqa: F401
  File "G:\stable-diffusion-webui\modules\processing.py", line 31, in <module>
    from ldm.data.util import AddMiDaS
  File "G:\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\data\util.py", line 3, in <module>
    from ldm.modules.midas.api import load_midas_transform
  File "G:\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\midas\api.py", line 11, in <module>
    from ldm.modules.midas.midas.transforms import Resize, NormalizeImage, PrepareForNet
  File "G:\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\midas\midas\transforms.py", line 6, in <module>
    def apply_min_size(sample, size, image_interpolation_method=cv2.INTER_AREA):
AttributeError: module 'cv2' has no attribute 'INTER_AREA'
Drücken Sie eine beliebige Taste . . .

A manual delete of the module from G:\stable-diffusion-webui\extensions\sd-webui-comfyui\ComfyUI\custom_nodes does not help.
It is required to delete and rebuild venv (G:\stable-diffusion-webui\venv) to recover the webui.
Gave it a second try, loaded ComfyUI and installed the module, the webui crashed again.

version: v1.10.1  •  python: 3.10.11  •  torch: 2.1.2+cu121  •  xformers: 0.0.23.post1  •  gradio: 3.41.2  •  checkpoint: 879db523c3
System:	Windows 10 Pro
Version	22H2
Betriebssystembuild	19045.4651

Tried a manual installation (recommended).
Seems to work but has a few  problems at the end:
Microsoft Windows [Version 10.0.19045.4651]
(c) Microsoft Corporation. Alle Rechte vorbehalten.

G:\stable-diffusion-webui\extensions\sd-webui-comfyui\ComfyUI\custom_nodes\was-node-suite-comfyui>pip install -r requirements.txt
Collecting git+https://github.com/WASasquatch/img2texture.git (from -r requirements.txt (line 3))
  Cloning https://github.com/WASasquatch/img2texture.git to c:\users\danie\appdata\local\temp\pip-req-build-wpaw1d4b
  Running command git clone --filter=blob:none --quiet https://github.com/WASasquatch/img2texture.git 'C:\Users\danie\AppData\Local\Temp\pip-req-build-wpaw1d4b'
  Resolved https://github.com/WASasquatch/img2texture.git to commit a546609a915caf1dcb84a15bf44b5b639ad924e6
  Installing build dependencies ... done
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  Cloning https://github.com/WASasquatch/cstr to c:\users\danie\appdata\local\temp\pip-req-build-nik62q83
  Running command git clone --filter=blob:none --quiet https://github.com/WASasquatch/cstr 'C:\Users\danie\AppData\Local\Temp\pip-req-build-nik62q83'
  Resolved https://github.com/WASasquatch/cstr to commit 0520c29a18a7a869a6e5983861d6f7a4c86f8e9b
  Installing build dependencies ... done
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Collecting git+https://github.com/WASasquatch/ffmpy.git (from -r requirements.txt (line 13))
  Cloning https://github.com/WASasquatch/ffmpy.git to c:\users\danie\appdata\local\temp\pip-req-build-cfwkmpz6
  Running command git clone --filter=blob:none --quiet https://github.com/WASasquatch/ffmpy.git 'C:\Users\danie\AppData\Local\Temp\pip-req-build-cfwkmpz6'
  Resolved https://github.com/WASasquatch/ffmpy.git to commit f000737698b387ffaeab7cd871b0e9185811230d
  Installing build dependencies ... done
  Getting requirements to build wheel ... done
  Preparing metadata (pyproject.toml) ... done
Collecting cmake (from -r requirements.txt (line 1))
  Using cached cmake-3.30.2-py3-none-win_amd64.whl.metadata (6.1 kB)
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  Using cached fairscale-0.4.13-py3-none-any.whl
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Collecting opencv-python-headless<=<IP_ADDRESS> (from opencv-python-headless[ffmpeg]<=<IP_ADDRESS>->-r requirements.txt (line 11))
  Using cached opencv_python_headless-<IP_ADDRESS>-cp37-abi3-win_amd64.whl.metadata (18 kB)
Collecting pilgram (from -r requirements.txt (line 12))
  Using cached pilgram-1.2.1-py3-none-any.whl.metadata (4.0 kB)
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Requirement already satisfied: torch>=1.8.0 in e:\programme\python\python310\lib\site-packages (from fairscale>=0.4.4->-r requirements.txt (line 2)) (2.1.2+cu121)
Collecting pillow<10,>=9.2 (from img2texture==1.0.6->-r requirements.txt (line 3))
  Using cached Pillow-9.5.0-cp310-cp310-win_amd64.whl.metadata (9.7 kB)
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Collecting pooch (from rembg->-r requirements.txt (line 14))
  Using cached pooch-1.8.2-py3-none-any.whl.metadata (10 kB)
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Requirement already satisfied: networkx>=2.8 in e:\programme\python\python310\lib\site-packages (from scikit-image>=0.20.0->-r requirements.txt (line 15)) (3.3)
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WARNING: opencv-python-headless <IP_ADDRESS> does not provide the extra 'ffmpeg'
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Requirement already satisfied: protobuf in e:\programme\python\python310\lib\site-packages (from onnxruntime->rembg->-r requirements.txt (line 14)) (4.25.3)
Requirement already satisfied: platformdirs>=2.5.0 in e:\programme\python\python310\lib\site-packages (from pooch->rembg->-r requirements.txt (line 14)) (4.2.2)
Requirement already satisfied: charset-normalizer<4,>=2 in e:\programme\python\python310\lib\site-packages (from requests->transformers->-r requirements.txt (line 20)) (3.3.2)
Requirement already satisfied: idna<4,>=2.5 in e:\programme\python\python310\lib\site-packages (from requests->transformers->-r requirements.txt (line 20)) (3.7)
Requirement already satisfied: urllib3<3,>=1.21.1 in e:\programme\python\python310\lib\site-packages (from requests->transformers->-r requirements.txt (line 20)) (2.2.2)
Requirement already satisfied: certifi>=2017.4.17 in e:\programme\python\python310\lib\site-packages (from requests->transformers->-r requirements.txt (line 20)) (2024.6.2)
Requirement already satisfied: humanfriendly>=9.1 in e:\programme\python\python310\lib\site-packages (from coloredlogs->onnxruntime->rembg->-r requirements.txt (line 14)) (10.0)
Requirement already satisfied: MarkupSafe>=2.0 in e:\programme\python\python310\lib\site-packages (from jinja2->torch>=1.8.0->fairscale>=0.4.4->-r requirements.txt (line 2)) (2.1.5)
Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in e:\programme\python\python310\lib\site-packages (from sympy->torch>=1.8.0->fairscale>=0.4.4->-r requirements.txt (line 2)) (1.3.0)
Requirement already satisfied: pyreadline3 in e:\programme\python\python310\lib\site-packages (from humanfriendly>=9.1->coloredlogs->onnxruntime->rembg->-r requirements.txt (line 14)) (3.4.1)
Using cached cmake-3.30.2-py3-none-win_amd64.whl (35.6 MB)
Using cached opencv_python_headless-<IP_ADDRESS>-cp37-abi3-win_amd64.whl (38.1 MB)
Using cached pilgram-1.2.1-py3-none-any.whl (817 kB)
Using cached rembg-2.0.58-py3-none-any.whl (33 kB)
Using cached Pillow-9.5.0-cp310-cp310-win_amd64.whl (2.5 MB)
Using cached pooch-1.8.2-py3-none-any.whl (64 kB)
Using cached PyMatting-1.1.12-py3-none-any.whl (52 kB)
Building wheels for collected packages: img2texture, cstr, ffmpy
  Building wheel for img2texture (pyproject.toml) ... done
  Created wheel for img2texture: filename=img2texture-1.0.6-py3-none-any.whl size=8448 sha256=e3529fa19ff735ece88e762f5c7c1746e00f1aa222c9baf93b73c33b3cbd292c
  Stored in directory: C:\Users\danie\AppData\Local\Temp\pip-ephem-wheel-cache-n2jflge1\wheels\ef\01\9f\2a02c1af22973c81e59b3e7c5a63a57bc73050b9176aa479d2
  Building wheel for cstr (pyproject.toml) ... done
  Created wheel for cstr: filename=cstr-0.1.0-py3-none-any.whl size=2847 sha256=a57a9aa0274a7988534642de7a32540dce53d56ba581865ce8e9630bc8429651
  Stored in directory: C:\Users\danie\AppData\Local\Temp\pip-ephem-wheel-cache-n2jflge1\wheels\89\3f\37\64121630832f72f13d3af8bb065e97483aa6e038bb27dd941a
  Building wheel for ffmpy (pyproject.toml) ... done
  Created wheel for ffmpy: filename=ffmpy-0.3.0-py3-none-any.whl size=5542 sha256=14154346c6248e0b2ef28f6e62ee28faba943a40147dc3f3764f6771ecac7721
  Stored in directory: C:\Users\danie\AppData\Local\Temp\pip-ephem-wheel-cache-n2jflge1\wheels\58\b8\b4\c142357beed3083ac6f76bff1206bb5923ac472c4a740e6921
Successfully built img2texture cstr ffmpy
Installing collected packages: ffmpy, cstr, pillow, pilgram, opencv-python-headless, cmake, pymatting, pooch, img2texture, fairscale, rembg
  Attempting uninstall: ffmpy
    Found existing installation: ffmpy 0.3.2
    Uninstalling ffmpy-0.3.2:
      Successfully uninstalled ffmpy-0.3.2
  Attempting uninstall: pillow
    Found existing installation: pillow 10.3.0
    Uninstalling pillow-10.3.0:
      Successfully uninstalled pillow-10.3.0
  Attempting uninstall: opencv-python-headless
    Found existing installation: opencv-python-headless <IP_ADDRESS>
    Uninstalling opencv-python-headless-<IP_ADDRESS>:
      Successfully uninstalled opencv-python-headless-<IP_ADDRESS>
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
albucore 0.0.12 requires opencv-python-headless>=<IP_ADDRESS>, but you have opencv-python-headless <IP_ADDRESS> which is incompatible.
albumentations 1.4.10 requires opencv-python-headless>=<IP_ADDRESS>, but you have opencv-python-headless <IP_ADDRESS> which is incompatible.
blendmodes 2024.1.1 requires Pillow<11,>=10.2.0, but you have pillow 9.5.0 which is incompatible.
Successfully installed cmake-3.30.2 cstr-0.1.0 fairscale-0.4.13 ffmpy-0.3.0 img2texture-1.0.6 opencv-python-headless-<IP_ADDRESS> pilgram-1.2.1 pillow-9.5.0 pooch-1.8.2 pymatting-1.1.12 rembg-2.0.58

Again the errors alone:
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
albucore 0.0.12 requires opencv-python-headless>=<IP_ADDRESS>, but you have opencv-python-headless <IP_ADDRESS> which is incompatible.
albumentations 1.4.10 requires opencv-python-headless>=<IP_ADDRESS>, but you have opencv-python-headless <IP_ADDRESS> which is incompatible.
blendmodes 2024.1.1 requires Pillow<11,>=10.2.0, but you have pillow 9.5.0 which is incompatible.

Don't use the same venv as other software. Create a new venv for every
project.
On Tue, Aug 6, 2024, 5:26 PM Daniel Schöni @.***> wrote:

Tried a manual installation (recommended).
Seems to work but has a few problems at the end:
Microsoft Windows [Version 10.0.19045.4651]
(c) Microsoft Corporation. Alle Rechte vorbehalten.
G:\stable-diffusion-webui\extensions\sd-webui-comfyui\ComfyUI\custom_nodes\was-node-suite-comfyui>pip install -r requirements.txt
Collecting git+https://github.com/WASasquatch/img2texture.git (from -r requirements.txt (line 3))
Cloning https://github.com/WASasquatch/img2texture.git to c:\users\danie\appdata\local\temp\pip-req-build-wpaw1d4b
Running command git clone --filter=blob:none --quiet https://github.com/WASasquatch/img2texture.git 'C:\Users\danie\AppData\Local\Temp\pip-req-build-wpaw1d4b'
Resolved https://github.com/WASasquatch/img2texture.git to commit a546609a915caf1dcb84a15bf44b5b639ad924e6
Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Collecting git+https://github.com/WASasquatch/cstr (from -r requirements.txt (line 4))
Cloning https://github.com/WASasquatch/cstr to c:\users\danie\appdata\local\temp\pip-req-build-nik62q83
Running command git clone --filter=blob:none --quiet https://github.com/WASasquatch/cstr 'C:\Users\danie\AppData\Local\Temp\pip-req-build-nik62q83'
Resolved https://github.com/WASasquatch/cstr to commit 0520c29a18a7a869a6e5983861d6f7a4c86f8e9b
Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Collecting git+https://github.com/WASasquatch/ffmpy.git (from -r requirements.txt (line 13))
Cloning https://github.com/WASasquatch/ffmpy.git to c:\users\danie\appdata\local\temp\pip-req-build-cfwkmpz6
Running command git clone --filter=blob:none --quiet https://github.com/WASasquatch/ffmpy.git 'C:\Users\danie\AppData\Local\Temp\pip-req-build-cfwkmpz6'
Resolved https://github.com/WASasquatch/ffmpy.git to commit f000737698b387ffaeab7cd871b0e9185811230d
Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Collecting cmake (from -r requirements.txt (line 1))
Using cached cmake-3.30.2-py3-none-win_amd64.whl.metadata (6.1 kB)
Collecting fairscale>=0.4.4 (from -r requirements.txt (line 2))
Using cached fairscale-0.4.13-py3-none-any.whl
Requirement already satisfied: gitpython in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 5)) (3.1.43)
Requirement already satisfied: imageio in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 6)) (2.34.2)
Requirement already satisfied: joblib in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 7)) (1.4.2)
Requirement already satisfied: matplotlib in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 8)) (3.9.0)
Requirement already satisfied: numba in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 9)) (0.60.0)
Requirement already satisfied: numpy in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 10)) (1.26.4)
Collecting opencv-python-headless<=<IP_ADDRESS> (from opencv-python-headless[ffmpeg]<=<IP_ADDRESS>->-r requirements.txt (line 11))
Using cached opencv_python_headless-<IP_ADDRESS>-cp37-abi3-win_amd64.whl.metadata (18 kB)
Collecting pilgram (from -r requirements.txt (line 12))
Using cached pilgram-1.2.1-py3-none-any.whl.metadata (4.0 kB)
Collecting rembg (from -r requirements.txt (line 14))
Using cached rembg-2.0.58-py3-none-any.whl.metadata (16 kB)
Requirement already satisfied: scikit-image>=0.20.0 in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 15)) (0.24.0)
Requirement already satisfied: scikit-learn in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 16)) (1.5.0)
Requirement already satisfied: scipy in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 17)) (1.14.0)
Requirement already satisfied: timm>=0.4.12 in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 18)) (1.0.7)
Requirement already satisfied: tqdm in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 19)) (4.66.4)
Requirement already satisfied: transformers in e:\programme\python\python310\lib\site-packages (from -r requirements.txt (line 20)) (4.30.2)
Requirement already satisfied: torch>=1.8.0 in e:\programme\python\python310\lib\site-packages (from fairscale>=0.4.4->-r requirements.txt (line 2)) (2.1.2+cu121)
Collecting pillow<10,>=9.2 (from img2texture==1.0.6->-r requirements.txt (line 3))
Using cached Pillow-9.5.0-cp310-cp310-win_amd64.whl.metadata (9.7 kB)
Requirement already satisfied: gitdb<5,>=4.0.1 in e:\programme\python\python310\lib\site-packages (from gitpython->-r requirements.txt (line 5)) (4.0.11)
Requirement already satisfied: contourpy>=1.0.1 in e:\programme\python\python310\lib\site-packages (from matplotlib->-r requirements.txt (line 8)) (1.2.1)
Requirement already satisfied: cycler>=0.10 in e:\programme\python\python310\lib\site-packages (from matplotlib->-r requirements.txt (line 8)) (0.12.1)
Requirement already satisfied: fonttools>=4.22.0 in e:\programme\python\python310\lib\site-packages (from matplotlib->-r requirements.txt (line 8)) (4.53.0)
Requirement already satisfied: kiwisolver>=1.3.1 in e:\programme\python\python310\lib\site-packages (from matplotlib->-r requirements.txt (line 8)) (1.4.5)
Requirement already satisfied: packaging>=20.0 in e:\programme\python\python310\lib\site-packages (from matplotlib->-r requirements.txt (line 8)) (24.1)
Requirement already satisfied: pyparsing>=2.3.1 in e:\programme\python\python310\lib\site-packages (from matplotlib->-r requirements.txt (line 8)) (3.1.2)
Requirement already satisfied: python-dateutil>=2.7 in e:\programme\python\python310\lib\site-packages (from matplotlib->-r requirements.txt (line 8)) (2.9.0.post0)
Requirement already satisfied: llvmlite<0.44,>=0.43.0dev0 in e:\programme\python\python310\lib\site-packages (from numba->-r requirements.txt (line 9)) (0.43.0)
Requirement already satisfied: jsonschema in e:\programme\python\python310\lib\site-packages (from rembg->-r requirements.txt (line 14)) (4.22.0)
Requirement already satisfied: onnxruntime in e:\programme\python\python310\lib\site-packages (from rembg->-r requirements.txt (line 14)) (1.15.0)
Collecting pooch (from rembg->-r requirements.txt (line 14))
Using cached pooch-1.8.2-py3-none-any.whl.metadata (10 kB)
Collecting pymatting (from rembg->-r requirements.txt (line 14))
Using cached PyMatting-1.1.12-py3-none-any.whl.metadata (7.4 kB)
Requirement already satisfied: networkx>=2.8 in e:\programme\python\python310\lib\site-packages (from scikit-image>=0.20.0->-r requirements.txt (line 15)) (3.3)
Requirement already satisfied: tifffile>=2022.8.12 in e:\programme\python\python310\lib\site-packages (from scikit-image>=0.20.0->-r requirements.txt (line 15)) (2024.6.18)
Requirement already satisfied: lazy-loader>=0.4 in e:\programme\python\python310\lib\site-packages (from scikit-image>=0.20.0->-r requirements.txt (line 15)) (0.4)
Requirement already satisfied: threadpoolctl>=3.1.0 in e:\programme\python\python310\lib\site-packages (from scikit-learn->-r requirements.txt (line 16)) (3.5.0)
Requirement already satisfied: torchvision in e:\programme\python\python310\lib\site-packages (from timm>=0.4.12->-r requirements.txt (line 18)) (0.16.2+cu121)
Requirement already satisfied: pyyaml in e:\programme\python\python310\lib\site-packages (from timm>=0.4.12->-r requirements.txt (line 18)) (6.0.1)
Requirement already satisfied: huggingface_hub in e:\programme\python\python310\lib\site-packages (from timm>=0.4.12->-r requirements.txt (line 18)) (0.23.4)
Requirement already satisfied: safetensors in e:\programme\python\python310\lib\site-packages (from timm>=0.4.12->-r requirements.txt (line 18)) (0.4.3)
Requirement already satisfied: colorama in e:\programme\python\python310\lib\site-packages (from tqdm->-r requirements.txt (line 19)) (0.4.6)
Requirement already satisfied: filelock in e:\programme\python\python310\lib\site-packages (from transformers->-r requirements.txt (line 20)) (3.15.4)
Requirement already satisfied: regex!=2019.12.17 in e:\programme\python\python310\lib\site-packages (from transformers->-r requirements.txt (line 20)) (2024.5.15)
Requirement already satisfied: requests in e:\programme\python\python310\lib\site-packages (from transformers->-r requirements.txt (line 20)) (2.32.3)
Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in e:\programme\python\python310\lib\site-packages (from transformers->-r requirements.txt (line 20)) (0.13.3)
WARNING: opencv-python-headless <IP_ADDRESS> does not provide the extra 'ffmpeg'
Requirement already satisfied: smmap<6,>=3.0.1 in e:\programme\python\python310\lib\site-packages (from gitdb<5,>=4.0.1->gitpython->-r requirements.txt (line 5)) (5.0.1)
Requirement already satisfied: fsspec>=2023.5.0 in e:\programme\python\python310\lib\site-packages (from huggingface_hub->timm>=0.4.12->-r requirements.txt (line 18)) (2024.6.1)
Requirement already satisfied: typing-extensions>=<IP_ADDRESS> in e:\programme\python\python310\lib\site-packages (from huggingface_hub->timm>=0.4.12->-r requirements.txt (line 18)) (4.12.2)
Requirement already satisfied: six>=1.5 in e:\programme\python\python310\lib\site-packages (from python-dateutil>=2.7->matplotlib->-r requirements.txt (line 8)) (1.16.0)
Requirement already satisfied: sympy in e:\programme\python\python310\lib\site-packages (from torch>=1.8.0->fairscale>=0.4.4->-r requirements.txt (line 2)) (1.12.1)
Requirement already satisfied: jinja2 in e:\programme\python\python310\lib\site-packages (from torch>=1.8.0->fairscale>=0.4.4->-r requirements.txt (line 2)) (3.1.4)
Requirement already satisfied: attrs>=22.2.0 in e:\programme\python\python310\lib\site-packages (from jsonschema->rembg->-r requirements.txt (line 14)) (23.2.0)
Requirement already satisfied: jsonschema-specifications>=2023.03.6 in e:\programme\python\python310\lib\site-packages (from jsonschema->rembg->-r requirements.txt (line 14)) (2023.12.1)
Requirement already satisfied: referencing>=0.28.4 in e:\programme\python\python310\lib\site-packages (from jsonschema->rembg->-r requirements.txt (line 14)) (0.35.1)
Requirement already satisfied: rpds-py>=0.7.1 in e:\programme\python\python310\lib\site-packages (from jsonschema->rembg->-r requirements.txt (line 14)) (0.18.1)
Requirement already satisfied: coloredlogs in e:\programme\python\python310\lib\site-packages (from onnxruntime->rembg->-r requirements.txt (line 14)) (15.0.1)
Requirement already satisfied: flatbuffers in e:\programme\python\python310\lib\site-packages (from onnxruntime->rembg->-r requirements.txt (line 14)) (24.3.25)
Requirement already satisfied: protobuf in e:\programme\python\python310\lib\site-packages (from onnxruntime->rembg->-r requirements.txt (line 14)) (4.25.3)
Requirement already satisfied: platformdirs>=2.5.0 in e:\programme\python\python310\lib\site-packages (from pooch->rembg->-r requirements.txt (line 14)) (4.2.2)
Requirement already satisfied: charset-normalizer<4,>=2 in e:\programme\python\python310\lib\site-packages (from requests->transformers->-r requirements.txt (line 20)) (3.3.2)
Requirement already satisfied: idna<4,>=2.5 in e:\programme\python\python310\lib\site-packages (from requests->transformers->-r requirements.txt (line 20)) (3.7)
Requirement already satisfied: urllib3<3,>=1.21.1 in e:\programme\python\python310\lib\site-packages (from requests->transformers->-r requirements.txt (line 20)) (2.2.2)
Requirement already satisfied: certifi>=2017.4.17 in e:\programme\python\python310\lib\site-packages (from requests->transformers->-r requirements.txt (line 20)) (2024.6.2)
Requirement already satisfied: humanfriendly>=9.1 in e:\programme\python\python310\lib\site-packages (from coloredlogs->onnxruntime->rembg->-r requirements.txt (line 14)) (10.0)
Requirement already satisfied: MarkupSafe>=2.0 in e:\programme\python\python310\lib\site-packages (from jinja2->torch>=1.8.0->fairscale>=0.4.4->-r requirements.txt (line 2)) (2.1.5)
Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in e:\programme\python\python310\lib\site-packages (from sympy->torch>=1.8.0->fairscale>=0.4.4->-r requirements.txt (line 2)) (1.3.0)
Requirement already satisfied: pyreadline3 in e:\programme\python\python310\lib\site-packages (from humanfriendly>=9.1->coloredlogs->onnxruntime->rembg->-r requirements.txt (line 14)) (3.4.1)
Using cached cmake-3.30.2-py3-none-win_amd64.whl (35.6 MB)
Using cached opencv_python_headless-<IP_ADDRESS>-cp37-abi3-win_amd64.whl (38.1 MB)
Using cached pilgram-1.2.1-py3-none-any.whl (817 kB)
Using cached rembg-2.0.58-py3-none-any.whl (33 kB)
Using cached Pillow-9.5.0-cp310-cp310-win_amd64.whl (2.5 MB)
Using cached pooch-1.8.2-py3-none-any.whl (64 kB)
Using cached PyMatting-1.1.12-py3-none-any.whl (52 kB)
Building wheels for collected packages: img2texture, cstr, ffmpy
Building wheel for img2texture (pyproject.toml) ... done
Created wheel for img2texture: filename=img2texture-1.0.6-py3-none-any.whl size=8448 sha256=e3529fa19ff735ece88e762f5c7c1746e00f1aa222c9baf93b73c33b3cbd292c
Stored in directory: C:\Users\danie\AppData\Local\Temp\pip-ephem-wheel-cache-n2jflge1\wheels\ef\01\9f\2a02c1af22973c81e59b3e7c5a63a57bc73050b9176aa479d2
Building wheel for cstr (pyproject.toml) ... done
Created wheel for cstr: filename=cstr-0.1.0-py3-none-any.whl size=2847 sha256=a57a9aa0274a7988534642de7a32540dce53d56ba581865ce8e9630bc8429651
Stored in directory: C:\Users\danie\AppData\Local\Temp\pip-ephem-wheel-cache-n2jflge1\wheels\89\3f\37\64121630832f72f13d3af8bb065e97483aa6e038bb27dd941a
Building wheel for ffmpy (pyproject.toml) ... done
Created wheel for ffmpy: filename=ffmpy-0.3.0-py3-none-any.whl size=5542 sha256=14154346c6248e0b2ef28f6e62ee28faba943a40147dc3f3764f6771ecac7721
Stored in directory: C:\Users\danie\AppData\Local\Temp\pip-ephem-wheel-cache-n2jflge1\wheels\58\b8\b4\c142357beed3083ac6f76bff1206bb5923ac472c4a740e6921
Successfully built img2texture cstr ffmpy
Installing collected packages: ffmpy, cstr, pillow, pilgram, opencv-python-headless, cmake, pymatting, pooch, img2texture, fairscale, rembg
Attempting uninstall: ffmpy
Found existing installation: ffmpy 0.3.2
Uninstalling ffmpy-0.3.2:
Successfully uninstalled ffmpy-0.3.2
Attempting uninstall: pillow
Found existing installation: pillow 10.3.0
Uninstalling pillow-10.3.0:
Successfully uninstalled pillow-10.3.0
Attempting uninstall: opencv-python-headless
Found existing installation: opencv-python-headless <IP_ADDRESS>
Uninstalling opencv-python-headless-<IP_ADDRESS>:
Successfully uninstalled opencv-python-headless-<IP_ADDRESS>
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
albucore 0.0.12 requires opencv-python-headless>=<IP_ADDRESS>, but you have opencv-python-headless <IP_ADDRESS> which is incompatible.
albumentations 1.4.10 requires opencv-python-headless>=<IP_ADDRESS>, but you have opencv-python-headless <IP_ADDRESS> which is incompatible.
blendmodes 2024.1.1 requires Pillow<11,>=10.2.0, but you have pillow 9.5.0 which is incompatible.
Successfully installed cmake-3.30.2 cstr-0.1.0 fairscale-0.4.13 ffmpy-0.3.0 img2texture-1.0.6 opencv-python-headless-<IP_ADDRESS> pilgram-1.2.1 pillow-9.5.0 pooch-1.8.2 pymatting-1.1.12 rembg-2.0.58
Again the errors alone:
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
albucore 0.0.12 requires opencv-python-headless>=<IP_ADDRESS>, but you have opencv-python-headless <IP_ADDRESS> which is incompatible.
albumentations 1.4.10 requires opencv-python-headless>=<IP_ADDRESS>, but you have opencv-python-headless <IP_ADDRESS> which is incompatible.
blendmodes 2024.1.1 requires Pillow<11,>=10.2.0, but you have pillow 9.5.0 which is incompatible.
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You are receiving this because you are subscribed to this thread.Message
ID: @.***>

What? That makes no sense. Create a new conda environment outside the comfy environment?

Stable Diffusion WebUI, or Automatic1111 or variants is a competing system which uses different dependencies than ComfyUI. You don't install them in the same conda/venv/docker.

Don't use the same venv as other software. Create a new venv for every project.

Using the Stable Diffusion WebUI with the ComfyUI extension, the same venv is used. This is by 'default' and it is not clear for me, how to change that and why it is not done by default, if it would be possible or required.
(@WASasquatch )

Stable Diffusion WebUI, or Automatic1111 or variants is a competing system which uses different dependencies than ComfyUI. You don't install them in the same conda/venv/docker.

As I know, I can't do anything, that influences whether to use or not to use the same dependencies, while installing the ComfyUI Extension in Stable Diffusion WebUI or Automatic1111.
I'm installing it by using the WebUI Extension installer and I don't have any idea, whats going on behind. I only see the results.
The same is for the ComfyUI Nodes and Models. I'm just using the ComfyUI Manager.
(@WAS-PlaiLabs )
If the WebUI crashes and won't come up after an installation of such a node or model, this tells me, that both are using the same environment. A possibility to recover is, as I have learned now, to delete the venv folder inside the base WebUI folder, to remove the last installed models or nodes manually and then start the WebUI again. This takes some time ...
I think, I should do a backup of the venv and ComfyUI\custom nodes folders in the future before any node installation, to prevent from such disasters.

Ah you are using the extension. That is a pretty old extension which hasn't had an update in 7mo. The thing about this is getting ConfyUI and A1111 together isn't the biggest problem, it's custom nodes using whatever versions of things. Often the newest which is a pain cause they often aren't using the new features in it.
I personally would suggest trying something like CushyStudio over using A1111. I've never had a good time with it and it's scripts let alone supporting ConfyUI's custom node ecosystem.

Well, thank you, @WASasquatch .
I do understand now, that the problem lies really on the extensions side, respectevely in conflicts within the used environments of A1111 and ConfyUI. There is no proper separation.
I've tried a parallel installation of the standalone ComfyUI portable now, which works really fine and without such problems.
Thanks to extra_model_paths.yaml I can use all models on both systems.
I've installed all the former problematic nodes and models all at once and had no problems !!!
(maybe except the ReActor node, but this is a different story with insightface, which has to be installed manually.)

Glad you got it figured out. I am having issues with ReActor too (again).
Ironic haha.
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Geocoder offline

Hey,
When my device is offline the geocoding make the app freeze for about a second, and then the geocoding method callback fire with an empty array.
I guess it's caused by the Google API call which fail.
I found in the Google Geocoding doc a "isPresent()" method which return true or false if the geocoding methods are available. I think this method could resolve this issue.
http://developer.android.com/reference/android/location/Geocoder.html#isPresent()
Thank you !

Would you like to provide a PR ?

@abellion Thank you for inspecting. I will check this later.

Um, isPresent() returns true on my device when it is in the Airplane mode.

This is not reproduce issue. This one close at once. If any update, please reopen this.


Use appropriate annotations on source properties in Gradle tasks

Was the addition of @IgnoreEmptyDirectories to prevent known bugs?

No, no bugs. It just means that when input files are snapshot for up to date checks that empty directories will be ignored, increasing performance if the only change in the source was the inclusion (or removal) of an empty directory.
getSource on SourceTask has had the annotation since Gradle 6.8, but it needs to be added here to take effect since we're overriding to update the path sensitivity annotation.

Something I learned is that we override the path sensitivity in https://github.com/detekt/detekt/pull/2182. I guess this can be useful if we are exploring remote build cache in the future.


diplodoc/terms

also shouldn't we think about the fact that if we insert tokens before others it will change their map?
other important point - to render term content inside other containers we think it's exact position in the original document, can we receive it?

It doesn't affect next elements maps. Previously we just ignored it and it worked
Yes, it works fine now, I tested it on several templates


Rework recipient lines and recipient parsing to be pluggable

Currently each supported recipient line and type is hard-coded and special-cased. While this is nice for e.g. building the enums, it makes it harder to extend with new recipient types, which is the single joint in the age format. In the interest of keeping that joint well oiled, we should rework the recipient line handling logic to be pluggable. Initially this would be an internal decision, but it should be usable via the library interface, and maybe later via binary plugins for the rage tool suit.
Related to #36.

After discussion at HACS 2020, it is likely that we will create a plugin system where the main implementations communicate with separate plugin binaries via a standard I/O interface. I'm still inclined to figure out an internal trait for handling recipient lines and keys though, as it means that adding support for more recipient lines is not a breaking change (though I could probably use incomplete enums for that), and removing support for recipient lines is not a breaking change.

#52 and #56 have improved recipient line parsing to the point that it could be behind an internal trait. Serialization still needs to be refactored.


riscv32: linker: Keep vectors section in ROMABLE_REGION

For non XIP based RISC-V devices, vectors section needs to be placed
in RAM rather than in ROM. This would require us to place the section
under ROMABLE_REGION alias instead of the hardcoded ROM region.
Signed-off-by: Manivannan Sadhasivam<EMAIL_ADDRESS>

Codecov Report

Merging #10889 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master   #10889   +/-   ##
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  Coverage   53.32%   53.32%
=======================================
  Files         215      215
  Lines       25886    25886
  Branches     5705     5705
=======================================
  Hits        13803    13803
  Misses       9763     9763
  Partials     2320     2320

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Thanks for your contribution @Mani-Sadhasivam! However, this looks like it might be a duplicate of #10549.


Sprite's modulate alpha when instantiating custom scene as child is not repsected when having Input processing logic

Godot version
3.5.2-stable, 4.0-stable
System information
macOS 13.2.1
Issue description
When adding an instantiated scene with alpha in self_modulate configured for the sprite to another scene as a child during a input processing logic, the alpha in self_modualte is not respeced
Steps to reproduce
See the attached reproduction project (3.5.2 stable). Run the project and click in the game screen, the added sprite does not have the configured self_modulate alpha applied. The issue also exists in 4.0-stable.
Minimal reproduction project
TestSprite1.zip

The sprite has correct alpha.
Or rather sprites.
You overlap 4 of them.


Keep-Alive Doesn’t Work with Transition-Group

Version
2.3.4
Reproduction link
https://jsfiddle.net/kxemxsjy/1/
Steps to reproduce
The JsFiddle was created by a gentleman on Vue help forum, it's not a complete replicate of the problem, but it's a good starting point for my testing.

Put something random to be cached by keep-alive in the card component
Wrap keep-alive around card components directly (components won't rendered at all)
Wrap keep-alive around card components directly and key the keep-alive (components won't rendered at all)
Wrap keep-alive around transition-group (components rendered, but nothing gets cached)
Specify name using include doesn't help either

What is expected?
Rating status (in rating component) should be kept for all cards correspondingly
What is actually happening?
Nothing's kept or the card components just not rendered at all due to Vue needs all items to be keyed (Which doesn't quite make sense for keep-alive...)
I went ahead and keyed the keep-alive anyway, but still no luck

I've been stuck on this issue for long enough, I think it's probably time to reach out for some help...
I have a search interface which displays results as card (using v-for), it will be switched to a different view card-reveal when user click on it.
There is a component inside each card called UserRating from which I want the rating info to be kept when users switch to card-reveal. I thought it was an obvious keep-alive case where the documentation seems to be quite straight forward. However, no matter where I wrap the keep alive (with target name), it just doesn't work... Some help would be appreciated. Thanks.
##Partial DOM structure for card and card-reveal

More code here...

  <keep-alive include="UserRating">
    <transition-group name="card" tag="div">
      <Card v-if="expansionReady"
          v-for="result in apiResults"
          :result="result"
          :key="result.id" />
    </transition-group>
  </keep-alive>

More code here...

  <transition name="slideIn" tag="div">
    <CardReveal v-if="expansionMode" :result="currentApiResult" />
  </transition>

##Here is what UserRating component look like:
<template>

     0}"
        @click.stop="userRate('up')">thumb_up
    <i class="material-icons results-rate-down"
        :class="{toggled: rateStatus < 0}"
        @click.stop="userRate('down')">thumb_down

</template>

The fiddle isn't really reproducing the issue, so I can only give vague feedback.
<keep-alive> is designed for the case where it has one direct child component that is being toggled - it can't work if you have v-for inside it, nor does it work if you wrap it on the entire <transition-group> (unless you are toggling the transition group instead).
More importantly - I don't think it's a good idea using <keep-alive> for state preservation like this, especially with v-for and <transition-group> involved, both of which are inherently working with lists instead of a single toggled child. I recommend thinking from another angle - hoist the ratings state out into a shared state object or a vuex store so that it's unaffected by the components' lifecycles.

I ran into this issue as well (and authored the fiddle).
The keep-alive documentation indicates you can wrap multiple elements which are conditionally rendered:

<keep-alive>
  <comp-a v-if="a > 1"></comp-a>
  <comp-b v-else></comp-b>
</keep-alive>

It is reasonable to expect this same behavior would hold when the multiple children are declared with v-for instead of an explicit list.
I apologize if the fiddle is incomplete. The fiddle simply wraps a v-for in a keep-alive. To observe the issue, you need to inspect the DOM to see if the elements are staying around. Is there a more obviously way to show if keep-alive is working?

The difference is that v-for can render multiple elements but the v-if/v-else only renders one

@posva: Thanks for your insight. That is a good distinction to keep in mind. Both comp-a and comp-b are kept alive, but only one is rendered at a time, based on the predicate a > 1.
Perhaps the documentation could be improved to clarify "multiple conditional children" are only supported when rendered mutually-exclusively. Note, it is not uncommon to do mutually-exclusive rendering using v-for as well. For example, conditionally rendering (v-if/v-show) based on a "currentIndex", for example. Granted, it would be difficult for Vue to know if v-for is being used in this mode.
From a usage/syntax sugar perspective, I'd love to be able to combine the convenience of v-for with the optimizations offered by <keep-alive>. As it's currently implemented, I must "unroll" the v-for and explicitly do each element, wrapped in <keep-alive>, which removes the incredible convenience of v-for and also makes it more difficult to maintain generic/reusable and dynamic components.

instead of using v-for + v-if, use a computed property to filter the array
Improvements on docs are always welcome 🙂

Great suggestion. Thanks for you help. I'll submit a doc PR. Thanks.


Add support for get and set when translating properties

C# properties appear are translated into individual getters and setter methods, but for some reason they don't use the native javascript get and set language constructs.
https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Functions/get
https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Functions/set
The fact that getters and setters are not translated with the same language semantic causes issues when attempting to share C# classes on both client and server as well as with serialization of data.
The following forum post discusses this and references that perhaps this could be a compilation setting in order to provide backward compatibility for older browsers. Could this be implemented as a new feature or is there someway to accomplish this via the plugin framework?
http://forums.bridge.net/forum/community/help/385-typescript-properties

Our plan is to implement this change in Bridge 16.0. We agree that it absolutely must be done.
Also being tracked in #1229.


Feature Request - Cross-Compile Powershell for PowerPC (PPC) architecture

Cross-compile Powershell to PowerPC (ppc) architecture.
This would allow Powershell to be utilized on IBM hardware (Power-series) which run RHEL, UNIX, and other *nixes.
As a sys admin with a work environment that is split between VMWare and IBM Power-series frames. Having powershell available on both platforms would allow a unified approach to managing them.
This idea was already mentioned on UserVoice a while ago, but it hasn't gained much reach. So I am not aware of how many users would find this beneficial.
Here is a link:
https://windowsserver.uservoice.com/forums/301869-powershell/suggestions/33127174-powershell-core-on-ibm-power-series-hardware

@bwright86 PowerShell Core is based on .Net Core and can only works on OSes which is supported by .Net Core.
You can find supported OS list here https://github.com/dotnet/core/blob/master/release-notes/3.0/3.0-supported-os.md
There is no support for PowerPC.
You should move your feature request to .Net Core repo.


Requests by Bibliographic Data

Currently, it is not possible to use this tools for all publications without a DOI or PMID. The WoS AMR allows to ask with any (?) combination of bibliographic data elements, e.g. Journal title + Volume + Issue - Start page. Any plans to support such requests here as well?

It's actually already possible for any element except authors with lookup_ids.py, though undocumented. For example, take this input csv:
PMID,DOI,UT,atitle,stitle,year
,,,weighted median filters: A tutorial,IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL SIGNAL PROCESSING,1996
,,000203011100014,,,

I believe you can use any combination of: Article title, journal title, ISSN, ISBN, volume, issue, year, starting page, author(s), UT, DOI, or PMID [info]. I think the combination of elements must map to a single result or no results are returned.

Addressed with https://github.com/Clarivate-SAR/wos-amr/commit/4c494267c44731a5e475a315193e4feae7ae5e87


Paypal Express: Support specifying :brand_name

Following https://cms.paypal.com/us/cgi-bin/?cmd=_render-content&content_ID=developer/e_howto_api_soap_r_SetExpressCheckout

Replaced with a more generic #250


I changed the public key link for the glibc sequence in the dockerfile since sgerrand warns us to update it ASAP (Cf. https://github.com/sgerrand/alpine-pkg-glibc/#please-note).
Regards.

Thank you (:


Separate true model parameters from the parameters used for approximation

A true model is an infinite, continuous model with a single solution.
There are many ways to approximate such a model with finite agents and discretization of continuous spaces.
The parameters pertaining to approximation shall be separate from the parameters of the true model.

One approach to this has been implemented already by @alanlujan91 in the SHARKFin AgentPopulation class.


Exposing the default_root_object setting on CloudFront for the redirect

We are using this awesome module for redirection, but found that our destination site does not have an index.html file which is presently hard-coded here
Exposed the setting as a variable which defaults to the original hard-coded value so that we do not break existing deployments.
Happy to update with feedback / changes.
Many thanks!

Merged & tagged as 3.0.6


Client Allocation Request for: 上海源信网络科技有限公司

Client Allocation Questions
Core Information

Name: 上海源信网络科技有限公司
Website / Social Media: https://www.yuanxinw.com
Region: Greater China
DataCap Requested: 5TiB
Addresses to be Notarized: f172xyt6ssmmikjbvgurqlkjojvfbqamepygg35zi
Notary Requested: Broz221

Thanks for your application.
Please answer following questions:
What's your name? What's your duty in this company? Please give me your E-mail address and your brief introduction.
Please give me simple overview of your company. (Company scale, establish time, project, use case, etc.)
What's you/your company's contribution to Filecoin? (If exsit)
What kind of data do you want to store? And how much? How about copy right of data?
How many miners do you want to store data to? Which aspect will you inspect these miners?
Could please you introduce your past usage of cloud storage?


manipulation

Hi Xiaohang, I ran your demos and the results are amazing. However, I do not find codes related to image manipulation such as delete, shift, reposition, and swap as you mentioned in your paper. Is it possible to also provide this part? Thanks a lot!

See https://github.com/XiaohangZhan/deocclusion-demo

Thank you for your reply!


SessionID

Hello,
how Can I get my sessionID when i'm logged in with this?

Please read README file again.

Hello,
There is only written stuff about the steam ID but i need the Session ID of the current login or am I blind?

This library uses standard PHP sessions, so you can use this:
http://php.net/manual/en/function.session-id.php

I need the sessionID from the steamcommunity page can you help me?


Update deploy-cloud-witness.md

Grammatical correction.

@himanshu-ram-punjabi - thanks for submitting this typo fix!


question

I have honor band 5 and it seems the app cannot discover the smart band, how can you help me fix it?

@AkiraDate BleController supports standard Bluetooth protocols according to https://www.bluetooth.com/specifications/gatt/services/  , so please make sure that your device has the service protocols and exposes to developers. Besides that, please pay attention to our SensorsController part under Client Development section in Development Guide https://developer.huawei.com/consumer/en/doc/development/HMSCore-Guides/sensorscontroller-develop-0000001050069728
Please let us know if this is helpful. We will keep following up under this post.

@AkiraDate BleController supports standard Bluetooth protocols according to https://www.bluetooth.com/specifications/gatt/services/  , so please make sure that your device has the service protocols and exposes to developers. Besides that, please pay attention to our SensorsController part under Client Development section in Development Guide https://developer.huawei.com/consumer/en/doc/development/HMSCore-Guides/sensorscontroller-develop-0000001050069728
Please let us know if this is helpful. We will keep following up under this post.

I already did it the way on the development guide and your code so I'm in a bind now

@AkiraDate Can you discover the smart band by BleController now? Before you register a listener for it, please call the saveDevice() method.


Words learned options: pronounce word

As a user
I want to listen to the pronunciation of a word
To learn how to say it
---------- Acceptance criteria ----------
On new lesson screen, on every word from the words learned

Show next to it the pronunciation button.
When user clicks the pronunciation button

Play the sound of that word.
Show the word that explains how to pronounce it.

Learn how to use Google's Translate API or any other source to play the pronunciation of a word.