text:
shadow-dom 模式下 css 不挂载到全局

这个插件不错👍，先前是自己写 vite 脚本调整的，但是 dev 模式并不好，看到你这个插件，想切换过来。但是发现这个插件默认把样式注入到全局了，没看到关的地方。对于油猴插件为了不受全局样式影响，shadow-dom 是不错的选择。因此需要把样式替换到 /* global-placeholder */ 占位符上。
两个方案

关闭此插件的 css 全局注入
集成 shadow-dom 模式的 /* global-placeholder */ 占位符替换。

怎么快速让样式插入到我这个占位符上呢？

先前写过的脚本。

const bundle = (mode: string): PluginOption => {
  const placeholder = '/* global-placeholder */';
  let global_css: string | null = null;
  return {
    name: 'build:bundle',
    enforce: 'post',
    async buildStart() {
      global_css = null
    },
    generateBundle(_options, bundle) {
      console.log('');
      console.log('=======>', Object.keys(bundle));

      const css_assets = Object.values(bundle).map(o => o.type === 'asset' && o.fileName.endsWith('.css') ? o : undefined).filter(o => o !== undefined);
      if (css_assets.length > 0) {
        global_css = css_assets.map(o => (typeof o.source === 'string' ? o.source : new TextDecoder().decode(o.source)).trim()).join(' ').replace(/\\/g, '\\\\') ?? '';
      }

      if (!global_css) {
        return;
      }

      let replaced = false;
      for (const chunk of Object.values(bundle)) {

        if (chunk.type === 'chunk') {
          const code = typeof chunk.code === 'string' ? chunk.code : new TextDecoder().decode(chunk.code);
          if (code.includes(placeholder)) {
            chunk.code = `${banner}${code.replace(placeholder, global_css)}`;
            replaced = true;
          }
        }
      }

      if (mode === 'production' && replaced) {
        for (const key of Object.keys(bundle)) {
          const file = bundle[key];
          if (file.type === 'asset' && file.fileName.endsWith('.css')) {
            delete bundle[key];
          }
        }
      }

    }
  }
};

我实现了 Build 的 placeholder 替换，请问 serve dev 下的替换怎么搞？

@lisonge  你好，我提交了 PR，请指导下，怎么让 placeholder 在 vite serve dev 下生效？

你的改动会造成 serve 与 build 模式下的行为不一致
import './xxx.css' 这类代码被 vite 视为全局样式
vite 目前暂未支持 shadow-dom 下 css  https://github.com/vitejs/vite/pull/12206
目前看起来 shadow-dom 下的 css 只能使用 css?inline 实现，而且失去了 hmr
import cssText from './style.css?inline';

const style = document.createElement('style');
style.textContent = cssText;
shadow.appendChild(style);

vite 下使用 Web components 的 lit 示例
template-lit-ts/src/my-element.ts
也是使用 内联 css

我用了 unocss ，没有单独的 style.css 文件，是动态生成的。

unocss 的 shadow-dom 的 placeholder 也好像有问题，它只管那个组件文件的 css，像油猴插件，其实就是最外层的组件才是 shadow-dom，需要把所有样式收集，放到 shadow–dom 的 <style>标签里</style>.

你为什么不在 vite-plugin-monkey 前面加一个插件把 css 移动到 js 里
好像没必要修改  vite-plugin-monkey 源代码

嗯，好像也可以。把我之前写的脚本放在  vite-plugin-monkey 之前就行了。到  vite-plugin-monkey 就没 css 给它注入了。
build 和 serve 行为不一致，你有什么思路，也通过插件来快捷的解决吗？上面你引用的 PR 貌似没那么容易合并。

谢谢你的耐心解答，我改成这样完美解决了，开发模式去 Head 上取样式，放到 shadow dom 里，生产模式就用 placeholder 替换。
SolidJs 完美啊，代码可以写的这么简洁。

如果 unocss 支持直接导出 原生 style 对象，生产模式 额外的插件 也不需要了
import unocssStyle from 'virtual:uno.css?style';

render(
  () => (
    <Portal useShadow>
        {unocssStyle}
        <App />
      </Portal>
  ),
  document.body,
);```

我上面的写法相当于启动后将 head 里的 styledom 对象移动到了 shadowdom 里，hmr 也都正常。

使用 unocss 现在看起来现在还是得自行处理才能更好的 HMR？

https://github.com/unocss/unocss/pull/2570#issuecomment-1666584117

我也遇到类似情况，用UnoCSS，外面套一层shadowDOM，但用的内联样式。
研究了几天，目前热更新和构建都可以了，但单文件组件内的style块不知道怎么引入到代码里，还没想到好的办法。
大致上就是UnoCSS里面加了一下内联的判断（默认情况resolveId阶段会把query丢掉），修改了virtual:uno.css转换使其兼容UnoCSS的HMR转换，然后开发模式下触发模块重载，构建模式下在JS里替换，详细方式写在这里了：https://github.com/unocss/unocss/issues/4137#issuecomment-2501112854 ，供各位参考

authors: UnluckyNinja lisonge mokeyish yunsii

repo: lisonge/vite-plugin-monkey


text:
Security Concern with Credetials.

I work for an organization which has a security concern with saving credentials using either the vscode settings.json file or the *.target.properties files as they would be saved in clear text on the users' disk. Instead, it would be great if we could utilize vscode's account provider which would save the credentials within the users' keystore.

Interesting feature, I don't have time for it now, but you are welcome to contribute to the project!

source: gharchive/issue

authors: lispercat parithon

repo: lispercat/sailpoint-iiq-dev-accelerator

license: MIT

license_type: permissive

license_source: github-api


text:
[New] all Scenario methods to show figures accept controll arguments of figures

Summary of this new feature
All methods of Scenario class to show figures, including .history() and .simulate(), are expected to accept controll  arguments of cs.line_plot() function. e.g. ylim=(0, None) to set y range.
(Optional) Solution
Add **kwargs to Scenario.history() etc. so that we can controll cs.line_plot() function internally called.

This is related to #503.

This is related to #503.

This is related to #495.

This is related to #495.


text:
'🦟[Bug Report]'  Request Received

This ticket was escalated from Zendesk by Kerry Washington:
Ticket: #3171
Type: Incident
Priority: -
Requester: Tysonismg2
Organization: -
Assignee: Kerry Washington

Describe the bug

To Reproduce
Steps to reproduce the behavior:

Go to '...'
Click on '....'
Scroll down to '....'
See error

Expected behavior
A clear and concise description of what you expected to happen.
Screenshots or GIFs
If applicable, add screenshots or GIFs to help explain your problem.
Mobile device (please complete the following information):

Device: [e.g. Pixel 4]
OS: [e.g. Android 25]
Litewallet Version [e.g. v1.19.3]

Additional context
Add any other context about the problem here.
Attachments: Image.jpeg 422E0C35D8B649F18D70BAC676486335.png 39CA7F723372412EA30A339DCFDFB349.png 8E07055AD1064E6CB4EBD4E054273F37.png 2F12F08DEEE441EE9013E579E4CA1391.png 535D79F6DBC04713B16A38F5E922F96C.png 9FFB70ACC7BB4EFB937F32E5DD364362.png 33D53F145338498F85347C69FD7031D4.png 026A3866D6764E66958CAA242165A4E2.png 6B0CF4BD9562422DAF3CF836D95D669B.png A30A3A86A323438285040AB4E519434B.png(created from Zendesk ticket #3171) gz#3171

Agent comment from Kerry Washington in Zendesk ticket #3171:Hi,
We think this issue is resolved and we'll close  this ticket now.
Regards
The Litewallet Team
Kerry Washington
Litewallet Team Manager
°°°

Agent comment from Kerry Washington in Zendesk ticket #3171:Hi,
We think this issue is resolved and we'll close  this ticket now.
Regards
The Litewallet Team
Kerry Washington
Litewallet Team Manager
°°°

Resolved

repo: litecoin-foundation/litewallet-android


text:
Bug: serializer not working with misleading message

Description
I had some problems with a serializer not working, and displaying an error message I couldn't decipher.
The issue was a SQLAlchemy relationship that was defined using a string type instead of the type itself:
conditions: Mapped[list["AlertTemplateCondition"]] = relationship(back_populates="alert_template")
When I was trying to serialize this object and its children, this error was raised:
Traceback (most recent call last):
  File "/home/0xSwego/projects/litestar-backend-template/.venv/lib/python3.10/site-packages/litestar/serialization/msgspec_hooks.py", line 141, in encode_json
    return msgspec.json.encode(value, enc_hook=serializer) if serializer else _msgspec_json_encoder.encode(value)
  File "/home/0xSwego/projects/litestar-backend-template/.venv/lib/python3.10/site-packages/litestar/serialization/msgspec_hooks.py", line 88, in default_serializer
    raise TypeError(f"Unsupported type: {type(value)!r}")
TypeError: Unsupported type: <class 'app.domain.alerts.models.AlertTemplateCondition'>

Removing the quotes from the type fixed the issue:
conditions: Mapped[list[AlertTemplateCondition]] = relationship(back_populates="alert_template")
It'd be great if the right serializer was found even if the type is written in quotes.
URL to code causing the issue
No response
MCVE
Models:
class AlertTemplate(orm.DatabaseModel):
    __tablename__ = "alert_templates"  # type: ignore[assignment]

    conditions: Mapped[list["AlertTemplateCondition"]] = relationship(back_populates="alert_template")

class AlertTemplateCondition(orm.DatabaseModel, orm.AuditColumns):
    __tablename__ = "alert_template_conditions"  # type: ignore[assignment]

    alert_template_id: Mapped[UUID] = mapped_column(ForeignKey("alert_templates.id"))
    alert_template: Mapped[AlertTemplate] = relationship()

DTOs:
class AlertTemplateDTO(SQLAlchemyDTO[AlertTemplate]):
    config = dto.config(max_nested_depth=1)

class AlertTemplateConditionDTO(SQLAlchemyDTO[AlertTemplateCondition]):
    config = dto.config(max_nested_depth=0)

Controller:
class AlertTemplatesController(Controller):
    """Handles the interactions within the AlertTemplate objects."""

    dependencies = {"alert_template_service": provide_alert_template_service}
    return_dto = AlertTemplateDTO

    @get(
        operation_id="ListAlertTemplates",
        name="alert_templates:list",
        summary="List Alert Templates",
        path=urls.ALERT_TEMPLATES_LIST,
    )
    async def list_alert_templates(
        self,
        alert_template_service: AlertTemplateService,
    ) -> OffsetPagination[AlertTemplate]:
        """List all alert templates"""
        results = await alert_template_service.list()
        return alert_template_service.to_dto(results)

Litestar Version
2.0.1
Platform

[X] Linux
[ ] Mac
[X] Windows
[ ] Other (Please specify in the description above)

Funding

If you would like to see an issue prioritized, make a pledge towards it!
We receive the pledge once the issue is completed & verified

Could you provide a minimal reproduction of the bug?

@guacs sure! I have taken the litestar-fullstack repo and added the code that is causing the problem:
https://github.com/0xSwego/litestar-fullstack/tree/master
I've also added a test that fails due to the error. Running pytest tests/integration/test_alerts.py will trigger it

@0xSwego I'm having some trouble reproducing this. Could you provide a minimal example with a minimal self-contained application (not the litestar-fullstack one)?

@0xSwego any updates on this?

@guacs I wouldn't know where to start from and it would take me a huge amount of time. If the issue cannot be reproduced because you have troubles with the code, I can close it.

@guacs I wouldn't know where to start from and it would take me a huge amount of time. If the issue cannot be reproduced because you have troubles with the code, I can close it.

Let me try once more to reproduce this. If I'm not able to, then we can close it.

@guacs you should be able to set up the whole project with the make install command (Unix friendly, unfortunately. I am on Windows and use WSL)

@guacs any updates?

I'm closing this since I haven't been able to create an MCVE for this. If anyone faces this issue and can provide an MCVE, please feel free to reopen the issue.

authors: 0xSwego guacs provinzkraut

repo: litestar-org/litestar


text:
feat(istio): Adding support to run in istio enabled mode

Signed-off-by: shubhamchaudhary shubham.chaudhary@mayadata.io
fixes: litmsuchaso/litmus#1474

Another PR will be needed in chaos-runner to look for chaos-container only in  the chaos-pod

time="2020-07-16T20:37:08Z" level=info msg="[PreReq]: Getting the ENV for the  experiment"
time="2020-07-16T20:37:08Z" level=info msg="[PreReq]: Updating the chaos result of pod-network-loss experiment (SOT)"
time="2020-07-16T20:37:12Z" level=info msg="The application informations are as follows\n" Label="run=nginx" Ramp Time=10 Namespace=shubham
time="2020-07-16T20:37:12Z" level=info msg="[Status]: Verify that the AUT (Application Under Test) is running (pre-chaos)"
time="2020-07-16T20:37:12Z" level=info msg="[Status]: Checking whether application pods are in running state"
time="2020-07-16T20:37:12Z" level=info msg="The running status of Pods are as follows" Pod=nginx-6876f9c9f8-kjtmx Status=Running
time="2020-07-16T20:37:12Z" level=info msg="[Status]: Checking whether application containers are in running state"
time="2020-07-16T20:37:12Z" level=info msg="The running status of container are as follows" container=istio-proxy Pod=nginx-6876f9c9f8-kjtmx Status=Running
time="2020-07-16T20:37:12Z" level=info msg="The running status of container are as follows" Pod=nginx-6876f9c9f8-kjtmx Status=Running container=nginx
time="2020-07-16T20:37:12Z" level=info msg="[Info]: Details of application under chaos injection" PodName=nginx-6876f9c9f8-kjtmx NodeName=gke-docker-default-pool-f23806ea-qrsb ContainerName=nginx
time="2020-07-16T20:37:12Z" level=info msg="[Ramp]: Waiting for the 10s ramp time before injecting chaos"
time="2020-07-16T20:37:22Z" level=info msg="[Status]: Checking the status of the helper pod"
time="2020-07-16T20:37:22Z" level=info msg="[Status]: Checking whether application pods are in running state"
time="2020-07-16T20:37:28Z" level=info msg="The running status of Pods are as follows" Pod=pumba-netem-kslush Status=Running
time="2020-07-16T20:37:28Z" level=info msg="[Status]: Checking whether application containers are in running state"
time="2020-07-16T20:37:32Z" level=info msg="The running status of container are as follows" container=istio-proxy Pod=pumba-netem-kslush Status=Running
time="2020-07-16T20:37:32Z" level=info msg="The running status of container are as follows" container=pumba Pod=pumba-netem-kslush Status=Running
time="2020-07-16T20:37:32Z" level=info msg="[Wait]: Waiting for 60s till the completion of the helper pod"
time="2020-07-16T20:37:32Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:33Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:34Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:35Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:36Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:37Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:38Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:39Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:40Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:41Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:42Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:43Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:44Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:45Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:46Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:47Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:48Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:49Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:50Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:51Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:52Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:53Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:54Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:55Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:56Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:57Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:58Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:37:59Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:00Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:01Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:03Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:04Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:05Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:06Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:07Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:08Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:09Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:10Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:11Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:12Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:13Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:14Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:15Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:16Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:17Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:18Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:19Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:20Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:21Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:22Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:23Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:24Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:25Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:26Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:27Z" level=info msg="helper pod status: Running"
time="2020-07-16T20:38:27Z" level=info msg="The running status of Pods are as follows" Pod=pumba-netem-kslush Status=Running
time="2020-07-16T20:38:27Z" level=info msg="[Cleanup]: Deleting the helper pod"
time="2020-07-16T20:38:46Z" level=info msg="[Ramp]: Waiting for the 10s ramp time after injecting chaos"
time="2020-07-16T20:38:56Z" level=info msg="[Confirmation]: The pod network loss chaos has been applied"
time="2020-07-16T20:38:56Z" level=info msg="[Status]: Verify that the AUT (Application Under Test) is running (post-chaos)"
time="2020-07-16T20:38:56Z" level=info msg="[Status]: Checking whether application pods are in running state"
time="2020-07-16T20:38:56Z" level=info msg="The running status of Pods are as follows" Pod=nginx-6876f9c9f8-kjtmx Status=Running
time="2020-07-16T20:38:56Z" level=info msg="[Status]: Checking whether application containers are in running state"
time="2020-07-16T20:38:56Z" level=info msg="The running status of container are as follows" Pod=nginx-6876f9c9f8-kjtmx Status=Running container=istio-proxy
time="2020-07-16T20:38:56Z" level=info msg="The running status of container are as follows" Status=Running container=nginx Pod=nginx-6876f9c9f8-kjtmx
time="2020-07-16T20:38:56Z" level=info msg="[The End]: Updating the chaos result of pod-network-loss experiment (EOT)"

source: gharchive/pull-request

repo: litmuschaos/litmus-go


text:
Draining 100% memory of a Kubernetes pod running on a node for Certain duration

This issue is for adding stress images for the pod memory hog experiment. The building of the image should be done in litmuschaos/test-tools repository. The image should contain a job that will basically be used to exec in a container and give a memory spike for the given chaos duration with a given memory consumption.

I tried several commands to achieve this the best one which fits this usecase is:
cat <( yes | tr \\n x | head -c $BYTES <(sleep $100) | grep n
here $BYTES is replaced with memory in Megabytes  $((1024*1024*800))) and  (sleep $100) means sleeping for 100s.
But one issue in this was:
The moment it reaches the memory we mentioned ( ((1024*1024*800))) )
The command gets terminated. This means sleep here is not working fine in bash or sh

Another very useful command which can do this task very easily is:
dd if=/dev/zero of=/dev/null bs=300M (300M is memory in megabytes)
This runs multiple times in the background and will drain out the memory very rapidly which in result also use the CPU in very large amount if, we want to drain the memory  in very less time then this seems to be the best one

In case we want to terminate dd if=/dev/zero of=/dev/null bs=300M this command after some time interval we can use timeout for this so the command will become timeout ${chaos-duration} dd if=/dev/zero of=/dev/null bs=300M

Fixed via https://github.com/litmuschaos/test-tools/pull/122

authors: ksatchit uditgaurav

repo: litmuschaos/litmus


text:
Feature Request: Decouple Project and User Creation

Currently, whenever a user is created, a project is automatically created along with it, though there is no way to create a project without creating a user. We want to adopt litmus in our org, but we want to have different projects per squad/domain of our organisation. It would be great to see if we can decouple the concept of the project and the user and also allow adding multiple owners to the project as mentioned in this issue.

What do you think of this issue @Saranya-jena @amityt? If you think it's good, I'll implement this feature.

This issue is currently being worked upon as part of LFX mentorship.


text:
Adding Remove/Sync pending workflows feature

Proposed changes
Summarize your changes here to communicate with the maintainers and make sure to put the link of that issue
Types of changes
What types of changes does your code introduce to Litmus? Put an x in the boxes that apply

[ ] New feature (non-breaking change which adds functionality)
[ ] Bugfix (non-breaking change which fixes an issue)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] Documentation Update (if none of the other choices applies)

Checklist
Put an x in the boxes that apply. You can also fill these out after creating the PR. If you're unsure about any of them, don't hesitate to ask. We're here to help! This is simply a reminder of what we are going to look for before merging your code.

[ ] I have read the CONTRIBUTING doc
[ ] I have signed the commit for DCO to be passed.
[ ] Lint and unit tests pass locally with my changes
[ ] I have added tests that prove my fix is effective or that my feature works (if appropriate)
[ ] I have added necessary documentation (if appropriate)

Dependency

Please add the links to the dependent PR need to be merged before this (if any).

Special notes for your reviewer:

@rajdas98 can this be closed? Ref: PR #2869


text:
ID每次都会变，能否通过ID找出联系人的备注或昵称？

如题。。。

@PythonFu itchat.get_friends(userName = theUserNameYouHave)

authors: PythonFu littlecodersh

repo: littlecodersh/ItChat


text:
🛑 USTC Mirrors is down

In b1eb9c9, USTC Mirrors (https://mirrors.ustc.edu.cn) was down:

HTTP code: 0
Response time: 0 ms

Resolved: USTC Mirrors is back up in 9051d96.

repo: littlekud/sites-status


text:
🛑 USTC Mirrors (Cmcc) is down

In cd35f11, USTC Mirrors (Cmcc) (https://cmcc.mirrors.ustc.edu.cn) was down:

HTTP code: 0
Response time: 0 ms

Resolved: USTC Mirrors (Cmcc) is back up in 982e2b4 after 8 minutes.


text:
feat(font): optionally override font settings

Add the following optional defines to override default font settings:

LV_FONT_DEFAULT: change the default from &lv_font_roboto_16
LV_FONT_ROBOTO_12=1: include Roboto 12pt font (not included by default)
LV_FONT_ROBOTO_22=1: include Roboto 22pt font (not included by default)

These changes were recommended by #54 .

Thank you.
I'm going to add a few conditionals around related macros, for completeness. For some reason I wasn't able to push it to this PR so I'll push it to master

authors: amirgon cfobel


text:
Add online-loading Kinetics-400 Datastet to train TANet

Since there are too many video frames in Kinetics-400 Dataset, it will lead to large disk cost if we extract all the frames in the ~300k videos. So we propose an online method. Through this, we can just input the video and extract the specific frames in the cache instead of storing in disk.

Since there are too many video frames in Kinetics-400 Dataset, it will lead to large disk cost if we extract all the frames in the ~300k videos. So I propose an online method. Through this, we can just input the video and extract the specific frames(after get the sample_indices) in the cache instead of storing in disk.

repo: liu-zhy/temporal-adaptive-module


text:
Support type parameters in def macros

The transform should take type parameters into consideration and handle PolyType.

It seems inlining makes this feature difficult to implement without sacrificing type safety.
Given the macro definition:
class eden {
  inline def as[T](a: Any): Any = meta {
    val tp = T.asInstanceOf[scala.meta.Type]
    val term = a.asInstanceOf[scala.meta.Term]
    q"$term.asInstanceOf[$tp]"
  }
}

We transform it into the follows:
class eden {
  inline def as[T](a: Any): Any = meta { eden$inline.as(this)(a) }    //   <= how to pass T?
}

object eden$inline {
  def as(prefix: Any)(T: Any)(a: Any): Any = {
    val tp = T.asInstanceOf[scala.meta.Type]
    val term = a.asInstanceOf[scala.meta.Term]
    q"$term.asInstanceOf[$tp]"
  }
}

But in the meta block above, how do we pass T to the implementation, so that inlining & type safety are not compromised?
Note that without inlining, we don't face this problem, as we don't have the call eden$inline.as(this)(a) as part of the code.

Type parameters are supported in e9e392bac516612ccca6b44057f2937ed61f8373. I ended up doing away with the complication of inlining. I resort to a special flag macro to tell whether to expand a macro or not. https://github.com/liufengyun/dotty/commit/ef16d23360e075b3e23db99158d62859a55526dd
It seems we can implement macros much simpler without inlining. Inlining is itself another category of useful macros with better foundation. Mix them together seems to make both harder.

Nice progress! Am I right in thinking that you only support meta blocks that are the sole right-hand sides of inline methods (by translating such methods into <macro> something)?

Yes, the translation is the same before, except we remove the inline flag and add macro flag, to avoid inlining.
I don't know how to translate meta blocks that are in the middle of an expression and reflectively expand such meta blocks.

Improvement of typing to avoid asInstanceOf boilerplate is now implemented in https://github.com/liufengyun/dotty/commit/26ee23a1624e728da761506775caf7b2559ef187 and https://github.com/liufengyun/eden/commit/acc43d3f9b6f451ca3edb34ec05812d483248e99 .

Close this for now.

authors: liufengyun xeno-by

repo: liufengyun/eden

license_source: bigquery


text:
moving documentation from src

It’s very fastest mapper, which I have ever seen!!!
Good work!
You need to move documentation from src to readme.md and add some examples.
It’s help people know how to use it.

updated the readme and added the wiki. Thank you @sigma7i

repo: liuhongbo/RoslynMapper


text:
当网络不稳定会报如下错误

比如在电梯里不稳定，然后出了电梯回报如下错误，然后导致App闪退。
java.net.SocketException: Software caused connection abort
at java.net.SocketInputStream.socketRead0(Native Method)
at java.net.SocketInputStream.socketRead(SocketInputStream.java:119)
at java.net.SocketInputStream.read(SocketInputStream.java:176)
at java.net.SocketInputStream.read(SocketInputStream.java:144)
at okio.InputStreamSource.read(JvmOkio.kt:90)
at okio.AsyncTimeout$source$1.read(AsyncTimeout.kt:129)
at okio.RealBufferedSource.indexOf(RealBufferedSource.kt:427)
at okio.RealBufferedSource.readUtf8LineStrict(RealBufferedSource.kt:320)
at okhttp3.internal.http1.HeadersReader.readLine(HeadersReader.kt:29)
at okhttp3.internal.http1.Http1ExchangeCodec.readResponseHeaders(Http1ExchangeCodec.kt:178)
at okhttp3.internal.connection.Exchange.readResponseHeaders(Exchange.kt:106)
at okhttp3.internal.http.CallServerInterceptor.intercept(CallServerInterceptor.kt:79)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.connection.ConnectInterceptor.intercept(ConnectInterceptor.kt:34)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.cache.CacheInterceptor.intercept(CacheInterceptor.kt:95)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.http.BridgeInterceptor.intercept(BridgeInterceptor.kt:83)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.http.RetryAndFollowUpInterceptor.intercept(RetryAndFollowUpInterceptor.kt:76)
at okhttp3.internal.http.RealInterceptorChain.proceed(RealInterceptorChain.kt:109)
at okhttp3.internal.connection.RealCall.getResponseWithInterceptorChain$okhttp(RealCall.kt:201)
at okhttp3.internal.connection.RealCall$AsyncCall.run(RealCall.kt:517)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1167)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:641)
at java.lang.Thread.run(Thread.java:919)
Suppressed: kotlinx.coroutines.DiagnosticCoroutineContextException: [StandaloneCoroutine{Cancelling}@eeba24d, Dispatchers.Main.immediate]

结合协程发请求，你需要手动捕获异常(设置异常回调)，才不会闪退

怎么捕获异常，有文档吗？

https://github.com/liujingxing/rxhttp/blob/master/README_zh.md#3相关文档

好的，谢谢了

repo: liujingxing/rxhttp


text:
How are CDR3 scores calculated?

I have a quick question about the definitions of the various "scores" indicated in the different file types. In particular, in the _cdr3.out file, there is a column called CDR3_score and another called CDR3_germline_similarity. I was checking how these are related and I found that the CDR3_score is highly discretized:
>> cdr3['CDR3_score'].value_counts()
CDR3_score
0.00    87094
1.00    28042
0.83    15706
0.67    14229
0.01     7305
0.50     6924
0.33      297
0.17       33
Name: count, dtype: int64

It only appears to take on values of 0, 0.01, 1/6, 1/3, 1/2, 2/3, 5/6, 1. Is this expected?
On the other hand, I'm assuming that CDR3_germline_similarity is the Hamming distance to the reference or something?
Thanks for your help!

For the scores, 0 means partial CDR3, 0.01 means CDR3 contains imputation sequence (based on the germline TCR sequence), 0.5 is rescued CDR3 sequence like due to very short anchor on V,J genes, the other numbers are x/6, where x is the number of satisfied motifs around CDR3 (YYC at 5', F/WGxG at the 3' end).

The germline similarity is the fraction of match in the edit distance to the overlapped germline V and J gene within the CDR3 region.

Thank you very much!


text:
[feature]Enable audio play at background and lockscreen.

Is your feature request related to a problem? Please describe.
Enable audio play at background when screen is locked and show lock screen widget.
Describe the solution you'd like
when screen is locked or app moved to back ground, the room should still be connected and audio should still play. If possible, video should also minimize to a picture in picture video. If screen is locked, then room should still connect and audio should still play. There also should be a lock screen widget.
Describe alternatives you've considered
There doesn't need to be audio play pause option on the lock screen widget. Just to make sure it is showing there, reminding users of connecting to the room and playing audio.
Additional context

duplicated https://github.com/livekit/client-sdk-flutter/issues/534

repo: livekit/client-sdk-flutter


text:
Enqueue Signal requests while reconnecting

But should we wait to send the queued requests until engine reconnected (Ice connected) ?
or it's ok to just send when signal is connected. 🤔

But should we wait to send the queued requests until engine reconnected (Ice connected) ? or it's ok to just send when signal is connected. 🤔

I think we need to wait until ICE is re-established. we also need to ensure that SyncState can always be sent and not queued.

But should we wait to send the queued requests until engine reconnected (Ice connected) ? or it's ok to just send when signal is connected. 🤔

I think we need to wait until ICE is re-established. we also need to ensure that SyncState can always be sent and not queued.

Got it ! We might need to change the JS SDK too https://github.com/livekit/client-sdk-js/commit/51086e368f3ccb2225a29df636b39d5a42564c24

Got it ! We might need to change the JS SDK too livekit/client-sdk-js@51086e3

yeah you are right. will look into it.

authors: davidzhao hiroshihorie

repo: livekit/client-sdk-swift


text:
Don't spam callback URL with Progress callbacks

Currently we send one after every transcoded segment, but should figure out a way to do 1 every X seconds.
@victorges suggested:

you could probably copy 100% of this progress reporter from the task-runner (we could move it to some shared utils lib at some point)
https://github.com/livepeer/task-runner/blob/13db95e3b5c784119d200629e443a32349d899d4/task/progress.go#L35
actually, would only need to change what it does when it "sends a progress update" here
https://github.com/livepeer/task-runner/blob/13db95e3b5c784119d200629e443a32349d899d4/task/progress.go#L115

Closed by #218
cc @thomshutt

repo: livepeer/catalyst-api


text:
Bounty: React Native Demo Live Streaming Application

Livepeer's API at livepeer.com make it very simple to create a live streaming application.
This task is to create an example live streaming application in react native, so can serve as a starting point for a mobile app on Android and iOS.  The application should:

Allow an user to enter an API key
Allow an user to create a stream
Allow an user to "go live"
Allow an user to view the HLS video in app
Allow an user to share the playback URL (can use something like: https://hls-js.netlify.app/demo/?src={playback_url})
Contain clear documentation, so it can be easily modified for other use cases

There are 3 steps for this bounty:

Create a wireframe that satisfies the above requirements, get feedback from the Livepeer team about the wireframe.
Implement the application.
Iterate with the Livepeer team to ensure the application works according to expectation.

👋🏽

authors: ericxtang jozanza

repo: livepeer/livepeer-demo-react-native


text:
No way to exit out of progress box for many uploads

Currently, if a user uploads a bunch of files on the dashboard, the progress box on the bottom right expands to show the progress. Right now, if there are too many, it's not possible to scroll or exit the box.

Complete, handled by @clacladev

repo: livepeer/studio


text:
Feature: allow empty remotePath and use default path

Some servers occasionally change remote paths for load-balancing purposes, so they recommend leaving the path empty and using the default home directory; manually setting a remotePath in these cases will eventually lead to permission and/or path not found errors.
Is something like this possible?

Nevermind, it seems using: "remotePath": "./", works

repo: liximomo/vscode-sftp


text:
Remote Browser: Wrong Directory with similiar name

Hello, I'm having a weird issue with the remote browser.
I have two sub folder in wordpress and they are called like this:

wp-content

themes

Divi
Divi Child Theme

Basically, if I try to access 'Divi Child Theme', it shows me 'Divi' folder files
Is this a real or I'm just doing it wrong?

Do you read the FAQ?

[ ] Yes.
[ ] I am going to read now.

Describe the bug
A clear and concise description of what the bug is.
To Reproduce
Steps to reproduce the behavior:

Go to '...'
Run command '....'
See error

Expected behavior
A clear and concise description of what you expected to happen.
Screenshots
If applicable, add screenshots to help explain your problem.
Desktop (please complete the following information):

OS: [e.g. Mac, Win, Linux]
VSCode Version [e.g. 1.27.0]
Extension Version [e.g. 1.7.0]

Extension Logs from Startup - required

Open User Settings.

On Windows/Linux - File > Preferences > Settings
On macOS - Code > Preferences > Settings

Set sftp.debug to true and reload vscode.

Reproduce the problem, get the logs from View > Output > sftp.

authors: demimontalto liximomo


text:
🛑 Movie is down

In 98d9d7d, Movie (http://h.liyaodong.com:8096) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Movie is back up in f7b2fdd.

repo: liyaodong/uptime


text:
graphql and websocket work, but http and https do not

Describe the bug
Doesn't work for http and https requests. I tried enabling the proxy but the same result. It gets cookies and headers from the site, but appears to throw away the content.
To Reproduce
Steps to reproduce the behavior:

Go to postwoman URL (in k8s cluster)
get https://www.google.com
Error: Network Error. Check console for details. Same result with proxy enabled.

Network: headers
GENERAL:
Request URL: https://www.google.com/
Request Method: GET
Status Code: 200
Remote Address: 172.217.14.196:443
Referrer Policy: no-referrer-when-downgrade

RESPONSE HEADERS:
alt-svc: quic=":443"; ma=2592000; v="46,43",h3-Q050=":443"; ma=2592000,h3-Q049=":443"; ma=2592000,h3-Q048=":443"; ma=2592000,h3-Q046=":443"; ma=2592000,h3-Q043=":443"; ma=2592000
cache-control: private, max-age=0
content-encoding: br
content-length: 65078
content-type: text/html; charset=UTF-8
date: Wed, 18 Dec 2019 23:30:16 GMT
expires: -1
p3p: CP="This is not a P3P policy! See g.co/p3phelp for more info."
server: gws
set-cookie: NID=194=Y2K7S1kMidDP1VYy2kySfA0Jo5GcpC29l1lWSCEWxGVSc-0kzP-QimflDXRAEjq4exaeWoWSBCsUnqJcLEhyP9sPRnh4Wv1CvXWW0qow6tkUuvQbUqbH8YHFR6_VFQe9gloFEENVL0-L9SjQXQFovJ7MGOsQ_oCMRO4CuLWyfzw; expires=Thu, 18-Jun-2020 23:30:16 GMT; path=/; domain=.google.com; HttpOnly
status: 200
strict-transport-security: max-age=31536000
x-frame-options: SAMEORIGIN
x-xss-protection: 0

REQUEST HEADERS:
:authority: www.google.com
:method: GET
:path: /
:scheme: https
accept: application/json, text/plain, */*
accept-encoding: gzip, deflate, br
accept-language: en-US,en;q=0.9
origin: https://postwoman.tan.cyndx.io
referer: https://postwoman.tan.cyndx.io/
sec-fetch-mode: cors
sec-fetch-site: cross-site
user-agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) snap Chromium/79.0.3945.79 Chrome/79.0.3945.79 Safari/537.36

Expected behavior
Page pulled from google
Desktop (please complete the following information):

OS: Ubuntu
Browser: chromium-browser
Version: Version 79.0.3945.79 (Official Build) snap (64-bit)

Additional context
It would be super helpful if the request could originate from the server component, that way I could test k8s endpoints from within the private cluster, without exposing any VirtualServices. Get and Post would need to work first... Running the liyasthomas/postwoman:latest container on k8s using CoreOS.

Did you tried any other endpoints? I think https://www.google.com have tight Cross-Origin Resource Sharing policies. Try out with the default endpoint and see if the issue persist.
Read more about CORS: https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS
Possible duplicate of #2

Probably Coors. My personal Grav blog doesn't even load in Postwoman. I have found one site other than reqres.in that does load: an instance of httpbin running in my k8s cluster. I think that the proper fix is to have the "server" make the requests instead of the browser. Until then I don't think I have any choice but to use the tool that works, Postman... :/  You project is great, I wish you the best with it.

authors: liyasthomas mabushey

repo: liyasthomas/postwoman


text:
Adding french language basic

Hello again ! (#354)  Just adding french language basic to prepare the ground.

[x] Added lang/fr-FR.js
[x] Modified nuxt.config.js

No problem for ping me, I will add the words in French without any problems ! :+1:

@thomasbnt new keywords are up! Looking forward on commiting translations ASAP.
Checklist:

[ ] Pull the latest changes from i18n branch
[ ] Find lang/<<your_file>>.js
[ ] Replace existing dummy translations with actual translated lacale (no need to update nuxt.config.js since language is already added once)
[ ] Save changes, Commit changes, Push to i18n branch only

Refer English translation file https://github.com/liyasthomas/postwoman/blob/i18n/lang/en-US.js for reference and stylings. Ping me for any doubts.

@liyasthomas already checked by @LaurentBrieu (https://github.com/liyasthomas/postwoman/pull/364)

We, then it was a mistake. Nevermind. 😊

authors: liyasthomas thomasbnt


text:
Implement HMAC for command and event queue.

Reference https://secure.php.net/hash_equals to mitigate timing leaks.

Can you please explain what you think is todo and why?

authors: Schrank Vinai

repo: lizards-and-pumpkins/catalog


text:
Wrong text appears upon hovering on buttons in Blockrain activity

Text should appear as "Rotate Block" instead of "Up Arrow"

Fixed in https://github.com/llaske/sugarizer/pull/628

authors: abhishektanwar llaske

repo: llaske/sugarizer


text:
Presentation - Lidi & Guy (current)

Lidi - build skeleton
Guy - share research slides.

The power point presentation draft is available in project_presentation (main - based) branch. Please pay attention , there is a new directory called 'presentation' under repo root that contain  presentation and results template files (to update with final scores and put as images into the relevant powerpoint slides)
@GuyYar1  @AlonShm  Guy and Alon, please fill in slides describing data processing , data pipeline and model architecture (especially the last one describing improvements - which need to be extended , maybe with citings and so on)


text:
Feat(codemods): Add codemod to update Tooltip and Dropdown non-flow p…

…lacements #DS-1138

Description

Additional context

Issue reference

coverage: 81.009% (+6.2%) from 74.819%
when pulling 8278d1a63fa7e6b4f3293742df21d1bd789febf9 on feat/codemod-tooltip-dropdown-placement
into 796b843a51e6aefe14f1c189a4e78671297e985e on main.

authors: coveralls crishpeen

repo: lmc-eu/spirit-design-system


text:
Feat(web): Introduce UNSTABLE Toggle component #DS-1345

Description

Additional context

Issue reference

coverage: 77.951%. remained the same
when pulling 7177732ccd082756dff2465d055d76fb335fa1d5 on feat/web-toggle
into bd48607ce4684638e5b52070aa9db88b9d8178b6 on main.

🎩 , I have only a few comments.
During the code review, I came up with a few insights, mostly related to the stable version of this component:

In the Figma it is possible to set if the component has icon or not. This shouldn't be implemented?

2. Should it be possible **change state by clicking on the validation/helper text**? (related to the Checkbox component, where you probably inspired yourself). And I've also noticed that in the example of validation states the danger variant with multiple error messages doesn't have cursor over label.
3. Nitpicking idea for form components: If there would be a composition of various form components, I can imagine that designer would like to have **possibility to set order of the component** (toggle-label or label-toggle), because eg. `Checkbox` has input first and then label. The same applies for transitions between checked/unchecked states.
   ![image](https://private-user-images.githubusercontent.com/33354913/348665320-608cb42d-2cbb-4b92-acb0-8488baf00614.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MjExMTgyMDAsIm5iZiI6MTcyMTExNzkwMCwicGF0aCI6Ii8zMzM1NDkxMy8zNDg2NjUzMjAtNjA4Y2I0MmQtMmNiYi00YjkyLWFjYjAtODQ4OGJhZjAwNjE0LnBuZz9YLUFtei1BbGdvcml0aG09QVdTNC1ITUFDLVNIQTI1NiZYLUFtei1DcmVkZW50aWFsPUFLSUFWQ09EWUxTQTUzUFFLNFpBJTJGMjAyNDA3MTYlMkZ1cy1lYXN0LTElMkZzMyUyRmF3czRfcmVxdWVzdCZYLUFtei1EYXRlPTIwMjQwNzE2VDA4MTgyMFomWC1BbXotRXhwaXJlcz0zMDAmWC1BbXotU2lnbmF0dXJlPTBhMDI0NzEwNjI2MTNkNjdmMmVmMTM2YzE2Mzg1NWIxNjgxYmEzNWZiZGQxYzA4MTAxYzEzMDQwNTgxMzI3NzQmWC1BbXotU2lnbmVkSGVhZGVycz1ob3N0JmFjdG9yX2lkPTAma2V5X2lkPTAmcmVwb19pZD0wIn0.A7xCGwBKwHcHCNdgicO9quxCNZC656W-69eKAFT2lac)

yes, I missed that
it acts the same as in checkbox, the danger state with multiple validation texts is a problem and I will create a topic for our thurday talks, because currently we are causing invalid HTML and I don't know what is the best solution. The current state is as elsewhere (not ideal, but working)
We decided to do this layout now. In relatively short term we plan to split all form components to small pieces and user will be able to combine them as they want.


text:
Parametric UMAP : "n_training_epochs=20" results in training for 200 epochs

Hello!
First, I'd like to thank all contributors for this great resource. Now onto my issue:
I'm using parametric umap with the following parameters
reducer = umap.parametric_umap.ParametricUMAP(n_components=2,min_dist=1,parametric_reconstruction=True,n_training_epochs=20)
However, this results in the network training for 200 epochs.
Thank you!

@erl-j  This also happens for me. I think this is due to the default loss_report_frequency being set to 10. You can see that the .fit call uses loss_report_frequency* n_training_epochs here
for your purposes, you should be able to pass loss_report_frequency=1 to the init
At a high level, I think this is expected behavior (meaning, the actual number of epochs is still correct), though it is deceiving from the keras logs. However, this means that the EarlyStopping callback needs to be adjusted accordingly also, if being used.
It might make sense to change the default loss_report_frequency to 1 and n_training_epochs to 10. What do you think @lmcinnes ?

@erl-j  This also happens for me. I think this is due to the default loss_report_frequency being set to 10. You can see that the .fit call uses loss_report_frequency* n_training_epochs here
for your purposes, you should be able to pass loss_report_frequency=1 to the init
At a high level, I think this is expected behavior (meaning, the actual number of epochs is still correct), though it is deceiving from the keras logs. However, this means that the EarlyStopping callback needs to be adjusted accordingly also, if being used.
It might make sense to change the default loss_report_frequency to 1 and n_training_epochs to 10. What do you think @lmcinnes ?

@erl-j , the '200' epochs is keras semantics. @walid0925 is right, I set the default loss_report_frequency to 10 so we would see the loss reported 10x per epoch. This means that those 200 epochs are actually 20 epochs, split into 10 sub epochs.
I can see how it would be more intuitive to set the default of loss_report_frequency to 1. Right now the default n_training_epochs is set at 1, so the loss would only be reported once by default.
Increasing the n_training_epochs will increase the default number of epochs it takes to train, so it will make training longer.
Generally I'm all for changing the default parameters to what makes the most sense to the most people.

@erl-j , the '200' epochs is keras semantics. @walid0925 is right, I set the default loss_report_frequency to 10 so we would see the loss reported 10x per epoch. This means that those 200 epochs are actually 20 epochs, split into 10 sub epochs.
I can see how it would be more intuitive to set the default of loss_report_frequency to 1. Right now the default n_training_epochs is set at 1, so the loss would only be reported once by default.
Increasing the n_training_epochs will increase the default number of epochs it takes to train, so it will make training longer.
Generally I'm all for changing the default parameters to what makes the most sense to the most people.

https://github.com/lmcinnes/umap/issues/521 brings up the same issue and also suggests we change loss_report_frequency for similar reasons.
I think setting loss_report_frequency to default to 1 would reduce confusion, then if you want to see loss reported sub-epoch, you can just increase loss_report_frequency.
I read through the proposed solutions linked in https://github.com/lmcinnes/umap/issues/521 but didn't see anything that I think would resolve the semantic confusion of seeing e.g. 200 epochs printed in the keras.fit function, and thinking your network was training for 200 epochs instead of 20. Maybe @dylanking42 has a suggestion?

https://github.com/lmcinnes/umap/issues/521 brings up the same issue and also suggests we change loss_report_frequency for similar reasons.
I think setting loss_report_frequency to default to 1 would reduce confusion, then if you want to see loss reported sub-epoch, you can just increase loss_report_frequency.
I read through the proposed solutions linked in https://github.com/lmcinnes/umap/issues/521 but didn't see anything that I think would resolve the semantic confusion of seeing e.g. 200 epochs printed in the keras.fit function, and thinking your network was training for 200 epochs instead of 20. Maybe @dylanking42 has a suggestion?

authors: erl-j timsainb walid0925

repo: lmcinnes/umap


text:
Error in training encoder decoder in Parametric UMAP with 1D vector data.

Hello,
I am trying to fit transform data with Parametric UMAP using Keras architecture for the encoder and decoder as described in docs. The data is of the shape (74096,1) and I have 100 samples for testing. I want to embed to 2D. My architecture is as follows
Setup
    dims = (74096,1)
    latent_dim = 2

Encoder
    encoder_inputs = keras.Input(shape=dims)
    xe = layers.Conv1D(32, 3, activation="relu", strides=2, padding="same",name='conv1')(encoder_inputs)
    xe = layers.Conv1D(64, 3, activation="relu", strides=2, padding="same",name='conv2')(xe)
    xe = layers.Flatten(name='flatten')(xe)
    xe = layers.Dense(16, activation="relu")(xe)
    z_mean = layers.Dense(latent_dim, name="z_mean")(xe)
    z_log_var = layers.Dense(latent_dim, name="z_log_var")(xe)
    z = Sampling()([z_mean, z_log_var])
    encoder = keras.Model(encoder_inputs, [z_mean, z_log_var, z], name="encoder")

 Layer (type)                   Output Shape         Param #     Connected to
==================================================================================================
 input_94 (InputLayer)          [(None, 74093, 1)]   0           []

 conv1 (Conv1D)                 (None, 37047, 32)    128         ['input_94[0][0]']

 conv2 (Conv1D)                 (None, 18524, 64)    6208        ['conv1[0][0]']

 flatten (Flatten)              (None, 1185536)      0           ['conv2[0][0]']

 dense_139 (Dense)              (None, 16)           18968592    ['flatten[0][0]']

 z_mean (Dense)                 (None, 2)            34          ['dense_139[0][0]']

 z_log_var (Dense)              (None, 2)            34          ['dense_139[0][0]']

 sampling_37 (Sampling)         (None, 2)            0           ['z_mean[0][0]',
                                                                  'z_log_var[0][0]']

Decoder
# This simply gets the mirror of the encoder set up
reshape_dims = (encoder.get_layer('conv2').output_shape[1], encoder.get_layer('conv2').output_shape[2])

latent_inputs = keras.Input(shape=(latent_dim))
xd = layers.Dense(16 , activation="relu")(latent_inputs)
xd = layers.Dense(encoder.get_layer('flatten').output_shape[1], activation="relu")(xd)
xd = layers.Reshape(reshape_dims)(xd)
xd = layers.Conv1DTranspose(64, 3, activation="relu", strides=2, padding="same")(xd)
xd = layers.Conv1DTranspose(32, 3, activation="relu", strides=2, padding="same")(xd)
decoder_outputs = layers.Conv1DTranspose(1, 3, activation="sigmoid", padding="same")(xd)
decoder = keras.Model(latent_inputs, decoder_outputs, name="decoder")

Model: "decoder"
_________________________________________________________________
 Layer (type)                Output Shape              Param #
=================================================================
 input_95 (InputLayer)       [(None, 2)]               0

 dense_140 (Dense)           (None, 16)                48

 dense_141 (Dense)           (None, 1185536)           20154112

 reshape_55 (Reshape)        (None, 18524, 64)         0

 conv1d_transpose_118 (Conv1  (None, 37048, 64)        12352
 DTranspose)

 conv1d_transpose_119 (Conv1  (None, 74096, 32)        6176
 DTranspose)

 conv1d_transpose_120 (Conv1  (None, 74096, 1)         97
 DTranspose)

=================================================================
Total params: 20,172,785
Trainable params: 20,172,785
Non-trainable params: 0

With this defined I set up my Parametric UMAP to fit to data called alignment_onehot (shape: (100, 74093)) using validation data val_onehot (shape: (10, 74093)).
    embedder = ParametricUMAP(
        encoder=encoder,
         decoder=decoder,
        dims=dims,
        parametric_reconstruction= True,
         reconstruction_validation=val_onehot,
        verbose=True,
        random_state=42
    )
embedding = embedder.fit_transform(alignment_onehot)

but when I try to fit the data I get the following Errors:
WARNING:tensorflow:Model was constructed with shape (None, 2) for input KerasTensor(<input_95 info>), but it was called on an input with incompatible shape (3, None, 2)
Input 0 of layer "decoder" is incompatible with the layer: expected shape=(None, 2), found shape=(3, 100, 2)
I'm not sure where the shape 3 comes from?? There are 100 embedded data points with latent dimension 2 but I'm confused on where how the 3 is included..
Here is the full output/error:
Output
ParametricUMAP(decoder=<keras.engine.functional.Functional object at 0x2aaedfb64520>, dims=(74093, 1), encoder=<keras.engine.functional.Functional object at 0x2ab0f50a6190>, optimizer=<keras.optimizers.optimizer_v2.adam.Adam object at 0x2ab101f80070>, parametric_reconstruction=True, reconstruction_validation=array([[1., 0., 1., ..., 0., 1., 0.],
       [1., 0., 1., ..., 0., 1., 0.],
       [1., 0., 1., ..., 0., 1., 0.],
       ...,
       [1., 0., 1., ..., 0., 1., 0.],
       [1., 0., 1., ..., 0., 1., 0.],
       [1., 0., 1., ..., 0., 1., 0.]]))
Wed Oct  5 13:14:13 2022 Construct fuzzy simplicial set
Wed Oct  5 13:14:14 2022 Finding Nearest Neighbors
Wed Oct  5 13:14:14 2022 Finished Nearest Neighbor Search
Wed Oct  5 13:14:14 2022 Construct embedding
WARNING:tensorflow:Model was constructed with shape (None, 2) for input KerasTensor(type_spec=TensorSpec(shape=(None, 2), dtype=tf.float32, name='input_95'), name='input_95', description="created by layer 'input_95'"), but it was called on an input with incompatible shape (3, None, 2).
Epoch 1/10

Error
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
/tmp/ipykernel_119266/1148489687.py in <module>
      5
      6
----> 7 embedding = embedder.fit_transform(alignment_onehot)

/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/umap/parametric_umap.py in fit_transform(self, X, y, precomputed_distances)
    215             return super().fit_transform(precomputed_distances, y)
    216         else:
--> 217             return super().fit_transform(X, y)
    218
    219     def transform(self, X):

/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/umap/umap_.py in fit_transform(self, X, y)
   2770             Local radii of data points in the embedding (log-transformed).
   2771         """
-> 2772         self.fit(X, y)
   2773         if self.transform_mode == "embedding":
   2774             if self.output_dens:

/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/umap/parametric_umap.py in fit(self, X, y, precomputed_distances)
    200             return super().fit(precomputed_distances, y)
    201         else:
--> 202             return super().fit(X, y)
    203
    204     def fit_transform(self, X, y=None, precomputed_distances=None):

/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/umap/umap_.py in fit(self, X, y)
   2682
   2683         if self.transform_mode == "embedding":
-> 2684             self.embedding_, aux_data = self._fit_embed_data(
   2685                 self._raw_data[index],
   2686                 self.n_epochs,

/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/umap/parametric_umap.py in _fit_embed_data(self, X, n_epochs, init, random_state)
    460
    461         # create embedding
--> 462         history = self.parametric_model.fit(
    463             edge_dataset,
    464             epochs=self.loss_report_frequency * self.n_training_epochs,

/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/keras/utils/traceback_utils.py in error_handler(*args, **kwargs)
     68             # To get the full stack trace, call:
     69             # `tf.debugging.disable_traceback_filtering()`
---> 70             raise e.with_traceback(filtered_tb) from None
     71         finally:
     72             del filtered_tb

/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/keras/engine/training.py in tf__train_function(iterator)
     13                 try:
     14                     do_return = True
---> 15                     retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope)
     16                 except:
     17                     do_return = False

/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/umap/parametric_umap.py in train_step(self, data)
   1133
   1134         with tf.GradientTape() as tape:
-> 1135             y_pred = self(x, training=True)  # Forward pass
   1136             # Compute the loss value
   1137             # (the loss function is configured in `compile()`)

ValueError: in user code:

    File "/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/keras/engine/training.py", line 1160, in train_function  *
        return step_function(self, iterator)
    File "/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/keras/engine/training.py", line 1146, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/keras/engine/training.py", line 1135, in run_step  **
        outputs = model.train_step(data)
    File "/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/umap/parametric_umap.py", line 1135, in train_step
        y_pred = self(x, training=True)  # Forward pass
    File "/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/keras/utils/traceback_utils.py", line 70, in error_handler
        raise e.with_traceback(filtered_tb) from None
    File "/data/cresswellclayec/conda/envs/DCA_ER/lib/python3.9/site-packages/keras/engine/input_spec.py", line 295, in assert_input_compatibility
        raise ValueError(

    ValueError: Exception encountered when calling layer "gradient_clipped_model_8" "                 f"(type GradientClippedModel).

    Input 0 of layer "decoder" is incompatible with the layer: expected shape=(None, 2), found shape=(3, 100, 2)

    Call arguments received by layer "gradient_clipped_model_8" "                 f"(type GradientClippedModel):
      • inputs=('tf.Tensor(shape=(100, 74093, 1), dtype=float32)', 'tf.Tensor(shape=(100, 74093, 1), dtype=float32)')
      • training=True
      • mask=None

I should say that I believe, maybe naively, that this is happening because Parametric umap is expecting 2D data (ie image data, (28, 28,1) ) and not the 1D data I'm using.. and that the embedded data is being re-cast weirdly inside umap before it is submitted to the decoder (hence the transition from the output (None, 2) --> (3, None, 2) )..

Hi Evan,
Can you try using the default encoder and decoder, rather than the convolutional networks?

Hello Tim,
Thanks for your quick response! It works with the default encoder and decoder.
However the resulting embedding isn't very good. I was hoping a convolutional network would solve the issue given the nature of the sequence data. For illustration here is an example embedding with the 100 sample data points (I ran the same analysis for 10000 data points with little difference in embedded grouping).

You could try an rnn encoder and decoder. You also will probably see more structure if you crop the outliers in your plot.

I’m going to mark this as closed since the original error is resolved but feel free to respond.

Looking through the network you defined, it looks like you took that architecture from a vae?

I did use vae as inspiration given that it has been effective in analyzing this type of data before (genome sequence data) and it seemed a natural fit with umap.
Just for my own understanding though: is the error I was having on the umap end? Is it just simply that parametric umap was not meant to handle 1D data? The example from the website used 2D convolutions.
WARNING:tensorflow:Model was constructed with shape (None, 2) for input KerasTensor(type_spec=TensorSpec(shape=(None, 2), dtype=tf.float32, name='input_2'), name='input_2', description="created by layer 'input_2'"), but it was called on an input with incompatible shape (3, None, 2).

Given the error it just seems that umap is passing something weird into the decoder.. I assumed that as long as my networks took the correct input shape and gave the correct output shape I should be fine regardless of the internals..

You also will probably see more structure if you crop the outliers in your plot.

Also those outliers persevere, when more data is included, very strange. I really want to get this architecture to work but I will try an rnn for the encoder and decoder. Thanks!

Hey, no, the issue is not on the UMAP end. If you can write an auto encoder in tensorflow with your dataset you should be able to use the same encoder here

authors: evancresswell timsainb


text:
Added more breez health check

Add breez health check in send flow
Add breez health check in swap flow
Show alert saying "BTC wallet is offline. Please try later." if breez is not operational

what's the best way to test this?

code looks good, but leaving this one open until we hear back from Breez and Blockstream on getting Greenlight health checks

Closing as we are moving away from greenlight.

repo: lnflash/flash-mobile


text:
Patch FPGA-SDC to consider time unit in global port timing constraints

…straints

Motivate of the pull request

[X] To address an existing issue. If so, please provide a link to the issue:
[ ] Breaking new feature. If so, please describe details in the description part.

Describe the technical details
What is currently done? (Provide issue link if applicable)

Address issue #316

What does this pull request change?

This PR improves in the following aspects:

[X] Add time unit support to SDC writer on the timing constraints for global port

Which part of the code base require a change

[ ] VPR
[ ] Tileable routing architecture generator
[ ] OpenFPGA libraries
[ ] FPGA-Verilog
[ ] FPGA-Bitstream
[X] FPGA-SDC
[ ] FPGA-SPICE
[ ] Flow scripts
[ ] Architecture library
[ ] Cell library
[ ] Documentation
[ ] Regression tests
[ ] Continous Integration (CI) scripts

Impact of the pull request

[ ] Require a change on Quality of Results (QoR)
[ ] Break back-compatibility. If so, please list who may be influenced.

@Icodextrin Please check if this patch works on your side.

This patch fixed the problem, thanks.

authors: Icodextrin tangxifan

repo: lnis-uofu/OpenFPGA


text:
fix(ci): set NODE_ENV to test in travis.yml

If you wanted to add db setup scripts like npm run db:migrate in your travis build, they rely on the NODE_ENV being set to test in order to pull from the config/test.js file.

LGTM

LGTM

authors: charlesbjohnson elnaz robinjoseph08

repo: lob/generator

license: mit


text:
Weird driver switch between initial visit and after refresh web page

I am not sure if this is a bug, would be great someone can help me confirm this.
Tested on Chrome 58.0.3029.110.
I am using React, on my src/index.js, before ReactDOM.render, I config localForage:
localForage.config({
  driver: [localForage.INDEXEDDB, localForage.LOCALSTORAGE],
  name: 'MyApp',
  version: 1.0,
  description: '',
});

localForage.ready().then(() => {
  console.log(localForage.driver());
});

On initial page visit, .ie open a new tab and type localhost:3000, above log result was asyncStorage.
When I refresh the current tab, log result was localStorageWrapper.

That's strange; is there any chance you have a race condition or are making a different call to localForage before your config call? Could you post a more full code snippet to see the code in context?

src/index.js
...

// localForage config
localForage.config({
  driver: [localForage.INDEXEDDB, localForage.LOCALSTORAGE],
  name: 'MyApp',
  version: 1.0,
  description: '',
});

localForage.ready().then(() => {
  console.log(localForage.driver());
});

// render
ReactDOM.render(
  <Provider store={store}>
    <AppContainer>
      <Router />
    </AppContainer>
  </Provider>,
  document.getElementById('root'),
);

// register service worker
registerServiceWorker();

If you leave out the config() call does anything change?

when I commented out config(), it always log localStorageWrapper regardless.

That's very strange! Do you have any add-ons on the browser or something messing with IndexedDB? What version of localForage are you using? It should be asyncStorage by default...

I'm using localforage 1.5.0. Let me try in private mode.

Great, on private mode it always asyncStorage, must be some of my extension...

Private mode will always force localStorage because private mode has bad IndexedDB and WebSQL support.

thats even weirder, my private Chrome mode always log asyncStorage.

By the way just auto updated to Chrome 59.

That's strange, but it sounds like it might be something on your Chrome install. If you can replicate this on another browser or machine, please re-open.
If you find out what this was please comment and let us know 😄

Thanks for your help!

Found it, so after disabling all extensions and enable them one by one, as soon as I enable Last Pass extension and visit my web page - it logs localStorageWrapper, so disabling it for now.

Wow, and that’s a very popular extension. Good to know, I’ll remember that if we run into this in the future! Thanks!

An out of scope comment from me: :+1: for using ready ()

authors: gnhuy91 thgreasi tofumatt

repo: localForage/localForage


text:
localforage for triple slash reference

It can save a lot of headache a simple new line of code in localforage.d.ts for newcomers who want to test/use localForage with typescript.
npm install localforage  or  download typings/localforage.d.ts then with triple slash reference point to localforage.d.ts.
/// <reference path="./path/to/your/your/localforage.d.ts" />
localforage.setItem('key', 'value').then(function () {
  return localforage.getItem('key');
}).then(function (value) {
  // we got our value
}).catch(function (err) {
  // we got an error
});

Any reason for closing this PR?

This was my first PR and I'm still learning how to do stuff, I wanted to make a new PR with a more appropriate description. Because I format by mistake the entire d.ts file and other crazy stuff, I decided to start everything all over. I thought this PR is completely removed, sorry about that, i made a new one.

authors: cosminalco tofumatt


text:
canonical url not appearing in generated html file

canonical url not appearing in generated html file.
Please let me know what option i need to supply to include rel canonical url in generated html snapshot

To my knowledge, there is no filter in this software that would remove such a thing from the snapshot. Are you supplying a custom filter?
Is there a public site I can use to reproduce the error?

Hello @CloudHadoop , I haven't heard back from you.
Is the canonical url in the source output, or is this something you wanted to add after the fact?

Closing since I haven't heard back in 3 weeks. Feel free to reopen to continue.

authors: CloudHadoop localnerve

repo: localnerve/html-snapshots


text:
add support for ingressClassName

For Kubernetes >= 1.18 we should be able to specify the ingress-controller via the field ingressClassName
See https://kubernetes.io/blog/2020/04/02/improvements-to-the-ingress-api-in-kubernetes-1.18/#specifying-the-class-of-an-ingress
Thanks.

Hey @arnoldas-jakstas-tg!
Thanks for the suggestion, this is something we could easily implement. In fact, this would be a good first issue, would you be interested in filing a PR?

Hey @arnoldas-jakstas-tg! Thanks for the suggestion, this is something we could easily implement. In fact, this would be a good first issue, would you be interested in filing a PR?

Sure, I'll raise a PR for the change.

repo: localstack/helm-charts


text:
Error Deploying Docker Container to Google Cloud Run

Hello,  this is my first time working with your project as well as with Google Cloud Run.
I have successfully loaded the Docker image from Docker Hub and pushed it to Google Container Registry for my project.
When I create the Google Cloud Run service I have tried setting the container port to 8080 as well as 3000.  When the service is deployed I receive the following error:
Cloud Run error: Container failed to start. Failed to start and then listen on the port defined by the PORT environment variable. Logs for this revision might contain more information.
The logs don't show any additional info.  Could you please advise on how to configure the variables to have this deploy successfully on Cloud Run?
Thanks for the great project!

add
const port = process.env.PORT || 8080;     app.listen(port, () => {         console.log('Hello world listening on port', port);     });
before

`app.use(router.routes());`

I'm facing another issue where it is creating http urls instead of https.

add
const port = process.env.PORT || 8080;     app.listen(port, () => {         console.log('Hello world listening on port', port);     });
before

`app.use(router.routes());`

I'm facing another issue where it is creating http urls instead of https.

From what I understand this will be impossible. Once you have the server running, when the clients come to connect they will be assigned a random PORT to connect to on your server - and Cloudrun won't allow anything other than the named port. Generally speaking I have failed in any attempt to get localtunnel running in any sort of docker orchestration:

cloudrun
kubernetes
fly.io

I am now realising it's down to this fundamental design choice.

authors: lawrencetaur nolandubeau royletron

repo: localtunnel/server


text:
Topic/mnaveau/architecture

This PR is a proposal of architecture around the WBMPC.
It proposes to:

create a default roscontroller that runs at 2kHz on the robot
create a ros-wbmpc-msgs package that deals with the creation of the ROS messages and services types
create a package implementing a ROS server that will read/stream the ros-wbmpc-msgs running the Sobec controller. This package is optional and maybe not worst it. (we have to think how to access to the feet trajectories though...

Thanks a lot ! This is a lot of work very much appreciated. One important point however, I have to plan to use the same architecture to access SASSA, SOLO or Bolt with ros2_control, therefore a believe that the linear_feeback_controller_msgs package should be separated as it will be/should be independent from the specific dependency of the controller.

https://github.com/loco-3d/linear-feedback-controller/issues/5


text:
Windows: setup could create Desktop shortcut for miner

see https://docs.microsoft.com/en-us/troubleshoot/windows-client/admin-development/create-desktop-shortcut-with-wsh

Most miners now use BOINC.

repo: loda-lang/loda-cpp


text:
Fundraising Campaign

Hello together, I'm the current maintainer of this package and I'm trying to raise some funds to keep this project up to date and since teamwork is a business application, I would appreciate a donation. Whether it is 10$ or 50$, I would appreciate any amount very much!
Donations can be done directly through GitHub or through Paypal. Thank you very much!
@zachauker @baerbro @Chrisedmo @johnny5th @Michael-Brooks @otsalko @jcandan @verypossible @MixMe

@simonschaufi I can certainly appreciate the request for support to maintain this project, however, it seems pretty suspect to be asking for donations on a project that hasn't had a release in over half a year. Especially when the majority of said release is composed of style fixes and annotations and no real updates to the functionality of the package and does not address any of the current open issues.
This repository also isn't currently owned by you, and I've seen no indication from the owner that suggests you are the primary contributor/maintainer. I think individuals may be more inclined to contribute financially if there was any sort of roadmap or plan for how the package will be improved and updated in the future. This package was released as open source with the expectation of not being a monetized product. To the best of my knowledge, it has no official association with Teamwork Project Management, so I don't see what the distinction of it as a "business application" means in this context. I mean no disrespect by these comments, but tagging everyone who's submitted an issue on this repository to ask for money without offering any response to the code issues themselves doesn't sit right with me personally.

@zachauker Thank you for your feedback!

I have asked Loduis if I can maintain this repo under his username because he didn't want to continue.
I'm raising funds because I would like to work on the reported issues
My roadmap is to make it fully compatible with PHP 8 and to make it fully compatible with the provided API of Teamwork
What i mean by business application: People who are using teamwork will most likely be a company and not only a single person (Freelancer). I'm myself don't use teamwork and I would like to have at least a little bit of costs covered for my time that I invest into this project because nobody pays me for this voluntary work.

Hello @simonschaufi ,
I currently have some time to maintain the project; in fact, I am in the process of restructuring the entire test base locally.

authors: loduis simonschaufi zachauker


text:
9 patch image

Another issue with the splash screens ;)
I have a splash.9.png image specified in the config screens:  android: mdpi: 'splash.9.png' which isnt stretched correctly because it gets copied without the .9 part of the name.

+1

repo: logankoester/grunt-phonegap


text:
🛑 Potus Remoto is down

In 7831b0f, Potus Remoto (https://remoto.potus.ar) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Potus Remoto is back up in 7b124e9.


text:
Change Client log to io.Writer to allow more diversity in logging

This allows higher control by the end user to setup logging how they wish such as logging to terminal when learning and starting to use this package, or passing the logs over the wire etc.
CHANGE: Renamed 'SetLogFile' to 'SetLog' and changed the parameter from a string to io.Writer
CHANGE: Changed logFile name and type to name Log of type io.Writer
CHANGE: func log of client now uses new log object.

Thanks for this change!

no problem just downloaded it and wanted to get started and noticed that so i figured id send a request :). thanks for the package which will hopefully be saving me loads of time xD.

repo: logpacker/PayPal-Go-SDK


text:
Package is not installable from pypi

$ mkvirtualenv test
New python executable in test/bin/python
Installing distribute.............................................................................................................................................................................................done.
Installing pip...............done.
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/predeactivate
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/postdeactivate
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/preactivate
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/postactivate
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/get_env_details
$ pip install strategies
Downloading/unpacking strategies
  Downloading strategies-0.2.0.tar.gz
  Running setup.py egg_info for package strategies
    Traceback (most recent call last):
      File "<string>", line 14, in <module>
      File "/home/sk/.virtualenvs/test/build/strategies/setup.py", line 10, in <module>
        install_requires=open('dependencies.txt').read().split('\n'),
    IOError: [Errno 2] No such file or directory: 'dependencies.txt'
    Complete output from command python setup.py egg_info:
    Traceback (most recent call last):

  File "<string>", line 14, in <module>

  File "/home/sk/.virtualenvs/test/build/strategies/setup.py", line 10, in <module>

    install_requires=open('dependencies.txt').read().split('\n'),

IOError: [Errno 2] No such file or directory: 'dependencies.txt'

----------------------------------------
Command python setup.py egg_info failed with error code 1 in /home/sk/.virtualenvs/test/build/strategies
Storing complete log in /home/sk/.pip/pip.log
$ python --version
Python 2.7.3

Dependencies wasn't in the MANIFEST.  Fixed and pushed to PyPI.
On Wed, May 20, 2015 at 3:41 PM, Sergey B Kirpichev <
notifications@github.com> wrote:

$ mkvirtualenv test
New python executable in test/bin/python
Installing distribute.............................................................................................................................................................................................done.
Installing pip...............done.
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/predeactivate
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/postdeactivate
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/preactivate
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/postactivate
virtualenvwrapper.user_scripts creating /home/sk/.virtualenvs/test/bin/get_env_details
$ pip install strategies
Downloading/unpacking strategies
Downloading strategies-0.2.0.tar.gz
Running setup.py egg_info for package strategies
Traceback (most recent call last):
File "", line 14, in
File "/home/sk/.virtualenvs/test/build/strategies/setup.py", line 10, in
install_requires=open('dependencies.txt').read().split('\n'),
IOError: [Errno 2] No such file or directory: 'dependencies.txt'
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "", line 14, in
File "/home/sk/.virtualenvs/test/build/strategies/setup.py", line 10, in
install_requires=open('dependencies.txt').read().split('\n'),

IOError: [Errno 2] No such file or directory: 'dependencies.txt'

Command python setup.py egg_info failed with error code 1 in /home/sk/.virtualenvs/test/build/strategies
Storing complete log in /home/sk/.pip/pip.log
$ python --version
Python 2.7.3
—
Reply to this email directly or view it on GitHub
https://github.com/logpy/strategies/issues/2.

Works for me.  Thank you, I'll close this bugreport.

authors: mrocklin skirpichev

repo: logpy/strategies


text:
add logseq-marks plugin

Submit a new Plugin to Marketplace
Plugin Github repo URL: https://github.com/Dieterbe/logseq-plugin-marks
Github releases checklist

[x] a legal package.json file.
[x] a valid CI workflow build action for Github releases. (Optional for theme plugin only).
[ ] a release which includes a release zip pkg from a successful build.
[x] a clear README file, ideally with an image or gif showcase. (For more friendly to users, it is recommended to have English version description).
[x] a license in the LICENSE file.

Hi, I'm not sure if the zip file is as expected. The release has a zip file but it seems to not include compiled code, only the source.
I wanted to submit this PR to get the process going, as this is my first plugin, with hopefully more to come :-)
Please have a look and let me know how to proceed,
thanks!

Hi @Dieterbe  such a cool plugin!  I created a PR to build a release by Github action https://github.com/Dieterbe/logseq-plugin-marks/pull/2 . I hope it's helpful :)

thank you @xyhp915 ! that fixes it!

repo: logseq/marketplace


text:
Messages in queue preventing new messages coming in

I'm running both logstash 5.3 and 5.2 and I'm seeing this in the log output...
[2017-04-25T08:30:00,222][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:01,222][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:02,222][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:02,871][DEBUG][logstash.pipeline        ] Pushing flush onto pipeline
[2017-04-25T08:30:03,223][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:04,223][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:05,223][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:06,223][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:07,223][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:07,872][DEBUG][logstash.pipeline        ] Pushing flush onto pipeline
[2017-04-25T08:30:08,224][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:09,224][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:10,224][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:11,224][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:12,224][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:12,871][DEBUG][logstash.pipeline        ] Pushing flush onto pipeline
[2017-04-25T08:30:13,225][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:14,225][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:15,225][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:16,225][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:17,226][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:17,870][DEBUG][logstash.pipeline        ] Pushing flush onto pipeline
[2017-04-25T08:30:18,226][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:19,226][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:20,226][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:21,226][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:22,227][DEBUG][logstash.inputs.jmx      ] There are still 3 messages in the queue conf. Sleep 1s.
[2017-04-25T08:30:22,869][DEBUG][logstash.pipeline        ] Pushing flush onto pipeline

which is preventing new jmx messages from coming in.
my conf file looke like this:
input {
        jmx {
          path => "/home/ec2-user/jmx-input"
          polling_frequency => 15
          nb_thread => 4
          add_field => {
                        "cluster" => "cluster1"
                }
        }

}
filter {

                ruby {
                        code => "event.set('timejmx', event.get('@timestamp').to_f * 1000 )"
                }
}
output {
        kafka {
                topic_id => "kafka-jmx"
                client_id => "logstash1-jmx-producer"
                bootstrap_servers => "kafka1:9092,kafka2:9092,kafka3:9092"
                acks => "0"
                key_serializer =>"org.apache.kafka.common.serialization.StringSerializer"
                codec => "json_lines"
        }

}

Whats weird is that I have this same conf setup across multiple nodes and only one of them is showing this issue. it polls JMX 3 times successfully, but then hangs on the above log output.
I have even tweaked with some logstash settings like this but still the same results:
pipeline.workers: 6
pipeline.output.workers: 3
pipeline.batch.size: 250
pipeline.unsafe_shutdown: true
queue.max_events: 500

I have stripped out the filter and also set the output to stdout and am still seeing the same behavior...

Now at the end of my log...I'm seeing this:

[Loaded rubyjit.LogStash::Instrument::NamespacedMetric$$initialize_59a8714b2d9ba31321867e2413880b15eeeeef04205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::NamespacedMetric$$gauge_b577f1ea9c1d2ea1f0b6e99069795deba30cf4eb205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::Metric$$namespace_8eaa8d5b1e4e16e3f170f628e10fc701f3804bef205797316 from __JVM_DefineClass__]
[Loaded rubyjit.Module$$stoppable_sleep_c19c1639527ca7d373b5093f339d26538f1c21ef205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::PersistentQueue$$collect_55c5216459221679bb959fd58127d310bc686ba8205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Agent$$running_pipelines_acdd46a24f865d468bf515c3ccfcbcb781a858de205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Pipeline$$collect_stats_d32f7ff295eef4555a66defecb811360732f5583205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::Os$$collect_64eb2d2771fb3b57c56a11495a7c40fef4264e13205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::Os$$collect_cgroup_a0b23d8c691cf9b4532a03c30a4149d3eced70b5205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::Cgroup$$get_59a4a4e8f012d69bc611d1135f0119b6107b35c9205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::Cgroup$$are_cgroup_available?_5f7deab7acaca82af833a88d6de93fee78d26e65205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_6973f0cb7ba797542d14ceb250444d8164c828c5205797316 from __JVM_DefineClass__]
[Loaded rubyjit.Module$$memory_610a3ccfbc3104dfb6a43b824297780e2e8ea7b8205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_jvm_metrics_0598acf1f323f2c8178f29540534cf0218e7fadb205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_heap_metrics_1c532709bd6464033c4db310fd2fa6877b82d518205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_non_heap_metrics_df148f407b63544a7a7e5af5e05ac72f7cf0c228205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_pools_metrics_72449b21a2022a74ac6681b77659396ddb7ac358205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$build_pools_metrics_b8b6a3c145544fcdbc3803852509e06c140e975f205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_threads_metrics_76dc7277021c4d692e2454aefc121257016cade5205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_process_metrics_5f7546cc0220f68c56d376c736d0696090b2f72b205797316 from __JVM_DefineClass__]
[Loaded rubyjit.Module$$process_d58c915135b93281c6257cc9117438068e52f53f205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_gc_stats_c632ac17e0ff115cf0362efee164bef27b4f8a60205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::JVM$$collect_load_average_baf486f8156d9f2d319bbaa98cba9b749be0752f205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Instrument::PeriodicPoller::LoadAverage::Linux$$get_3ee9642cb921ec069a09768057211b3aec46e058205797316 from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Agent$$running_pipelines_acdd46a24f865d468bf515c3ccfcbcb781a858de205797316$block_0$RUBY$__file__ from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Agent$$running_pipelines_acdd46a24f865d468bf515c3ccfcbcb781a858de205797316$block_1$RUBY$__file__ from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Instrument::PeriodicPoller::JVM$$collect_heap_metrics_1c532709bd6464033c4db310fd2fa6877b82d518205797316$block_0$RUBY$__file__ from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Instrument::PeriodicPoller::JVM$$collect_non_heap_metrics_df148f407b63544a7a7e5af5e05ac72f7cf0c228205797316$block_0$RUBY$__file__ from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Instrument::PeriodicPoller::JVM$$collect_pools_metrics_72449b21a2022a74ac6681b77659396ddb7ac358205797316$block_0$RUBY$__file__ from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Instrument::PeriodicPoller::JVM$$collect_pools_metrics_72449b21a2022a74ac6681b77659396ddb7ac358205797316$block_1$RUBY$__file__ from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Instrument::PeriodicPoller::JVM$$collect_gc_stats_c632ac17e0ff115cf0362efee164bef27b4f8a60205797316$block_0$RUBY$__file__ from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Pipeline$$flush_15a7f81bbfa79b21406ec43dadd5ae207170b5f8205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::FlushEvent$$flush?_6ff4fb73b2f8427def7476b44367f6118b71c5ba205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Pipeline$$flush_filters_to_batch_f6b9831fb7b2da2bba95faf8011ee9d9904d25c7205797316 from __JVM_DefineClass__]
[Loaded rubyjit.LogStash::Pipeline$$flush_filters_dcd1c695ed0c78707f43a780bd81abeb2ab3669a205797316 from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Pipeline$$flush_filters_to_batch_f6b9831fb7b2da2bba95faf8011ee9d9904d25c7205797316$block_0$RUBY$__file__ from __JVM_DefineClass__]
[Loaded rubyjit$LogStash::Pipeline$$flush_filters_dcd1c695ed0c78707f43a780bd81abeb2ab3669a205797316$block_0$RUBY$__file__ from __JVM_DefineClass__]

repo: logstash-plugins/logstash-input-jmx


text:
Agent Address field of SNMPV1 Trap is coming as combination of hexadecimal and ASCII value

When trying to extract fields of SNMPv1 trap from logstash output. Here is my pipeline:

And This is what I see in output:

Here, agent address is coming as combination of hexadecimal and ASCII value.
"agent_address" => ""\xFFA\xFFA""
I need agent address in IP Address format( like 1.1.1.1) .

Hey there,
We've moved this issue into this new SNMP integration plugin, which combines the logstash-input-snmp and logstash-input-snmptrap plugins into one.
Considering we've switched the underline library from ruby-snmp to snmp4j, I'd suggest you to upgrade to this integration plugin (migration guide) and try it again.
Please note that the new plugin introduced a few breaking changes compared to individual one, for example, your grok filter won't work as expected, as the message field format has changed. As an alternative, you could get those values from the metadata fields (SNMPv1 only): [@metadata][input][snmptrap][pdu][agent_addr], [@metadata][input][snmptrap][pdu][enterprise], [@metadata][input][snmptrap][pdu][generic_trap], [@metadata][input][snmptrap][pdu][specific_trap], and so on, e.g:
input {
   snmptrap {
       ...
       add_field => {
          "agent_address" => "%{[@metadata][input][snmptrap][pdu][agent_addr]}"
          "generic_trap" => "%{[@metadata][input][snmptrap][pdu][generic_trap]}"
           ...
       }
   }
}

authors: edmocosta jkrishnak


text:
L-1016 By default, don't check ENV vars in Vercel non-production build

Resolves https://github.com/logtail/logtail-nextjs/issues/6 when building project via vercel build while not having VERCEL_ENV variable accessible during build.

@curusarn That's what I did even before #14, worked as intended with example project on my machine. There's just too many variables to ensure other's will have the same experience...
Here's full output for possible use in the future:
Petrs-MacBook-Pro:logger petrheinz$ vercel build
Vercel CLI 32.5.6
WARNING: You should not upload the `.next` directory.
Installing dependencies...

up to date in 1s

124 packages are looking for funding
  run `npm fund` for details
Detected Next.js version: 14.0.2
Detected `package-lock.json` generated by npm 7+
Running "npm run build"

> build
> next build

 ✓ Linting and checking validity of types
   ▲ Next.js 14.0.2

 ⚠ /api/edge provided runtime 'experimental-edge'. It can be updated to 'edge' instead.
 ✓ Creating an optimized production build
 ✓ Compiled successfully
 ⚠ You are using an experimental edge runtime, the API might change.
 ✓ Collecting page data
 ✓ Generating static pages (3/3)
 ✓ Collecting build traces
 ✓ Finalizing page optimization

Route (pages)                              Size     First Load JS
┌ ● /                                      4.92 kB        91.5 kB
├   /_app                                  0 B            86.5 kB
├ ○ /404                                   182 B          86.7 kB
├ ℇ /api/edge                              0 B            86.5 kB
├ λ /api/hello                             0 B            86.5 kB
└ λ /serverSideProps                       407 B          86.9 kB
+ First Load JS shared by all              86.5 kB
  ├ chunks/framework-66d32731bdd20e83.js   45.2 kB
  ├ chunks/main-8c2fcf961f1eeec3.js        31.8 kB
  ├ chunks/pages/_app-9cf4ffac8ca82c92.js  8.75 kB
  └ chunks/webpack-59c5c889f52620d6.js     819 B

ƒ Middleware                               36.8 kB

○  (Static)        prerendered as static content
●  (SSG)           prerendered as static HTML (uses getStaticProps)
λ  (Dynamic)       server-rendered on demand using Node.js
ℇ  (Edge Runtime)  server-rendered on demand using the Edge Runtime

Traced Next.js server files in: 237.505ms
Created all serverless functions in: 95.793ms
Collected static files (public/, static/, .next/static): 1.594ms
✅  Build Completed in .vercel/output [7s]

@curusarn I hope @jakeleventhal will verify that it works in their use case as well, so we know we're in the clear before releasing another small fix 🙂

@PetrHeinz https://github.com/logtail/logtail-nextjs/issues/6#issuecomment-1828054057

authors: PetrHeinz jakeleventhal

repo: logtail/logtail-nextjs


text:
Could not find com.sangcomz:FishBun:0.11.2

Bug Report
multiple_images_picker version: 1.0.1
Is it happening on Android: yes
Is it happening on iOS: no
$ flutter doctor
Doctor summary (to see all details, run flutter doctor -v):
[✓] Flutter (Channel stable, 3.10.2, on macOS 13.4.1 22F82 darwin-arm64, locale de-DE)
[✓] Android toolchain - develop for Android devices (Android SDK version 33.0.2)
[✓] Xcode - develop for iOS and macOS (Xcode 14.3)
[✓] Chrome - develop for the web
[✓] Android Studio (version 2022.2)
[✓] VS Code (version 1.79.2)
[✓] VS Code (version 1.80.0-insider)
[✓] Connected device (2 available)
[✓] Network resources

• No issues found!

Describe the bug
Hi there,
whenever I want to build any of my projects using multiple_images_picker version: 1.0.1 I get this build error on android builds:
$ flutter build apk

FAILURE: Build failed with an exception.

* What went wrong:
Execution failed for task ':multiple_images_picker:generateReleaseRFile'.
> Could not resolve all files for configuration ':multiple_images_picker:releaseCompileClasspath'.
   > Could not find com.sangcomz:FishBun:0.11.2.
     Required by:
         project :multiple_images_picker

* Try:
> Run with --stacktrace option to get the stack trace.
> Run with --info or --debug option to get more log output.
> Run with --scan to get full insights.

* Get more help at https://help.gradle.org

BUILD FAILED in 6s
Running Gradle task 'assembleRelease'...

Looks like the FishBun dependency is not available anymore.
In case it helps: resolving the dependecy worked just fine 4 days ago (last successfull know build was 2023-06-19)
In case you need any help to debug this further please let me know
thansk for your help,
markus

Hi, I had the same problem,
I fixed it by change the library dependencies
in build.gradle
in root
multiple_images_picker-1.0.1\android\build.gradle
from
implementation 'com.sangcomz:FishBun:0.11.4'
to
implementation 'io.github.sangcomz:FishBun:0.11.4'
it will be like this :
dependencies {
implementation 'androidx.exifinterface:exifinterface:1.3.1'
implementation 'io.github.sangcomz:FishBun:0.11.4'
implementation 'com.github.bumptech.glide:glide:4.11.0'
}
Regards

authors: mohamedezoSD thekorn


text:
bro you dumbass

"I am in the process of taking legal action against someone stealing my code and posting it as their own. They modified my code as well as deleted all credit towards me. Do not steal my work as I will take legal actions." did you make this months ago? gliz Made it you dumbass he didn't do any of this shit dumbass .. also you aren't in trouble with anybody with legal claims goofy ass ☠

gilx got banned he might have given lol-jude the code

repo: lol-jude/Blooket-Hacks


text:
command line

Hi, please make a command line app that every one can use it easy.

Sure why not.

Thanks alot.

authors: lolPants mehdikhody

license: ISC


text:
🛑 Subtle Bodies is down

In 4647f12, Subtle Bodies (https://subtle-bodies.jau.co.jp) was down:

HTTP code: 500
Response time: 5373 ms

Resolved: Subtle Bodies is back up in 6fa07f5.

repo: longforme/longforme-uptime-monitor