I reported zone.js developers the same issue https://github.com/angular/zone.js/issues/954. They replied they could not reproduce it.

Not sure if I understood your question correctly as it may mean any of following two.

#1 - Grep in first 10 lines

head -10 filename | grep "search string"

#2 - Show first 10 grep result lines

grep "search string" filename | head -10

The issue is resolved when I build the app in release mode. Debug mode was causing performance overhead, but switching to release mode fixed the lag and improved scrolling performance significantly.

Many thanks @lazyone! The below works well:

Error generating CloudFront signed URL: Error: ENAMETOOLONG: name too long, open '-----BEGIN RSA PRIVATE KEY----- LS0tLS1CRUdJTi

is your CCAvenue working properly? If yes, I need a solution. I am getting the error '10002 Merchant Authentication failed.' Can you guide me on how to resolve this?

I have added the proper accessCode and merchantId, but the issue is still not resolved. I did some research and found that I might need to add the Android Integration Kit plugin. However, I don't know how to integrate it.

Can you suggest how to fully integrate CCAvenue?

Hi do you find the solution bro because i am also stuck here

localhost (http://127.0.0.1:8000/)is saying

wss://localhost:8080/app/r4klajydlrt66ofal8cc?protocol=7&client=js&version=8.4.0-rc2&flash=false' failed:

and my ENV is this in laravel 11 with reverb

APP_NAME=Laravel
APP_ENV=local
APP_KEY=base64:+l5y9bR2vIa2RzICZFDery9ogQJoEDAYFE77iBrTTRw=
APP_DEBUG=true
APP_TIMEZONE=UTC
APP_URL=http://localhost

APP_LOCALE=en
APP_FALLBACK_LOCALE=en
APP_FAKER_LOCALE=en_US

APP_MAINTENANCE_DRIVER=file
# APP_MAINTENANCE_STORE=database

PHP_CLI_SERVER_WORKERS=4

BCRYPT_ROUNDS=12

LOG_CHANNEL=stack
LOG_STACK=single
LOG_DEPRECATIONS_CHANNEL=null
LOG_LEVEL=debug

DB_CONNECTION=mysql
 DB_HOST=127.0.0.1
 DB_PORT=3306
 DB_DATABASE=chat_9
 DB_USERNAME=root
 DB_PASSWORD=

SESSION_DRIVER=database
SESSION_LIFETIME=120
SESSION_ENCRYPT=false
SESSION_PATH=/
SESSION_DOMAIN=null

BROADCAST_CONNECTION=reverb
FILESYSTEM_DISK=local
QUEUE_CONNECTION=database

CACHE_STORE=database
CACHE_PREFIX=

MEMCACHED_HOST=127.0.0.1

REDIS_CLIENT=phpredis
REDIS_HOST=127.0.0.1
REDIS_PASSWORD=null
REDIS_PORT=6379

MAIL_MAILER=log
MAIL_SCHEME=null
MAIL_HOST=127.0.0.1
MAIL_PORT=2525
MAIL_USERNAME=null
MAIL_PASSWORD=null
MAIL_FROM_ADDRESS="[email protected]"
MAIL_FROM_NAME="${APP_NAME}"

AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_DEFAULT_REGION=us-east-1
AWS_BUCKET=
AWS_USE_PATH_STYLE_ENDPOINT=false

VITE_APP_NAME="${APP_NAME}"


REVERB_APP_ID=214093
REVERB_APP_KEY=r4klajydlrt66ofal8cc
REVERB_APP_SECRET=ip7lrpqbd1dy54yl4njw
REVERB_HOST="localhost"
REVERB_PORT=8080
REVERB_SCHEME=http

VITE_REVERB_APP_KEY="${REVERB_APP_KEY}"
VITE_REVERB_HOST="${REVERB_HOST}"
VITE_REVERB_PORT="${REVERB_PORT}"
VITE_REVERB_SCHEME="${REVERB_SCHEME}"

Use the command DESCRIBE tablename in mysql

Nltk uses VADER method for sentiment analysis. And this method is rule based and does not have really good understanding of context.

You will get better result if you will try some Pre-Trained transformer based model such as Roberta. Because these model uses attention module and have really good understanding of context.

And you can also use free version of GPT or open source module such as LLama 3.1 8B to get the label.

I tried free version of GPT and I get accurate result on all 5 examples.

Enabled the WebSocket support on my MQTT protocol, and declare host as ws://sample-mqtt.com.ph:port/mqtt.

verify the Update SQL Shell Shortcut target and Please check pgpass.conf- Update any entries with port 5433 to 5432 in %APPDATA%\postgresql\pgpass.conf.

they have anti scraping tools, better use https://rentcast.io, https://findvest.io

I get the same error message when I try to load the pickled model through mlflow. The model I am trying to download is from xgboost framework but somehow it is giving me sklearn error. My sklearn is 1.5.2 version but the same error as mentioned above still persists.

Error loading model: 'super' object has no attribute 'sklearn_tags'

channels:

• conda-forge dependencies:
• python=3.9.21
• pip<=24.2
• pip:
  • mlflow==2.19.0
  • numpy==2.0.1
  • pandas==2.2.3
  • psutil==6.1.1
  • scikit-learn==1.5.2
  • scipy==1.13.1
  • xgboost==2.1.3 name: mlflow-env

For windows postqresql service error, i just had to go back and replace posgresql.conf with the factory-default file and deleted C:\Program Files\PostgreSQL\XX\data\postmaster.pid file then restarted server and service started.

A few importand info

Postqresql port 5432 should not be used by different applications can be checked with the following command netstat -an | find "5432"

The user running the postgre service must be NETWORK_SERVICE and the password field must contain the postqre db password

Date 2024.12.26

Here is how i set it up using php and js

https://github.com/Cyford-Technologies-LLC/reCAPTCHA-v3-Auto/blob/main/google.php

1. grecaptcha.execute
2. Send token to server
3. Execute verification immediately when page loads
4. if data.score > 0.5 {echo Success}
5. Optional: Refresh verification every 2 minutes

Do watch this video will help : https://www.youtube.com/playlist?list=PLuji25yj7oIKWUxnb3GeRfql9s5C26CyD

I suspect that you are being blocked by the site.

WooCommerce has recently changed its Checkout page implementation on its newer versions. Hence, the legacy code may not work. You can try downgrading the WooCommerce version or adhering to the latest checkout code.

so was getting similar issue. Late to the party, but hopefully this helps someone else. I paused my internal testing track (which i guess made production the only one that would get served). breakdown: So, v21 is prod. v22 internal test upload

all of a sudden both prod and internal aab upload when downloaded from playstore showed white screen

paused internal testing downloaded app once more - works

key thing i noticed was, on your physical device go to apps -> yourApp -> at the bottom app version - it most likely says the internal version not the prod version

Hopefully that was clear - lost a lot of braincells tryna debug something with no info - if you're in same boat you know how it feels - good luck

We are using GCE with k8s, where we are deploying pods on GCE servers, and service accounts are linked with server that the pod is deployed on, and not directly with the pod itself.

The issue was that in k8s yaml file, used to deploy the pod, we were not setting hostNetwork. After setting hostNetwork to true the metadata request returned result successfully.

Before this setting, I guess the pod will run in it's own network instead of using the server's network. More info: What is hostNetwork in Kubernetes?

I guess the code above one is backend and lower one is front-end. Are you able to get the response in the streaming from the openai? Bcz in python function call look like this:

    def aduioTextStream(text):
        with client.audio.speech.with_streaming_response.create(
            model="tts-1", voice="alloy", input=text, response_format="pcm"
        ) as response:
            for chunk in response.iter_bytes(chunk_size=1024):
                yield chunk

And yes I am facing the same issue in front-end side. the chunks are streaming to front-end but when make it audible and decoding it the content-type show the "octet-stream". I am backend dev. and i don't have enough knowledge in the front-end. Let me know it you know the answer how i can handle it.

SAP settings are sometimes controlled by Group Policy objects as well. Below are the troubleshooting steps/solutions you can try:

1. Ask your Org. admin for a specialized GPO for SAP installed machines where the Robot runs.
2. If there is no GPO make sure to edit the registry during the automation
3. If the options 1 and 2 are not possible, then using ABAP will also work.
4. Automate SAP using SAP BAPI (System user is enough you wont even need a dialog user with the right permissions/access level)
5. Check the local SAP config files while setting up SAP (In the config files the default might be to enable them when SAP restarts or periodical reset)

let me know if none of the above work. post the screenshots of your config/registry etc and we can see what else can be done.

You must use the method getMessageThread for this. Check the flag can_get_message_thread from getMessageProperties to know whether a channel post has comments.

After installing postgresql@16 by brew:

brew install postgresql@16

it is located on:

/opt/homebrew/Cellar/postgresql@16/16.6

Same, I encountered this issue too. It happens because your setup doesn’t support modern JS features like nullish coalescing (??) and optional chaining (?.). Here are quick workarounds for this:

1. Eject CRA – Run npm run eject to customize Babel and Webpack, but note that you’ll manage all configurations yourself using .babelrc.
2. Downgrade @mui/x-charts – Use an older version that works with your current setup.
3. Upgrade react-scripts – This will update Babel and Webpack to support modern JS features without downgrading libraries.

Well, the criptos can use 256bits, so BINARY(32) resolves to store, the same c++ code do to store on LevelDB blockchain. But.. if the problem is only to store this is OK. The real problem is to do the calcs (SUM p example) inside SQL. If you use a program, so there are libraries do work with large numeric data types as uint256. Study if DECIMAL(27,18) will be OK to your case. I dont know an easy way to proccess the calcs inside SQL with number with 256b at the moment. On SQL Server is possible to create programs on .NET so you can program some aritmetic works inside SQL SERVER, to your BINARY(32) data, the same is possible on Firebird with external FUNCTIONS. Maybe the easiest way is to do by program.

since it's quite unnoticeable, i always prefer to set a more colorful color for it. it's called "Suggesion ellipses (...)" in Display items.

With the help of shantharuban's answer,

I've ended up configuring the settings of Visual Studio Code this way:

The other portion settings have an original value of on and changed into off, but I found it more helpful to see the specific widget property name, so I've decided to change from off to inline as shown on the provided image.

It behaves like this way:

Let's see how it behaves compared to off and on Quick Suggestions other value's settings.

choose smaller image(less than 50kb)

I was not flashing the program correctly, a lot of the tutorials I used I think were fine. I needed to be flashing it to RAM instead of programming the tab.

As was mentioned in commend by @loganfsmyth, in order to call join on JoinHanlde you need to own it (because join "consumes" the JoinHandle). But get method on HashMap provides you with a borrow, not an ownership. So the solution would be to use remove to obtain owned value from HashMap

fn stop_server_command(id: usize) {
    if let Some((handler, signal)) = SERVER_INSTANCES.lock().unwrap().remove(&id) {
        signal.send(()).unwrap();
        handler.join().unwrap();
    }
}

I know this is an early problem. I also encountered this problem. It seems that Whisper can be used only when using pusher channel in larravel, and client events must be enabled

There's a 'download zip' option in the same dropdown from where the git clone URL is copied. This should help. enter image description here

Workspace setting was created with just this line in it:

"editor.quickSuggestions": false,

Which obviously caused quick suggestions to stop showing. This was not in the general VS code settings so remove it.

According to: https://www.w3.org/TR/css-flexbox-1/#flex-wrap-property

The flex-wrap property controls whether the flex container is single-line or multi-line, and the direction of the cross-axis, which determines the direction new lines are stacked in.

So if you set the "flex-wrap" property to "wrap", the flex container will be a multi-line container, and then "align-content" works.

I ended up doing the following. I created a file called 'clientApplication' with the following code

"use client";
import { useEffect } from "react";
import { usePathname } from 'next/navigation';

import FadeInElements from './scripts/FadeInElements'

export default function ClientApplication({ children }) {
  const pathname = usePathname();

  useEffect(() => {
    FadeInElements(pathname);
  });

  return children;
}

Then in my layout.js I wrapped this around my {children}

export default function RootLayout({ children }) {

  return (
    <html lang="en">
      <body data-theme="light">
        <ClientApplication>
          {children}
        </ClientApplication>
      </body>
      <GoogleAnalytics gaId="G-7GTMYC6GZP" />
      <Analytics />
      <SpeedInsights />
    </html>
  )

This seems to be working okay. Do you see any concerns with it?

You'll need to implement a loop step in your Zap before the Twilio step to loop through all "to" phone numbers and the respective "val" that needs to be sent as a message.

There's a guide on implementing looping here: https://help.zapier.com/hc/en-us/articles/8496106701453-Loop-your-Zap-actions#h_01HME0XPHPAMF4BQ4A6KH9D645.

Ideally, there will be one loop iteration for each phone number and the respective val, which you can then map into the Twilio step (the guide covers this too).

I also encountered the same situation. In my case, I simply deleted node_modules and reinstalled npm. Then, I ran ./gradlew clean. I hope this helps you.

# start
fun _start():
  await self.master.run()
  await self.master.running()
self._task = self._loop.create_task(self._start())
self._loop.run_until_complete(self._task)

# stop
self.master.shutdown()
self._task.done()

1. First, let's calculate how much memory your model might be using:

The error shows you're trying to allocate ~69GB (69271363584 bytes), which is far too large for most GPUs or CPUs

2. Potential causes of the memory issue:

a) Input Dimensions:

You haven't shared the dimensions of your input data, but this could be a key issue Check your batch size, sequence length, and d_model values The memory usage grows quadratically with sequence length due to attention mechanisms

b) Positional Encoding Implementation:

self.encoding = torch.zeros(max_len, d_model)

• Your current implementation creates a large tensor of size (max_len, d_model)
• max_len=5000 might be unnecessarily large for your use case

3. Suggestions for fixing the issue:

   class PositionalEncoding(nn.Module): def init(self, d_model, max_len=5000, dropout=0.1): super(PositionalEncoding, self).init() self.dropout = nn.Dropout(p=dropout)

        # Create more memory-efficient positional encoding
        pe = torch.zeros(max_len, d_model)
        position = torch.arange(0, max_len).unsqueeze(1).float()
        div_term = torch.exp(
            torch.arange(0, d_model, 2).float() * (-math.log(10000.0) / d_model)
        )
   
        pe[:, 0::2] = torch.sin(position * div_term)
        pe[:, 1::2] = torch.cos(position * div_term)
        pe = pe.unsqueeze(0)
   
        # Register buffer instead of parameter
        self.register_buffer('pe', pe)
   
    def forward(self, x):
        x = x + self.pe[:, :x.size(1)]
        return self.dropout(x)
   

4. Additional optimization suggestions:

   class TransformerDecoder(nn.Module): def init(self, vocab_size, d_model, num_heads, num_layers, max_seq_length): super(TransformerDecoder, self).init() self.embedding = nn.Embedding(vocab_size, d_model) self.positional_encoding = PositionalEncoding(d_model, max_seq_length)

        # Add dropout
        self.dropout = nn.Dropout(0.1)
   
        # Memory-efficient decoder layer
        decoder_layer = nn.TransformerDecoderLayer(
            d_model=d_model,
            nhead=num_heads,
            dim_feedforward=4*d_model,  # Standard size
            dropout=0.1,
            batch_first=True  # Avoid permute operations
        )
        self.transformer_decoder = nn.TransformerDecoder(decoder_layer, num_layers=num_layers)
        self.fc_out = nn.Linear(d_model, vocab_size)
   
    def forward(self, target_seqs, memory, target_mask):
        embedded = self.embedding(target_seqs)
        embedded = self.positional_encoding(embedded)
        embedded = self.dropout(embedded)
   
        # No need for permute if batch_first=True
        output = self.transformer_decoder(embedded, memory, target_mask)
        return self.fc_out(output)
   

5. To debug this issue:

a) Print the shapes of your tensors:

def forward(self, target_seqs, memory, target_mask):
    print(f"Target seqs shape: {target_seqs.shape}")
    print(f"Memory shape: {memory.shape}")
    print(f"Target mask shape: {target_mask.shape}")
    # ... rest of the forward method

b) Try reducing these parameters:

• Batch size
• Sequence length (max_seq_length)
• Model dimension (d_model)
• Number of heads (num_heads)
• Number of layers (num_layers)

c) Add gradient checkpointing more strategically: from torch.utils.checkpoint import checkpoint

class TransformerDecoder(nn.Module):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.use_checkpointing = True  # Add a flag for checkpointing

    def forward(self, target_seqs, memory, target_mask):
        if self.use_checkpointing and self.training:
            return checkpoint(self._forward, target_seqs, memory, target_mask)
        return self._forward(target_seqs, memory, target_mask)

    def _forward(self, target_seqs, memory, target_mask):
        # Original forward pass code here
        pass

Could you share:

1. What are the dimensions of your input data?
2. The values you're using for d_model, num_heads, and num_layers?
3. Your batch size?

This would help pinpoint the exact cause of the memory issue.

--access-logfile option may be required like:

gunicorn --access-logfile /tmp/gunicorn.log --error-logfile /tmp/gunicorn.log --capture-output --log-level info

Cloudflare provide free tunnel. You can try with it.

• Document: https://developers.cloudflare.com/cloudflare-one/connections/connect-networks/

• Install cloudflare tunnel on your local, publish your local with Cloudflare's domain. (.... trycloudflare.com)

كيف نبيراتي كونت إنتغرام هضا إلحساب يرجي ان يتصكر على هضا إلحساب https://www.instagram.com/t_h_e_______q_u_e_e_n/ وكيف تعريف إيل Mot a passé

Is there anyway now to get this data? For example if I want to get horuly pricing for N2-standard-2 programmatically

In my case, I deleted the “.idea” file and reconfigured all settings.

Just found a solution for the "missing dll" issue

Solving the OpenCV DLL load failed Issue: A Step-by-Step Guide

If you’re using OpenCV with GPU acceleration (CUDA and cuDNN) and encountering the error ImportError: DLL load failed while importing cv2: The specified module could not be found, this article will walk you through diagnosing and fixing the issue based on a real-world example.

The Problem

While setting up OpenCV for Python 3.10 with GPU support, I encountered the following error when trying to import OpenCV (cv2):

Traceback (most recent call last):
  File "test.py", line 3, in <module>
    import cv2
  File "C:\Python310\lib\site-packages\cv2\__init__.py", line 181, in <module>
    bootstrap()
  File "C:\Python310\lib\site-packages\cv2\__init__.py", line 153, in bootstrap
    native_module = importlib.import_module("cv2")
  File "C:\Python310\lib\importlib\__init__.py", line 126, in import_module
    return _bootstrap._gcd_import(name[level:], package, level)
ImportError: DLL load failed while importing cv2: The specified module could not be found.

Environment Details:

• Python Version: 3.10.11
• OpenCV Version: 4.7.0 (custom-built from source with CUDA support)
• CUDA Version: 11.8
• cuDNN Version: 8.9.7
• Build Tool: Visual Studio 2019 (MSVC 14.29)
• OS: Windows 10

Paths Configured:

• PATH Environment Variable:

  C:\DevelopmentTools\OpenCV\install\bin
  C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin
  C:\Program Files\NVIDIA\CUDNN\v8.9.7\bin
  

• LIB Environment Variable:

  C:\DevelopmentTools\OpenCV\install\x64\vc16\lib
  C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\lib\x64
  C:\Program Files\NVIDIA\CUDNN\v8.9.7\lib\x64
  

• INCLUDE Environment Variable:

  C:\DevelopmentTools\OpenCV\install\include
  C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\include
  C:\Program Files\NVIDIA\CUDNN\v8.9.7\include
  

The Cause

This error is common when OpenCV cannot locate the shared libraries (DLLs) required during its runtime. Specifically:

1. Python 3.8+ DLL Loading Behavior:

   • Starting with Python 3.8, the way Python loads DLLs has changed. It no longer automatically searches the system PATH environment variable for DLLs unless explicitly directed to do so.
   • As a result, even though the required DLLs (like opencv_world470.dll, cudart64_118.dll, and cudnn64_8.dll) were present in the paths, Python didn’t load them.

2. OpenCV Loader Script:

   • OpenCV’s loader script (cv2/__init__.py) dynamically handles paths for its binaries. However, it depends on either os.add_dll_directory() (Python 3.8+ feature) or a properly configured PATH.
   • If these paths were not set correctly during runtime, OpenCV couldn’t load the required dependencies.

The Solution

Here’s the step-by-step process to resolve this issue:

1. Verify Environment Variables

Ensure the following paths are included in your environment variables:

• Add OpenCV, CUDA, and cuDNN binary paths to the PATH:

  C:\DevelopmentTools\OpenCV\install\bin
  C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin
  C:\Program Files\NVIDIA\CUDNN\v8.9.7\bin
  

• Add library paths to the LIB environment variable:

  C:\DevelopmentTools\OpenCV\install\x64\vc16\lib
  C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\lib\x64
  C:\Program Files\NVIDIA\CUDNN\v8.9.7\lib\x64
  

• Add include paths to the INCLUDE environment variable:

  C:\DevelopmentTools\OpenCV\install\include
  C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\include
  C:\Program Files\NVIDIA\CUDNN\v8.9.7\include
  

2. Use os.add_dll_directory() for Python 3.8+

If you’re using Python 3.8 or newer, explicitly add these directories in your Python script before importing OpenCV:

import os

# Add OpenCV, CUDA, and cuDNN binary paths
os.add_dll_directory(r'C:\DevelopmentTools\OpenCV\install\bin')
os.add_dll_directory(r'C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.8\bin')
os.add_dll_directory(r'C:\Program Files\NVIDIA\CUDNN\v8.9.7\bin')

import cv2
print(cv2.getBuildInformation())

This ensures Python explicitly knows where to find the required DLLs.

3. Recheck Required DLLs

Use a tool like Dependencies to analyze the cv2.cp310-win_amd64.pyd file. This tool shows if any required DLLs are missing. Common missing files include:

• cudart64_118.dll (CUDA runtime)
• cudnn64_8.dll (cuDNN library)
• opencv_world470.dll (OpenCV core)

Ensure these files exist in the specified paths.

4. Update Visual C++ Redistributable

Install the latest Visual C++ Redistributable for Visual Studio 2019:

• Download from Microsoft.

5. Test OpenCV

After completing the above steps, test OpenCV with a simple script:

import cv2
print(cv2.__version__)
print(cv2.getBuildInformation())

Conclusion

This issue stemmed from Python’s updated DLL loading behavior and OpenCV’s dependency on dynamically linked libraries. By ensuring that all required DLLs are in the correct paths and explicitly specifying these paths for Python, I was able to resolve the problem.

Key Takeaways

• For Python 3.8+, use os.add_dll_directory() to manage DLL paths.
• Ensure environment variables (PATH, LIB, INCLUDE) are configured correctly.
• Use tools like Dependencies to diagnose missing DLLs.
• Keep your CUDA, cuDNN, and Visual C++ Redistributable versions compatible with your OpenCV build.

Feel free to use this guide to resolve similar issues in your setup!

1. You cannot call any constructor of your sealed class in normal code. You can call its constructor when inheriting only.

2. You must describe child classes only in the same file as this class.

ok ,I got it

The reason for this is that containerd version 2 has a very different configuration specification compared to version 3, and the links online and in my research are all for version 2, but the actual runtime environment is version 3

The solutions are as follows

Registry Configuration - Introduction This document is a very important reference

 mkdir -p /etc/containerd/certs.d/privatehub.ye:5000

root@cp01:~# cat hosts.toml
server = "https://registry-1.docker.io"

[host."http://privatehub.ye:5000"]
  capabilities = ["pull", "resolve", "push"]
  skip_verify = true

cp hosts.toml /etc/containerd/certs.d/172.26.22.242:5000/hosts.toml

systemctl restart containerd.service

You can just set some keywords instead of a fixed date

keywords like: last Monday or tomorrow etc.

example:

it's work Menu Bar: View > Hide Code Review Reference

Turns out the api key I was using (the one in the apiKey field of my firebase config object) did not have my *.firebaseapp.com domain set up in the website restrictions section. adding it there allowed it to work although i suspect theres a better way to get it working for localhost? its solved my issue for now though

Click inside div element and it will highlight yellow for the beginning of the div and end of the current div

For a single command, please try git rebase main feature_branch && git checkout main && git merge --ff-only feature_branch

I'm not sure how it worked but I did

axios.defaults.withCredentials = true

In each file that uses import axios

This is what worked for me:

-_exists_:field_name

Taken from here

app("/",function()
{
//some logic here
})

//we have to write this way
app.get("/",function()
{
//some logic here
})

please check the two links below if it would help: https://www.percona.com/blog/how-to-reclaim-space-in-innodb-when-innodb_file_per_table-is-on/ https://dba.stackexchange.com/questions/8982/what-is-the-best-way-to-reduce-the-size-of-ibdata-in-mysql

Here is only one option how to do that

https://docs.github.com/en/organizations/managing-oauth-access-to-your-organizations-data/denying-access-to-a-previously-approved-oauth-app-for-your-organization

Same problem for me.

I used this flag:

pip3 install Adafruit_DHT --config-settings="--build-option=--force-pi"

Here is how to pass an argument to the setup script: https://github.com/pypa/pip/issues/11358#issuecomment-1493207214

Here is how to force a specific platform: https://github.com/adafruit/Adafruit_Python_DHT/blob/8f5e2c4d6ebba8836f6d31ec9a0c171948e3237d/setup.py#L33

For poor souls like me getting this error (right on "package" instruction) in JetBrains IDE with Go linter plugin on Windows for completely valid imports, check line separators of file. I believe diff tool needed for goimports linter have problems with CRLF. After converting to LF all was fine.

In answer by @veefu statement

You can’t supply a type when you use New-Variable so if you need a read only or constant variable then create it as shown above then use Set-Variable to make it read only or constant.

• this is wrong.

Its exactly the opposite - you can't modify Constant option after you created variable. New-Variable command allows to set options. Set-Variable allows to set options, but doesn't allow to set option - Constant.

This is clearly visible in New-Variable documentation: PowerShell New-Variable [-Option ] from Documentation: https://learn.microsoft.com/en-us/powershell/module/microsoft.powershell.utility/new-variable?view=powershell-5.1#-option

Also none of the above mentioned methods work in Powershell except .NET method. They are all - strings in result, when I use GetType() and Attributes property of variable never gets populated.

The only way to effectively get rid of such process without reboot is to log off

As @Garvin Hicking mentioned, xdebug is super helpful, especially in the backend. But if you can't or don't want to run xdebug, just try putting a die() after your debug.

    \TYPO3\CMS\Core\Utility\DebugUtility::debug($whatEver);
    die();

Support for infinity intervals was added in PostgreSQL 17.

Check out the release notes.

With this version, your code works: https://dbfiddle.uk/lRKTMLZ3

I ended-up using the GitHub GraphQL API with actions/github-script into workflow, instead of actually using the binary. The step handles properly both additions and deletions, with CreateCommitOnBranch mutation.

Previous implementation, without verified signature:

New implementation:

You can examine the actual PR with the new implementation.

Thanks to @MrWhite Latest working solution that covers the file names containing spaces:

RewriteRule ^(.+)$ viewProfile.php?Name=$1 [B,L]

I have listed the different documentation that can help you :

AWS Glue permission : https://docs.aws.amazon.com/glue/latest/dg/permissions.html

IAM Role for Amazon Web Service : https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies.html

AWS RedShift permission : https://docs.aws.amazon.com/redshift/latest/mgmt/grant-privileges.html

S3 permissions : https://docs.aws.amazon.com/AmazonS3/latest/userguide/using-with-s3-actions.html

Dynamo IAM Permission : https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/iam-policy-examples.html

EMR IAM Permission : https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-iam-roles.html

And an example of configuration in CloudFormation, i let you try it and adapt it if necessary :

Resources:
  GlueJobRole:
    Type: AWS::IAM::Role
    Properties:
      AssumeRolePolicyDocument:
        Version: "2012-10-17"
        Statement:
          - Effect: "Allow"
            Principal:
              Service: "glue.amazonaws.com"
            Action: "sts:AssumeRole"
      Policies:
        - PolicyName: "GlueJobS3Policy"
          PolicyDocument:
            Version: "2012-10-17"
            Statement:
              # Permissions for Redshift
              - Effect: "Allow"
                Action:
                  - "redshift:DescribeClusters"
                  - "redshift:CopyFromS3"
                  - "redshift:Select"
                Resource: "*"
              
              # Permissions for S3
              - Effect: "Allow"
                Action:
                  - "s3:GetObject"
                  - "s3:PutObject"
                  - "s3:ListBucket"
                  - "s3:ListBucketMultipartUploads"
                Resource:
                  - "arn:aws:s3:::your-s3-bucket-name/*"
                  - "arn:aws:s3:::your-s3-bucket-name"
              
              # Permissions for Glue resources
              - Effect: "Allow"
                Action:
                  - "glue:GetTable"
                  - "glue:GetTableVersion"
                  - "glue:GetTableVersions"
                  - "glue:GetDatabase"
                  - "glue:GetPartitions"
                  - "glue:BatchGetPartition"
                  - "glue:CreateJob"
                  - "glue:GetJob"
                  - "glue:UpdateJob"
                  - "glue:StartJobRun"
                  - "glue:GetJobRun"
                Resource: "*"
              
              # Permissions for DynamoDB (optional)
              - Effect: "Allow"
                Action:
                  - "dynamodb:Scan"
                  - "dynamodb:Query"
                Resource: "*"
              
              # Permissions for EMR (optional)
              - Effect: "Allow"
                Action:
                  - "elasticmapreduce:ListClusters"
                  - "elasticmapreduce:DescribeCluster"
                  - "elasticmapreduce:DescribeStep"
                Resource: "*"

Docker documentation about bridge networking(https://docs.docker.com/engine/network/drivers/bridge/) :

For Docker, a bridge network uses a software bridge which allows containers connected to the same bridge network to communicate, while providing isolation from containers which are not connected to that bridge network.

Docker documentation about host networking (https://docs.docker.com/engine/network/drivers/host/) :

If you use the host network driver for a container, that container’s network stack is not isolated from the Docker host. For instance, if you run a container which binds to port 445 and you use host networking, the container’s application will be available on port 445 on the host’s IP address.

If you want to deploy multiple containers connected between them with a private internal network use bridge networking. If you want to deploy a container connected to the same network stack as the host (and access the same networks as the host) use host networking. And, if you want to publish some ports, run the container with the --publish or -p option, such as -p 445:445.

After disabling istio-proxy for the services connecting to Kafka, everything start working. On a different stand, it all works fine without disabling. Why this is so is not yet clear.

Yaron. Can we talk about this game? Thanks, Yehuda ([email protected]).

Yes, you can redirect Users to Google Identity Platform (Google IDP) and return them to Discourse but with customization. However, Google IDP does not provide a hosted login mask that aggregates all the providers. You'll need to build or use a custom login page for this.

These are potential workarounds for the Missing Login Mask.

• In your Google Identity Platform settings, ensure you’ve added and configured the additional providers (e.g., Apple, Facebook, or email/password) under the Identity Providers section.

• Utilize Firebase Authentication, part of Google's Identity Platform, which offers a customizable UI and supports multiple authentication providers.

• Set up a custom authentication system using Firebase to manage user sign-ins and then integrate it with Discourse.

I hope this information is useful in addressing your issue.

Simply using list-style: none; worked for me!

summary {
    list-style: none;
}

I had this exact same issue. What worked for me was going into the JSON file and changing the "nbformat" value to 4 and the "nbformatminor" value to 0. I had my nbformat version set to 5 and apparently that version won't render on Github. You can change the values of those two lines of JSON straight on Github by going into the "Code" tab.

Almost everything on git-hub must be compiled, as it is a source code. You need to build the files, which installs them locally. Hope that helps.

Your app seems to be using background location. Whether or not you need it is a different matter.

If your app can provide its functionality while requiring the user to have the app open, then you don’t need the permission.

Background location access is when you need to know the user’s location when the app is in the background.

If you are following the user’s route and don’t expect them to have your app in the foreground, then you do need it.

Your motivation would be exactly why you need it and how it benefits the user - if you are tracking routes as the main purpose of your app, then that is the benefit to the user.

The restriction is intended to keep users secure and not to hamper legitimate functionality. Many apps have a good reason to need background location, but you need to be clear on how you’re using it.

ghci> :set +m
ghci> let pascal 1 = [1]
ghci|     pascal n = zipWith (+) (0:pascal (n-1)) (pascal (n-1) ++ [0])
ghci|

ghci> pascal 3
[1,2,1]
ghci> pascal 4
[1,3,3,1]
ghci> pascal 5
[1,4,6,4,1]
ghci> pascal 6
[1,5,10,10,5,1]

enter code hereAdb Shell simples battery reset 9999999999999999999999999999999999999

I've solved the issue by changing out UnderscoredNamingConvention.Instance with HyphenatedNamingConvention.Instance in the deserializer

I am also facing the issue where http.server is not ruuning after packaging into exe by PyInstaller. Here is the issue posted: https://github.com/pyinstaller/pyinstaller/issues/8952.

Can you please help?

Can you try using this instead of the black flag you are using

🏴

Ref.: https://emojipedia.org/black-flag#emoji

(The black flag you are using if I copy it and then paste it into notepad I get six funny chars , squares, after it which I don't get with the above one. But perhaps there is a explanation for that? )

This is probably because you are trying to run Moodle in PHP 8

Encountered the same issue when I was migrating the servers, and when I switched the PHP version to PHP 7, it worked flawlessly.

thanks @basim bro I was trying to resolve this issue from 3 days.Finally i got this .Actually the request was taking a lot of time because of mongodb atlas ,because i have not added the "access from anywhere feature" in mongodb atlas

How about clickAndHold in karate to draw a line in canvas. I tried using down() and up() and not working. Can anyone help

I found out what the Problem is:

I use Expo Go on my Phone to simulate the App. I think the cause is that the App tries to connect to the local appwrite but on my Phone, that of course does not exist there. When i open the App in the web on my PC it works.

I will post here again if i find a workaround or fix for that.

Consider using sf::VertexArray of type sf::PrimitiveType::TriangleFan which you may use as circle if you choose the number of elements large enough. See SFML : designing your own entities with vertex arrays for more details about vertex drawing.

For given example of array

sf::VertexArray wheel(sf::PrimitiveType::TriangleFan, 6);

wheel[0].position = sf::Vector2f(100.f, 100.f); // Central point
wheel[1].position = sf::Vector2f(150.f, 100.f);
wheel[2].position = sf::Vector2f(100.f, 150.f);
wheel[3].position = sf::Vector2f( 50.f, 100.f);
wheel[4].position = sf::Vector2f(100.f,  50.f);
wheel[5].position = sf::Vector2f(150.f, 100.f);

wheel[0].color = sf::Color::White;
wheel[1].color = sf::Color::Red;
wheel[2].color = sf::Color::Yellow;
wheel[3].color = sf::Color::Green;
wheel[4].color = sf::Color::Blue;
wheel[5].color = sf::Color::Magenta;

you'll get such a picture

Well, turns out answer was simply adding notification to property Courier in Delivery class:

        public Courier? Courier 
    {
        get { return courier; }
        set
        {
            courier = value;
            OnPropertyChanged("NameCourierFull");
        }
    }

That's it, now courier name in DataGrid refresh every time new courier is picked. But funny thing is that if I try to add there OnPropertyChanged("CourierUid") that doesn't help refresh CourierUid. Well I don't need to do it anyway but if anyone knows proper way to make it, I'd still like to know how. Just in case.

Alright, I found the answer to the question: Add the data file and then create the DBMS as mentioned in the post. That is it! No need to follow further steps; the graph is already created in the database. Hopefully this helps everyone. Also, I am using Neo4j Desktop and not aura.

Similarly to @chux's answer, I'm used to do something like this ;

#define MAX_SZ 10485760UL
#define BLOCK_SZ 64UL

#define DP_BUF_RSV_SIZE     (256 * 16 * BLOCK_SZ)
#define DP_BUF_UL_SIZE      (3072 * 16 * BLOCK_SZ)
#define DP_BUF_DL_SIZE      (4096 * 16 * BLOCK_SZ)
#define DP_BUF_COMMON_SIZE  (2048 * 16 * BLOCK_SZ)

#if ((DP_BUF_RSV_SIZE + DP_BUF_UL_SIZE + DP_BUF_DL_SIZE + DP_BUF_COMMON_SIZE) > MAX_SZ)
#error Too large

// Eventually
#elif ((DP_BUF_RSV_SIZE + DP_BUF_UL_SIZE + DP_BUF_DL_SIZE + DP_BUF_COMMON_SIZE) % BLOCK_SZ)
#error Not multiple of 64
#endif

So the program wouldn't compile if DP_BUF_RSV_SIZE + DP_BUF_UL_SIZE + DP_BUF_DL_SIZE + DP_BUF_COMMON_SIZE is superior to MAX_SZ, or if it ain't a multiple of 64.

I mean this works:

document.onload = () => {document.write("Goodbye world!")}

<div id="foo">
    <div class="bar">
        Hello world!
    </div>
</div>

Is it possible to create another instance of the javascript console

In browser, consoles cannot be instantiated. Only one instance exists. So to group data together you need to create new own separate method which will save all messages and output them into some place.

In Node.JS you can create new instances of Console class and set out/err streams for new instance.

https://nodejs.org/api/console.html#new-consolestdout-stderr-ignoreerrors

In Jupyter first go to Settings, then Settings Editor, then Text Editor and check the case Code Folding. Tried it yet, no need for extension.

You need to expose the relevant ports on the host IP. You can do that using the -p switch to docker run.

For example:

docker run -p 445:445 container

The above will map port 445 on the local host to the docker container. Make sure nothing else is listening on the same port.

Its the issue of invalidation of SHA-1 and SHA-256 fingerprints . You may generate new keys by ./gradlew signingReport and load them into firebase console

Apparently the original code seems to work in some cases. It would surely be helpful to give the Xcode version used in each case.

I had same issue: Created ps1 file in share and task scheduler to run with -Bypass file \fileshare deployed with GPO under NT AUTHORITY\System to run, but it failed with permission denied, even dir \sharedfolder was showing directory. Tried many times didn't work but when I ran the script (ps1) localy it ran fine, so it has to be permissions on the share folder which it had everyone and SYSTEM as shared permissions to run and Security as well.

The fix was when I add "Authenticated Users" under the NTFS (Security Tab) on folder that was shared, taskscheduler start working.

As you can read in the Javadocs, this class actually exists and your code should work.

Sadly I don't have the reputation to just comment on your question and tell you to improve it.

Use the modified below code line, instead of the one in your first message;

   sText = rSelectedRange.Cells(iRow, iColumn).Text

The problem only because of the missing of Microsoft Visual C++ Redistributable.

I have installed using this link and problem solved.

This resolved the issue for me.

Cannot connect to etcd #454

  ETCD_ENABLE_V2: "true"
  ALLOW_NONE_AUTHENTICATION: "yes"
  ETCD_ADVERTISE_CLIENT_URLS: "http://etcd:2379" <---
  ETCD_LISTEN_CLIENT_URLS: "http://0.0.0.0:2379"

I face the same problem:

1 Failed download: ['XAUUSD=X']: YFTzMissingError('$%ticker%: possibly delisted; no timezone found')

But when I try with AAPL it works!