Daily Error Troubleshooting Log

Writing code always comes with a bunch of problems.

I am recording some of the trivial issues and their solutions here.

1. Error when running npx docusaurus start​

• Error Message:

  file:///home/user/workspace/blog/node_modules/@docusaurus/core/bin/docusaurus.mjs:30
  process.env.BABEL_ENV ??= 'development';
                      ^^^
  
  SyntaxError: Unexpected token '??='
  

• Solution:

  The ??= operator requires Node.js version 15.0.0 or higher.

  nvm install node
  nvm use node
  

2. 'choco' command not recognized​

• Error Message:

  PS C:\Windows\System32> choco install git -y
  >>
  choco : The term 'choco' is not recognized as the name of a cmdlet, function, script file, or operable program. Check the spelling of the name, or if a path was included, verify that the path is correct and try again.
  At line:1 char:1
  + choco install git -y
  + ~~~~~
      + CategoryInfo          : ObjectNotFound: (choco:String) [], CommandNotFoundException
      + FullyQualifiedErrorId : CommandNotFoundException
  

• Solution:

  This indicates that Chocolatey was not successfully installed, often due to not running PowerShell as an Administrator.

  Run PowerShell as an Administrator, and then execute the Chocolatey installation command again.

  Set-ExecutionPolicy Bypass -Scope Process -Force; [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.ServicePointManager]::SecurityProtocol -bor 3072; iex ((New-Object System.Net.WebClient).DownloadString('https://community.chocolatey.org/install.ps1'))
  

3. Chocolatey installation failure​

• Error Message:

  Warning: An existing Chocolatey installation was detected. Installation will not continue. This script will not overwrite existing installations.
  If there is no Chocolatey installation at 'C:\ProgramData\chocolatey', delete the folder and attempt the installation again.
  
  Please use choco upgrade chocolatey to handle upgrades of Chocolatey itself.
  If the existing installation is not functional or a prior installation did not complete, follow these steps:
  - Backup the files at the path listed above so you can restore your previous installation if needed.
  - Remove the existing installation manually.
  - Rerun this installation script.
  - Reinstall any packages previously installed, if needed (refer to the lib folder in the backup).
  
  Once installation is completed, the backup folder is no longer needed and can be deleted.
  

• Solution:

  This indicates that Chocolatey is already installed. Please remove the old installation before reinstalling.

  Remove-Item "C:\ProgramData\chocolatey" -Recurse -Force
  

4. Remote port forwarding​

• Description:

  You’ve started a service on a remote machine, such as TensorBoard, but can't access it directly, so you need to forward the port through your local machine.

• Solution:

  Assuming the service is running on port 6006 on the remote machine, and you want to access it on the same port on your local machine.

  When using SSH to log in, you can forward the port using the -L parameter:

  ssh -L 6006:localhost:6006 user@remote_ip_address
  

  This way, you can access the TensorBoard service on the remote machine via http://localhost:6006 on your local machine.

5. Inconsistent Web Rendering Behavior in Development and Deployment Environments​

• Description:

  You've set the layout style of the blog in custom.css:

  .container {
    max-width: 90%;
    padding: 0 15px;
    margin: 0 auto;
  }
  

  In the deployment phase, this style seems to be overridden by other higher-priority styles, but in the development phase, this style is normal.

• Solution:

  Be more specific in selecting the target:

  body .container {
    max-width: 90%;
    padding: 0 15px;
    margin: 0 auto;
  }
  

6. Turbojpeg Warning When Reading Images​

• Description

  When reading images, the following warning messages appear:

  turbojpeg.py:940: UserWarning: Corrupt JPEG data: 18 extraneous bytes before marker 0xc4
  turbojpeg.py:940: UserWarning: Corrupt JPEG data: bad Huffman code
  turbojpeg.py:940: UserWarning: Corrupt JPEG data: premature end of data segment
  

• Solution

  To avoid these annoying warnings, you should filter out the problematic images:

  import cv2
  import warnings
  
  data = ['test1.jpg', 'test2.jpg', 'test3.jpg']
  
  for d in data:
    with warnings.catch_warnings(record=True) as w:
      warnings.simplefilter("always", UserWarning)
  
      # Read the image and see if there are any warnings
      cv2.imread(d)
  
      # Remove the data if warnings are present
      if w:
        data.remove(d)
  
  # Saving the filtered data
  

7. Docusaurus Deployment: showLastUpdateTime: true Not Working​

• Description

  In docusaurus.config.js, you set showLastUpdateTime: true and showLastUpdateAuthor: true, but after deployment, you find that it has no effect. The rendered page displays the same time and author?

• Solution

  The problem is caused by an incorrect setting when checking out the branch during deployment, which prevents git from correctly obtaining the last update time and author.

  Change it like this:

  steps:
    - uses: actions/checkout@v4
      with:
        fetch-depth: 0
  

  Setting fetch-depth: 0 will solve the problem.

8. Checking Error Logs Inside a Docker Container​

• Description

  A service is running inside a Docker container, but the service has encountered an error and is not functioning properly, so you need to check the error logs.

• Solution

  First, check the target container's ID:

  docker ps
  

  Then, view the logs:

  docker logs container_id
  

  Entering two separate commands to view the desired error messages is quite cumbersome, so we can simplify it into a single command.

  Assuming the target name to be checked is: TARGET_NAME, the command is as follows:

  docker logs $(docker ps -q --filter "ancestor=TARGET_NAME")
  

9. Checking the i18n Status in Docusaurus​

• Description

  How can we check the current language status in Docusaurus?

• Solution

  You can use i18n to retrieve the current language status:

  import useDocusaurusContext from "@docusaurus/useDocusaurusContext";
  
  const {
    i18n: { currentLocale },
  } = useDocusaurusContext();
  

  Then, you can use the currentLocale variable to obtain the corresponding language data.