Tux

Executing a Cron Job Within an Anaconda Environment

 in Bash / GNU/Linux  tagged anaconda / conda / cron / crontab by

For those seeking to automate their Python scripts using cron jobs within an Anaconda environment, there’s a straightforward method to ensure your scripts run under the correct environment. This approach involves leveraging the capabilities of bash and the configuration of your cron environment to recognize and activate the necessary Anaconda environment. Here’s how to set it up:

  1. Export Anaconda Initialization to a Dedicated Configuration File First, isolate the Anaconda initialization snippet from your ~/.bashrc file by copying it to a new file, say ~/.bashrc_for_cron. This step ensures the cron environment can source the necessary configurations to activate Anaconda environments. Make sure that:
  • The file is readable by the user scheduling the cron job.
  • The file is secured against write access from other users to mitigate security risks.
  1. Configure Cron to Use Bash and Source the Anaconda Configuration Edit your crontab configuration by running crontab -e and prepend your cron jobs with two crucial lines:
   SHELL=/bin/bash
   BASH_ENV=~/.bashrc_for_cron

These lines configure cron to execute jobs using bash instead of the default sh shell and to source the Anaconda configurations from ~/.bashrc_for_cron. When invoked by cron, this setup ensures that bash is aware of the necessary environment to activate Anaconda environments.

  1. Activate Anaconda Environment Before Executing Your Script When scheduling your Python script in crontab -e, prefix the command with the conda activate instruction to switch to your desired Anaconda environment. For instance, to run a script at 12:30 AM every day within a specific Anaconda environment, your cron job entry would look like:
   30 0 * * * conda activate opencv_env; python /path/to/script.py

This ensures that the script executes within the context of the specified Anaconda environment, opencv_env, leveraging any dependencies or configurations defined within that environment.

By following these steps, you can seamlessly schedule and run Python scripts under specific Anaconda environments, leveraging cron’s scheduling capabilities while ensuring the correct environment and dependencies for your scripts.

Various problems with legacy SSH systems

 in Bash / GNU/Linux  tagged diffie-hellman-group1-sha1 / HostKeyAlgorithms / KexAlgorithms / ssh / ssh-dss by

Case 1

ssh [email protected];

Unable to negotiate with 192.168.1.1 port 22: no matching key exchange method found. Their offer: diffie-hellman-group1-sha1

We solved this problem using the following command:

ssh -oKexAlgorithms=+diffie-hellman-group1-sha1 [email protected];

Case 2

ssh -oKexAlgorithms=+diffie-hellman-group1-sha1 [email protected];

Unable to negotiate with 192.168.1.1 port 22: no matching host key type found. Their offer: ssh-rsa,ssh-dss

We solved this problem using the following command:

ssh -oKexAlgorithms=+diffie-hellman-group1-sha1 -oHostKeyAlgorithms=+ssh-dss [email protected];

How to Free Space from /var/log by Removing Old Log Files

 in GNU/Linux  tagged /var/log/ / free space / GNU/Linux / ubuntu by

Introduction

Managing disk space is a critical task for system administrators and users alike. In Linux systems, the /var/log directory can become a source of space consumption due to the accumulation of log files. In this post, we’ll explore a simple command to free up space by deleting old compressed log files and discuss its pros and cons.

The Command

The command find /var/log -type f -name "*.gz" -delete is a powerful way to clean up space in the /var/log directory. Here’s a breakdown of what this command does:

  • find /var/log: Searches in the /var/log directory.
  • -type f: Restricts the search to files.
  • -name "*.gz": Looks for files ending with .gz, which are typically compressed log files.
  • -delete: Deletes the files that match the search criteria.

Pros

  1. Efficient Space Management: This command quickly frees up disk space consumed by old, compressed log files, which is essential for the smooth functioning of the system.
  2. Automatable: The command can be automated through a cron job or a script, making regular maintenance easier.
  3. Selective Deletion: It specifically targets .gz files, which are usually older log files that have been compressed, thus keeping the most recent logs intact.

Cons

  1. Potential Data Loss: Important historical data in the log files could be lost if they are deleted without proper review.
  2. Lack of Control Over File Age: This command does not discriminate based on the age of the log files. It deletes all .gz files, regardless of how recently they were compressed.
  3. No Backup: The command executes a direct deletion without creating backups, which could be problematic if a file is deleted accidentally.

Best Practices

  • Review Files Before Deletion: Run the command without the -delete flag first to review which files will be deleted.
  • Implement Log Rotation: Set up log rotation to manage log files systematically, compressing and archiving older logs while deleting the oldest ones.
  • Backup Important Logs: Always keep a backup of important logs before running any deletion command.

Conclusion

While the command find /var/log -type f -name "*.gz" -delete is an effective way to free up space in the /var/log directory, it’s important to use it judiciously. Understanding its pros and cons helps in making informed decisions about log management in a Linux environment.