Resolving PermissionError in Python Multiprocessing with Scheduled Tasks

Encountering a `PermissionError` when attempting to run multiple Python scripts concurrently? Discover how to effectively schedule and execute your scripts without conflicts.
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Troubleshooting PermissionError While Running Python Scripts Concurrently

If you’ve been working with Python and trying to schedule multiple scripts to execute simultaneously, you might have run into some challenges. One common issue developers face is the PermissionError: [WinError 5] Access denied, as well as problems with the scripts running sequentially instead of concurrently. This guide explores how to address these issues, ensuring your Python scripts run smoothly at scheduled intervals without any hiccups.

Understanding the Problem

In your setup, you want to run two different .py files concurrently at specific times every day. This involves using the multiprocessing module alongside a scheduling tool. While you managed to run the scripts without using the schedule module, adding it into the mix presented errors.

The main errors you've come across include:

A PermissionError indicating access denial.

Scripts executing sequentially instead of concurrently.

Let’s break down how to effectively solve this problem.

Solution Steps

1. Import Necessary Modules

Start by importing the required modules: multiprocessing, time, and schedule. It’s also wise to directly import the modules you’re planning to use (in this case, International and National).

2. Define Your Functions

Rather than importing modules within processes, define your functions to trigger these modules. Here's how you can set up your functions for multiprocessing:

Function for National Script:

[[See Video to Reveal this Text or Code Snippet]]

Function for International Script:

[[See Video to Reveal this Text or Code Snippet]]

3. Scheduling the Functions

Set up your scheduling inside the if __name__ == '__main__' block. This ensures the scheduling processes only run when the script is executed and prevents unintended behavior when the script is imported elsewhere.

Here’s how the complete code looks:

[[See Video to Reveal this Text or Code Snippet]]

4. Running the Code

After structuring your code as shown above, running the script should allow the tasks to execute concurrently at the specified time without encountering the PermissionError. If you still experience issues, it’s worthwhile to check permissions and ensure that your Python environment is correctly set up.

Additional Considerations

It might also be beneficial to consider other tools for scheduling tasks, such as cron (on Unix-like systems) or Task Scheduler (on Windows), which can manage tasks in a more stable environment.

Conclusion

By modifying your approach to use functions directly defined for the multiprocessing calls and correctly setting your schedules in the __main__ context, you can effectively run your Python scripts concurrently without encountering access issues. If you follow the recommended steps, you should be able to run your scripts seamlessly every day at the desired time. Happy coding!