Overview :-

Have you ever found yourself scrolling through pages of AWS Transcribe jobs, wondering how you could clear out old or unnecessary ones without spending the whole afternoon clicking away? It turns out, Python is your friend in this scenario. Python boasts simple, effective tools that can help manage and delete AWS Transcribe jobs in bulk, saving you time and reducing clutter in your AWS environment. From a quick cleanup to managing resources efficiently, Python scripts provide a straightforward solution to handle these tasks.

Pre-requisites :-

Before diving into the heart of deleting AWS Transcribe jobs using Python, here is a checklist of what you’ll need:

• AWS Account: Obviously, you need access to an account where your Transcribe jobs are located.

• Python Installed: Make sure Python is installed on your computer. Any version above 3.0 should do the trick.

• AWS CLI: Install and configure AWS Command Line Interface on your machine. This lets your scripts talk to the AWS services.

• Boto3 Library: Boto3 is the Amazon Web Services (AWS) SDK for Python. It allows Python developers to write software that makes use of services like Amazon S3 and Amazon EC2.

Procedure :-

Step-1 :- Create a file with name delete-transcript-jobs.py on your desktop.

Step-2 :- Copy the below code in the file

import boto3

def delete_all_transcribe_jobs():
    # Initialize the Amazon Transcribe client
    transcribe = boto3.client('transcribe')

    # List all transcription jobs
    response = transcribe.list_transcription_jobs()

    # Check if there are any transcription jobs
    if 'TranscriptionJobSummaries' in response:
        # Iterate through each job and delete it
        for job in response['TranscriptionJobSummaries']:
            # Get the name of the transcription job
            job_name = job['TranscriptionJobName']
            print(f"Deleting job: {job_name}")

            # Delete the transcription job
            transcribe.delete_transcription_job(TranscriptionJobName=job_name)
            print(f"Job {job_name} deleted successfully.")
    else:
        print("No transcription jobs found.")

# Call the function to delete all transcription jobs
delete_all_transcribe_jobs()

Step-3 :- Open a terminal window and configure your Aws credentials. Next run the command to execute the script.

python3 delete-transcript-jobs.py

Step-4 :- After executing the command u can able to see that the transcript jobs is getting deleted.

Conclusion :-

Here we are! You’ve just learned how to manage your AWS Transcribe jobs using Python effectively. It’s like having a little digital assistant at your fingertips. Remember, managing digital resources efficiently not only saves time but also helps keep your AWS costs down.

If you ever find yourself getting overwhelmed by the small, repetitive tasks, remember that Python and Boto3 are here to help streamline your workflows. Happy coding, and may your digital environment stay as neat as a new pin!