How to run different Jupyter notebooks conditionally in a AWS Sagemaker notebook instance

Question

I have a AWS sagemaker notebook instance which have 2 different jupyter notebooks. There are certain conditions in which each of it should work.

So, if the consition A exist, the Jupyter Notebook 1 should run and if Condition B exist, the Jupyter Notebook 2 should run.

I have tried this code so far, but it doesnt work:

if condition A:

    sm_client = boto3.client('sagemaker')
    notebook_instance_name = NotebookInstanceName
    notebook_instance_name = 'Calorie-1615128222'
    url = sm_client.create_presigned_notebook_instance_url(NotebookInstanceName=notebook_instance_name)['AuthorizedUrl']
    
    print(url)

    url_tokens = url.split('/')
    http_proto = url_tokens[0]
    http_hn = url_tokens[2].split('?')[0].split('#')[0]

    s = requests.Session()
    r = s.get(url)
    cookies = "; ".join(key + "=" + value for key, value in s.cookies.items())
    print(cookies)

    ws = websocket.create_connection(
        "wss://{}/terminals/websocket/1".format(http_hn),
        cookie=cookies,
        host=http_hn,
        origin=http_proto + "//" + http_hn
    )
    
    print(ws)
    
    # ws = websockets.connect("wss://{}/terminals/websocket/1".format(http_hn))
    
    ws.send("""[ "stdin", "jupyter nbconvert --execute --to notebook --inplace /home/ec2-user/SageMaker/Calorie/Notebook1.ipynb 
--ExecutePreprocessor.kernel_name=conda_tensorflow2_p36 --ExecutePreprocessor.timeout=1500\\r" ]""")
    #ws.send("""[ "stdin", "jupyter nbconvert --execute Notebook1.ipynb --ExecutePreprocessor.kernel_name=conda_tensorflow2_p36 --ExecutePreprocessor.timeout=1500\\r" ]""")
    
    time.sleep(5)
    ws.close()
    print("websocket client created")
    #return None
    

Please help. Many Thanks

Answer 1

Have you considered orchestrating this using AWS Step Functions or SageMaker Pipelines depending on your use case?