Azure ML studio designer python executor is outdated

Question

Azure ML studio designer python executor is outdated

Wasim Khan 20

Hey Team,

Explored a lot on Azure ML studio service and found the designer is helpful. Still an issue when I am using the Execute Python Script in the designer it is import all libraries older version and when checked its python version it was also outdated.
How can we upgrade to the latest still not able to figure it out. azuremldesignerpython

Wasim Khan 20 Reputation points

2025-03-04T10:59:04.1966667+00:00

I am using azure ml studio designer(classic) > Create a new pipeline using classic prebuilt components > components > Execute Python Script
Anonymous

2025-03-05T22:34:55.29+00:00
Hi Wasim Khan

In Azure Machine Learning, there are two types of environments: curated and custom. Curated environments come with popular ML frameworks and tools and are available by default in your workspace. They are regularly updated by Azure for the latest releases and security patches. Custom environments, on the other hand, are user-defined and can be created using the az ml environment create command.

Curated environments are supported by cached Docker images, which help lower job preparation costs and speed up model deployment. You can use these environments directly for training or deployment by referencing them with the azure ml:<curated-environment-name>:<version> or azure ml:<curated-environment-name>@latest syntax. Additionally, you can use these curated environments as a base for your custom environments by modifying their Docker files.

You can see the set of available curated environments in the Azure Machine Learning studio UI, or by using the CLI (v2) via az ml environment list. https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-serverless-compute?view=azureml-api-2&tabs=python And this: https://learn.microsoft.com/en-us/python/api/overview/azure/ai-ml-readme?view=azure-python

We are excited to introduce the GA of Azure Machine Learning Python SDK v2. The Python SDK v2 introduces new SDK capabilities like standalone local jobs, reusable components for pipelines and managed online/batch inferencing. Python SDK v2 allows you to move from simple to complex tasks easily and incrementally. This is enabled by using a common object model which brings concept reuse and consistency of actions across various tasks. The SDK v2 shares its foundation with the CLI v2 which is also GA. Source code | Package (PyPI) | Package (Conda) | API reference documentation | Product documentation | Samples This package has been tested with Python 3.7, 3.8, 3.9 and 3.10. For a more complete set of Azure libraries, see https://aka.ms/azsdk/python/all

I hope these helps you. Thank you!
Anonymous

2025-03-08T01:13:07.55+00:00

Hi Wasim Khan

Following up to see if the response was helpful.
Wasim Khan 20 Reputation points

2025-03-10T05:46:08.3666667+00:00

The question here is how can I run my custom python script for model training and reschedule it on weekly basis and the python script component in the Designer is outdated what are the alternate options available. I created a custom script job but that cannot be scheduled.
Anonymous

2025-03-11T18:31:25.2533333+00:00
Hi Wasim Khan

To run your custom Python script for model training and schedule it on a weekly basis in Azure Machine Learning, consider the following steps.

Instead of relying on the Execute Python Script component in the designer, you can create a pipeline that includes your custom Python script. This allows for more flexibility and the ability to incorporate various components.

Once you've created your pipeline, you can schedule it to run at regular intervals, such as weekly. This can be done using the Azure Machine Learning CLI, SDK, or the studio UI. You can create, retrieve, update, and deactivate schedules for your pipeline jobs.

If you prefer using custom script jobs, you can still schedule them by wrapping them in a pipeline. This way, you can leverage the scheduling capabilities of Azure Machine Learning while executing your custom scripts.

I hope these helps you. Thank you!
Wasim Khan 20 Reputation points

2025-03-12T14:11:19.14+00:00

Understood kothapally,
I have a Python script that works when using a custom script option in a job, but I am unable to find the option to schedule it.
Could you provide me with the steps of the process you mentioned above?
Anonymous

2025-03-13T16:26:27.1533333+00:00

Hi Wasim Khan

Following up to see if the response was helpful.
Wasim Khan 20 Reputation points

2025-03-13T16:50:23.3366667+00:00

This is helpful. Thanks for this deep clarification.

1 answer

Your answer

Wasim Khan 20 Reputation points

2025-03-04T10:59:04.1966667+00:00

I am using azure ml studio designer(classic) > Create a new pipeline using classic prebuilt components > components > Execute Python Script
Anonymous

2025-03-08T01:13:07.55+00:00

Hi Wasim Khan

Following up to see if the response was helpful.
Wasim Khan 20 Reputation points

2025-03-10T05:46:08.3666667+00:00

The question here is how can I run my custom python script for model training and reschedule it on weekly basis and the python script component in the Designer is outdated what are the alternate options available. I created a custom script job but that cannot be scheduled.
Anonymous

2025-03-11T18:31:25.2533333+00:00

Hi Wasim Khan

To run your custom Python script for model training and schedule it on a weekly basis in Azure Machine Learning, consider the following steps.

Instead of relying on the Execute Python Script component in the designer, you can create a pipeline that includes your custom Python script. This allows for more flexibility and the ability to incorporate various components.

Once you've created your pipeline, you can schedule it to run at regular intervals, such as weekly. This can be done using the Azure Machine Learning CLI, SDK, or the studio UI. You can create, retrieve, update, and deactivate schedules for your pipeline jobs.

If you prefer using custom script jobs, you can still schedule them by wrapping them in a pipeline. This way, you can leverage the scheduling capabilities of Azure Machine Learning while executing your custom scripts.

I hope these helps you. Thank you!
Wasim Khan 20 Reputation points

2025-03-12T14:11:19.14+00:00

Understood kothapally,
I have a Python script that works when using a custom script option in a job, but I am unable to find the option to schedule it.
Could you provide me with the steps of the process you mentioned above?
Anonymous

2025-03-13T16:26:27.1533333+00:00

Hi Wasim Khan

Following up to see if the response was helpful.
Wasim Khan 20 Reputation points

2025-03-13T16:50:23.3366667+00:00

This is helpful. Thanks for this deep clarification.

Answer 1

Hi Wasim Khan

Ensure you have an Azure subscription and create a workspace if you haven't done so.
Install the Azure CLI and the ml extension, or ensure you have the Azure Machine Learning SDK v2 for Python set up.
Create a job definition that includes your Python script. This can be done through the Azure CLI or the SDK.
Use the scheduling capabilities in Azure Machine Learning to set up a time-based schedule for your job. You can create a schedule based on elapsed time to handle routine tasks.
After creating the schedule, you can retrieve, update, or deactivate it as needed via CLI, SDK, or the studio UI.
kindly refer these https://learn.microsoft.com/en-us/azure/machine-learning/how-to-schedule-data-import?view=azuHope this helps. Do let us know if you any further queries.
If this answers your query, do click Accept Answer and Yes for was this answer helpful. And, if you have any further query do let us know.

I Hope these helps you. Thankyou!

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Azure ML studio designer python executor is outdated

1 answer

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