---
id: azure-mgmt-machinelearningcompute
version: "0.4.1"
license: MIT License
license_treatment: permissive
maintenance: active
---

# azure-mgmt-machinelearningcompute — Microsoft Azure Machine Learning Compute Management Client Library for Python

License: permissive · Maintenance: active · Downloads: 1.6M/mo

## What it is and what it does

This package is a Python client library for the Azure Machine Learning Compute Management API, part of Microsoft's Azure SDK for Python. It wraps Azure Resource Manager (ARM) endpoints to let you programmatically provision, configure, and tear down machine learning compute resources—clusters, nodes, and associated infrastructure—directly from Python code.

The library depends on msrestazure, azure-common, and azure-mgmt-nspkg to handle authentication, HTTP communication, and namespace management. It's designed for developers building automation, infrastructure-as-code tools, or integration layers that need to manage Azure ML compute at scale. The package has been tested against Python 2.7 and 3.4–3.6, though it has not received updates since 2018.

Use it for:

- Automate provisioning of Azure ML compute clusters as part of a CI/CD pipeline or infrastructure-as-code workflow.
- Build a multi-tenant ML platform that dynamically allocates compute resources based on workload demand.
- Delete and recycle compute clusters programmatically to control Azure spending and resource lifecycle.
- Integrate Azure ML cluster management into a custom orchestration or workflow tool written in Python.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Manages Azure Machine Learning Compute resources via the Azure Resource Manager API, providing Python bindings to create, configure, and delete compute clusters and related infrastructure.

Yes, if you are actively using Azure Machine Learning Compute and need programmatic management of clusters via Python. The package is stable, permissively licensed, and has no known vulnerabilities. However, verify that it aligns with your Azure SDK strategy—Microsoft has released newer, unified SDKs since 2018, so check whether your project should migrate to a more current client library to ensure long-term support.

## Install

pip install azure-mgmt-machinelearningcompute
uv add azure-mgmt-machinelearningcompute
poetry add azure-mgmt-machinelearningcompute

## Installing azure-mgmt-machinelearningcompute

Before you install: Low install friction with three stable Azure dependencies. Package is actively maintained with recent commits, though the latest release is from 2018; suitable for production use if your Azure ML workflows haven't migrated to newer SDK versions.

License in practice: MIT License permits commercial and private use with minimal restrictions, making it safe to adopt in most projects.

Quickstart:

pip install azure-mgmt-machinelearningcompute

from azure.mgmt.machinelearningcompute import MachineLearningComputeManagementClient
from msrestazure.azure_active_directory import AADTokenCredentials

credentials = AADTokenCredentials(token, client_id)
client = MachineLearningComputeManagementClient(credentials, subscription_id)

Requires Azure subscription credentials and appropriate AAD authentication setup; Python 2.7 or 3.4+ as tested in the package.

Verify before relying:

- Whether this package is still recommended for new Azure ML projects or if migration to newer unified SDK is required.
- Current support status for Python versions beyond 3.6, given the package's 2018 release date.

## Package facts

- License: MIT License (permissive)
- Python support: unspecified
- Install friction: low
- Maintenance: active
- Downloads: 1.6M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

azure machine learning compute management, azure arm api python client, azure cluster provisioning sdk, azure ml infrastructure as code, azure resource manager compute, azure-sdk, infrastructure-as-code, cloud-compute

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