azure-mgmt-machinelearningcompute
Microsoft Azure Machine Learning Compute Management Client Library for Python
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 on this page — 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
azure-mgmt-machinelearningcompute on PyPI
pip
pip install azure-mgmt-machinelearningcomputeuv
uv add azure-mgmt-machinelearningcomputepoetry
poetry add azure-mgmt-machinelearningcomputeInstalling 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 | not specified |
| Install friction | low — pure-Python wheel |
| Runtime dependencies | 3 — msrestazure, azure-common, azure-mgmt-nspkg |
| Maintenance | actively maintained — 2,999 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 1,647,429/month — #3,690 on PyPI (30-day window, as of 2026-08-14) |
| Known vulnerabilities | none known (OSV.dev, checked 2026-08-14) |
Evidence: azure_mgmt_machinelearningcompute-0.4.1-py2.py3-none-any.whl
Tags
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