azureml
Microsoft Azure Machine Learning Python client library
Decision gist · record as of 2026-08-14
No. This package is abandoned and no longer maintained as of 2019. Microsoft explicitly directs users away from it to newer Azure ML resources. Unless you are maintaining legacy code that already depends on it, you should use the current Azure ML Python SDK instead. The endpoints and APIs may no longer work with modern Azure services.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires valid Azure ML Studio workspace ID and authorization token; endpoints may no longer be operational since the package is abandoned.
- Installation is straightforward with no compiled dependencies, but the package is abandoned as of 2019 and no longer maintained.
- The repository is archived and has not received updates in several years, making it unsuitable for new projects.
License · maintenance · safety
MIT License (permissive) — Licensed under the MIT License (permissive), which allows broad use, modification, and distribution with minimal restrictions.
last release 2016-03-14 (3805 days) · last repo commit 2019-06-28 · 90 stars · archived
0 known vulnerabilities (OSV.dev, 2026-08-14) · 206,514 downloads/mo, #9,569 on PyPI
Alternatives
Verify before relying
pip install azureml
from azureml import Workspace
ws = Workspace(workspace_id='your-id', authorization_token='your-token')
for ds in ws.datasets:
print(ds.name)
frame = ws.datasets[0].to_dataframe()- Whether this package works with current Azure ML Studio infrastructure or if the endpoints and APIs have changed since abandonment
- Compatibility with Python versions beyond 3.4, given the package was last tested with Python 2.7, 3.3, and 3.4
- Whether the REST endpoints this library connects to are still operational or have been superseded by newer Azure ML services
What it is and what it does
This is a legacy Python client library for Azure Machine Learning Studio that predates the modern Azure ML SDK. It allows you to authenticate to an Azure ML workspace, enumerate and access datasets stored there, and download them as Pandas DataFrames or raw binary/text data. You can also upload new datasets or update existing ones by serializing DataFrames back to the workspace. The library handles authentication via workspace ID and token, supports regional endpoints, and can read intermediate datasets from experiment outputs.
However, the package has been abandoned since 2019 and is no longer maintained. Microsoft has moved on to newer SDKs and platforms. The description itself notes that this content is no longer maintained and directs users to the Azure Machine Learning Notebooks project instead. The APIs and REST endpoints it connects to are subject to change and may no longer be compatible with current Azure ML infrastructure.
Use it for
- Retrieve datasets from an existing Azure ML Studio workspace into a local Python environment for analysis or preprocessing
- Upload processed data back to Azure ML Studio as a new dataset after manipulation in Pandas
- Access intermediate datasets from completed ML Studio experiments for further analysis or reuse
- Automate dataset synchronization between local Python scripts and Azure ML Studio in legacy workflows
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
No.
This package is abandoned and no longer maintained as of 2019. Microsoft explicitly directs users away from it to newer Azure ML resources. Unless you are maintaining legacy code that already depends on it, you should use the current Azure ML Python SDK instead. The endpoints and APIs may no longer work with modern Azure services.
Install
azureml on PyPI
Before you install
Installation is straightforward with no compiled dependencies, but the package is abandoned as of 2019 and no longer maintained. The repository is archived and has not received updates in several years, making it unsuitable for new projects.
Requires valid Azure ML Studio workspace ID and authorization token; endpoints may no longer be operational since the package is abandoned.
License in practice
Licensed under the MIT License (permissive), which allows broad use, modification, and distribution with minimal restrictions.
Quickstart
pip install azureml
from azureml import Workspace
ws = Workspace(workspace_id='your-id', authorization_token='your-token')
for ds in ws.datasets:
print(ds.name)
frame = ws.datasets[0].to_dataframe()Verify before relying
- Whether this package works with current Azure ML Studio infrastructure or if the endpoints and APIs have changed since abandonment
- Compatibility with Python versions beyond 3.4, given the package was last tested with Python 2.7, 3.3, and 3.4
- Whether the REST endpoints this library connects to are still operational or have been superseded by newer Azure ML services
Package facts
| License | MIT License permissive |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Abandoned 3,805 days since the last release |
| Last repo commit | repository archived |
| First released | |
| Downloads | 206,514 / month, #9,569 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaLicense :: OSI Approved :: MIT LicenseProgramming Language :: PythonProgramming Language :: Python :: 2Programming Language :: Python :: 2.7Programming Language :: Python :: 3Programming Language :: Python :: 3.3Programming Language :: Python :: 3.4 |
Evidence: azureml-0.2.7-py2.py3-none-any.whl
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See also azureml-mlflow · azureml-core · azureml-dataset-runtime · openml · azureml-fsspec · mltable · azureml-contrib-services · ucimlrepo · azureml-train-restclients-hyperdrive · azure-ai-ml