--- id: azureml version: "0.2.7" license: MIT License license_treatment: permissive maintenance: abandoned --- # azureml — Microsoft Azure Machine Learning Python client library License: permissive · Maintenance: abandoned · Downloads: 206.5K/mo ## 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 However, the package has been abandoned since 2019 and is no longer maintained.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 The description itself notes that this content is no longer maintained and directs users to the Azure Machine Learning Notebooks project instead.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 above — verify before relying. Connects to Azure Machine Learning Studio workspaces to download, upload, and manage datasets from Python, with optional conversion to and from Pandas DataFrames. No. This package is abandoned and no longer maintained as of 2019.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 pip install azureml uv add azureml poetry add azureml ## Installing azureml 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you install: Installation is straightforward with no compiled dependencies, but the package is abandoned as of 2019 and no longer maintained.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. 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() Requires valid Azure ML Studio workspace ID and authorization token; endpoints may no longer be operational since the package is abandoned. 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: unspecified - Install friction: low - Maintenance: abandoned - Downloads: 206.5K/month (top 15,000 on PyPI) - Known vulnerabilities: none known ## Tags azure machine learning studio client, download datasets from azure ml, azure ml workspace access, pandas dataframe azure ml, azure ml dataset management, azure studio python sdk, machine learning dataset sync, legacy, azure-ml, abandoned [View on SkillFed](https://skillfed.io/packages/azureml) · [View on PyPI](https://pypi.org/project/azureml/)