---
id: azureml-fsspec
version: "1.4.0"
license: Proprietary https://aka.ms/azureml-preview-sdk-license 
license_treatment: unclear
maintenance: active
---

# azureml-fsspec — Access datastore uri with fsspec

License: unclear · Maintenance: active · Downloads: 171.1K/mo

## What it is and what it does

azureml-fsspec registers a custom fsspec filesystem handler for azureml:// URIs, bridging Azure Machine Learning datastores and Python's data-processing ecosystem. It lets you use fsspec's abstraction layer to read and write files directly from Azure ML datastores without manual credential management or intermediate downloads.

The package wraps fsspec around azureml-dataprep and pytz, handling URI parsing, authentication (including service principal and managed identity), and registry lookups. It is maintained by Microsoft, actively updated for recent Python versions (3.12, 3.13 support added in 1.4.0), and designed for data scientists and ML engineers working within Azure ML environments.

Use it for:

- Access training data from an Azure ML datastore via fsspec without downloading files locally.
- Read parquet or CSV files from Azure ML datastores for distributed processing.
- Integrate Azure ML datastores into existing fsspec-based workflows without rewriting data-loading logic.
- Automate data pipeline steps that reference Azure ML datastore paths using fsspec APIs.
- Support hybrid ML workflows where Azure ML is the central data repository.

## Worth the install?

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

Provides a filesystem interface to Azure Machine Learning datastores via fsspec, allowing you to access data files using azureml:// URIs with standard data-processing libraries.

Yes, if you work within Azure Machine Learning and need fsspec access to datastores. Install friction is low and maintenance is active. The proprietary license requires review before use in commercial or redistributed products. No known security vulnerabilities as of the latest release.

## Install

pip install azureml-fsspec
uv add azureml-fsspec
poetry add azureml-fsspec

## Installing azureml-fsspec

Before you install: Low install friction with a pure-Python wheel. Maintenance is active; the latest release (1.4.0) is recent and addressed setuptools compatibility issues in azureml-dataprep, a key runtime dependency.

License in practice: Licensed under a proprietary Microsoft license (Proprietary https://aka.ms/azureml-preview-sdk-license). License treatment is unclear; review the linked license terms before use in commercial or redistributed contexts.

Quickstart:

pip install azureml-fsspec

import fsspec
fs = fsspec.filesystem('azureml')
files = fs.ls('azureml://subscriptions/{sub_id}/resourcegroups/{rs_group}/workspaces/{ws}/datastores/workspaceblobstore/paths/myfolder')

Requires Python 3.10–3.13 and valid Azure Machine Learning subscription, resource group, workspace, and datastore credentials.

Verify before relying:

- Whether the proprietary license permits commercial use or redistribution without explicit Microsoft agreement.
- Authentication flow details beyond mlclient support (e.g., service principal, managed identity setup steps).
- Performance characteristics or limits when working with large datasets via fsspec.

## Package facts

- License: Proprietary https://aka.ms/azureml-preview-sdk-license  (unclear)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 171.1K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

azure machine learning datastore filesystem, fsspec azure ml integration, azureml uri file access, azure datastore fsspec handler, ml datastore file interface, azure-ml, data-access

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